Mentally Disordered Offenders Under Community Supervision Research Paper

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Offenders with serious mental illness (schizophrenia, bipolar, major depression) are overrepresented in criminal justice settings. Most offenders – both with and without mental illness – are not incarcerated but instead are supervised in the community on probation and parole. Offenders with serious mental illness are more likely to fail on community supervision than their relatively healthy counterparts. With a focus on community supervision in North America, this research paper distills research on (1) explanations for why offenders with mental illness are at increased risk for supervision failure and (2) promising-and evidence-based practices for reducing this risk.

Statement Of The Problem

Overrepresentation Of Offenders With Mental Illness

Of the 7.2 million people under correctional supervision (Bureau of Justice Statistics 2011), nearly one-sixth have a serious mental illness (SMI; Fazel and Danesh 2002). Disorders that fall under this classification include schizophrenia (i.e., symptoms such as delusions and hallucinations, disorganized thought processes, and even catatonia), bipolar disorder (i.e., fluctuations in mood and activity levels that range from severely depressive to manic), and major depressive disorder (i.e., intense feelings of sadness and anhedonia). All three disorders can severely affect daily functioning. The current rates of SMI in correctional populations are approximately three times higher for men and twice as high for women than that found in the general population (see Teplin 1990; Kessler et al. 2006).

Community Supervision Failure

The majority (~70 %) of offenders both with and without SMI are supervised in the community on probation or parole (Bureau of Justice Statistics 2011). While on community supervision, offenders with SMI are at greater risk of failure (i.e., breach supervision and return to custody in jail or prison) than offenders without SMI. Based on a cohort of 45,000 California State parolees (20 % of whom were pre-identified as having a mental illness), Eno Louden and Skeem (2011) found that those with mental disorder were more than three times more likely to have parole revoked (i.e., terminated) than those without mental disorder. Moreover, those with acute (i.e., severe, sudden increase/onset of symptoms) mental illness had even higher rates of return to custody than parolees with more stable (i.e., ongoing, managed symptoms) mental illness. Similarly, in an unpublished dissertation that compared 115 probationers with SMI to 518 randomly selected non-disordered probationers, Dauphinot (1996) found that probationers with SMI were more likely to be arrested (54 %) and revoked (37 %) than those without SMI (30 %, 24 %, respectively) over a 3-year follow-up.

Technical violations appear to be an especially problematic concern for offenders with SMI. Relative to non-disordered offenders, offenders with SMI have disproportionately high rates of technical violations and are more likely to fail community supervision failure as a result of a technical violation. This finding has been demonstrated in a small sample of Canadian federal offenders (37 SMI vs. 37 non-disordered; Porporino and Motiuk 1995) and parolees in New York (147 SMI vs. 400 non-disordered; Feder 1991) and California (Eno Louden and Skeem 2011). All three studies indicate significant proportional differences between offenders with SMI and non-disordered offenders in their failure due to technical offenses. One study, in particular, showed that the relative risk of supervision failure due to technical violations (vs. person, property, drug, and minor offenses) is almost twice as great for offenders with SMI (52.9 %) than non-disordered (29.7 %) offenders (Eno Louden and Skeem 2011).

The Link Between Mental Illness And Recidivism

Several explanations for community supervision failure among offenders with SMI have been proposed. Skeem and colleagues (2006, 2011) provide a framework for understanding three important paths to failure for offenders with SMI. The first two paths, direct and indirect proximal effects, keep the role of mental illness central to the equation (see Skeem and Eno Louden 2006). The third path by which offenders with SMI can fail community supervision de-emphasizes mental illness as a proximal or immediate cause of supervision failure. Instead, this path views mental illness as a distal factor that is related to – or mediated by – other, stronger predictors of supervision failure (see Skeem et al. 2011). Although these pathways can overlap, evidence for each of these three routes is distilled separately below.

The Proximal Direct Route

The direct route between mental illness and community supervision failure suggests that symptoms of mental illness lead directly to criminal behavior. For example, someone may experience hallucinations in the form of voices compelling them to engage in an illegal act (e.g., theft). In this particular case, the criminal act is directly attributable to the experience of psychotic symptoms.

Although lay people may endorse beliefs that support a link between mental illness and crime or violence, the empirical evidence suggests such beliefs may be unfounded. In fact, among offender samples, mental illness is either unrelated or negatively correlated with future criminal behavior. In a meta-analysis conducted by Bonta et al. (1998), p. 35 predictors of general recidivism and 27 predictors of violent recidivism were examined across 64 unique samples. A clinical domain, comprised of clinical variables such as psychosis, treatment history, mood disorder, and current mental disorder, showed significant negative effects for both general (r =-.02) and violent recidivism (r =-.03; for a recent update, see Quinsey et al. 2006).

Even though mental illness does not predict recidivism for the majority of offenders with SMI, the symptoms of mental illness may directly lead to criminal behavior for a small proportion of offenders. In one study, 113 individuals with mental illness in a jail diversion program were interviewed about the cause of their index offense. Three independent raters used a 100-point scale (definitely not [0] to definitely [100]) with 5 point increments to rate the likelihood that the offense was attributable to either “the specific influence of concurrent delusions or hallucinations on the criminal offense identified in the police arrest report” or “any other symptom-based influence, such as confusion, depression, thought disorder, or irritability” (Junginger et al. 2006, p. 880). Results indicated that the index offense for only about 8 % of the sample was attributable to the symptoms of mental illness.

In a similar study, Peterson et al. (2010) matched 111 parolees with SMI to 109 parolees without SMI and examined their pattern of offending using official parole records. Parolees were classified into one of five groups based on their offense patterns by four independent raters: (1) psychotic (violent offenses driven by delusions or hallucinations), (2) disadvantaged (survival crimes such as shoplifting), (3) reactive (crimes driven by hostility or impulsivity), (4) instrumental (goal-driven crimes that involve manipulation or deceit), or (5) gang or drug related. Here, the offense pattern was attributable to psychosis in only 5 % of the parolees with SMI. Although replication is needed, the two studies taken together emphasize the importance of the link between mental illness and crime for a small proportion of offenders – less than 10 %. Meanwhile, the relationship between mental illness and crime for the majority of offenders with SMI may be better understood through other avenues, which are reviewed next.

The Proximal Indirect Route

This second avenue by which offenders with SMI can fail community supervision also emphasizes a proximal link between psychiatric symptoms and failure, but this route is indirect. In this path, offenders with SMI are believed to fail supervision not because their psychiatric symptoms lead to criminal behavior but because these symptoms lead to another outcome such as declined functioning or substance use. This third variable then leads to the termination of supervision.

For instance, it could be that the symptoms of mental illness prevent offenders on community supervision from doing what is required of them. If a supervisee is severely depressed and physically unable to get out of bed to attend probation or parole appointments, he could incur a technical violation or even be revoked for noncompliance. Alternatively, supervision can be revoked due to the inability to stay clean and sober – a standard condition of community supervision. Indeed, having SMI raises the likelihood of a co-occurring substance disorder; almost 75 % of offenders with SMI also have a substance use problem (James and Glaze 2006; Abram and Teplin 1991). In both scenarios, mental illness leads to the failure of meeting conditions of community supervision, which can then lead to revocation.

The Third Variable Route

The final pathway of the mental illnessrecidivism link suggests that a third variable – not mental illness – is actually responsible for community supervision failure. In this route, something that is separate from – but related to – mental illness can explain supervision failure. The mental health status of the individual remains important, but it is viewed as a distal variable that exposes offenders to more proximal factors that contribute to supervision failure.

The research examining this “third variable” route has identified two very distinct but important factors that contribute to the community supervision failure of offenders with SMI. The first factor, the role of supervision practices among probation and parole officers, demonstrates a truly spurious relationship of the mental illness-recidivism link. The research on this topic suggests the manner in which an officer supervises an offender can directly affect the offender’s criminal justice outcomes. This process can occur with offenders with and without SMI, but there are some concerns that officers’ stigmatizing attitudes about mental illness can influence officers’ supervision style with this population in particular. The second factor, an offender’s criminogenic risk, demonstrates a mediated relationship between mental illness and recidivism. Here, mental illness exposes individuals to risk factors that strongly relate to criminal behavior (e.g., poverty, antisocial associates).

Supervising Officer Effects. Officer orientation (i.e., guiding viewpoint) toward rehabilitation versus public safety can influence offenders’ outcomes, whether they have mental illness or not. In a seminal ethnographic study of 7,000 probationers and parolees and their supervising officers, Klockars (1972) found that officer supervision orientation characterized by extreme emphasis on law enforcement/control or social casework/rehabilitation, as opposed to a blend of these approaches, can negatively affect supervisees’ outcomes. Decades later, Paparozzi and Gendreau (2005) provided further evidence to support this theory when they examined similar supervision styles (punishment, social casework, and balanced) in a matched sample comparing 142 parolees on intensive supervision to 142 offenders on standard parole. Offenders who had “balanced” officers were least likely to be revoked for any offense or due to a new conviction than offenders who had punishment oriented or strictly social casework-oriented officers.

Results from these studies of general offenders likely also apply to offenders with SMI, and recent evidence indicates that officers may be particularly likely to adopt these supervision strategies with offenders with SMI. Doing so can adversely affect their outcomes. In other words, officers may be inclined to supervise offenders with SMI in ways that increase their likelihood of returning to custody.

In an experimental study, Eno Louden and Skeem (2013) presented 234 probation officers with a vignette portraying a probationer with mental disorder, substance abuse, both, or neither. Officers were asked to provide risk assessment ratings for the probationers then predict how they would supervise that probationer if he were placed on their caseload. Officers judged probationers with mental disorder, particularly schizophrenia, as being at high risk for both new offense and violence, compared to probationers with no disorder or only substance abuse. Specifically, officers estimated that a probationer with schizophrenia had a 68.6 % chance of committing a new offense and a 55.2 % chance of committing violence while on probation, compared to 49.3 % and 39.0 %, respectively, for a probationer with no mental disorder. Further, they also sought to monitor these probationers closely via frequent meetings – wanting to meet with a probationer with schizophrenia an average of 6.1 times per month compared to 3.3 times per month for a probationer with no disorder (Eno Louden and Skeem 2013). Other research has shown that closer supervision can increase detection of noncompliance, particularly for technical violations (Petersilia and Turner 1993; Paparozzi and Gendreau 2005). Although much work remains to be done on why officers may hold certain beliefs about the risk of offenders with mental illness and the reasons for supervising them more closely, the strong influence officers have on supervisees’ outcomes is apparent.

Shared Criminogenic Risk. In addition to officer effects, another “third variable” that has a strong influence on community supervision failure of offenders with SMI is criminogenic risk (e.g., risk factors related to criminal behavior). As established through several comprehensive metaanalytic studies, the strongest risk factors for criminal behavior – dubbed the “central eight” – are history of antisocial behavior; antisocial personality pattern; antisocial cognition; antisocial associates; family and marital instability; deficits in school or work aptitude, productivity, or motivation; lack of pro-social leisure and recreational pursuits; and substance use (see Andrews et al. 2004, 2006; Andrews and Dowden 2006). Research suggests that the criminogenic risk factors most strongly related to recidivism in non-disordered offenders also predict recidivism for offenders with SMI (Bonta et al. 1998).

In fact, mental illness may disproportionately expose offenders with SMI to specific criminogenic risk factors such as poverty and antisocial associates that lead to community supervision failure. Several studies have indicated that not only do offenders with and without SMI share the same risk factors for recidivism but also that those with SMI actually are higher on many general criminogenic risk factors. In one study of 627 offenders with and without mental health problems (defined as the presence of depression, psychosis, prior suicide threats or attempts, and other emotional distress), Girard and Wormith (2004) found higher risk/needs scores for offenders with mental illness than those without mental illness on an Ontario version of the Level of Service Inventory, a variation of the popular, well-validated risk assessment. Moreover, the relationship between offenders’ specific risk/needs profile and general recidivism was stronger for those with mental health problems than those without them. In another study, Skeem et al. (2008) examined 112 parolees with SMI and 109 parolees without SMI and found those with SMI had higher general (total scores) and specific risk/needs profiles on the Level of Service/Case Management Inventory (LS/CMI; Andrews et al. 2004) than non-disordered parolees.

Routes Of Supervision Failure: A Summary

In summary, the relationship between mental illness and community supervision failure for offenders with SMI is complex. There are various routes by which offenders with SMI fail community supervision. For a small proportion of offenders with SMI, community supervision failure is directly attributable to the symptoms of mental illness. However, the symptoms of mental illness can also influence a trajectory of noncompliant behavior that leads to technical violations, an especially problematic concern for this group. For the majority of offenders with SMI, however, supervision failure is likely attributable to criminogenic risk factors that are shared with non-disordered offenders. Finally, and perhaps to a lesser extent, the specific supervision styles and strategies employed by community corrections officers can also play an important role in community supervision failure. Equipped with an understanding of how offenders with SMI can fail community supervision, this research paper now turns to an overview of the current approaches used to supervise offenders with SMI in the community, highlights their evidence base, and discusses the strengths and weaknesses of the current policy model in light of this empirical evidence.

Strategies For Supervising Offenders With SMI In The Community: Specialty Mental Health Caseloads

Perhaps the most common current approach employed in the community supervision of offenders with SMI is specialty mental health caseloads. The last decade has seen increasing implementation of specialty mental health caseloads to manage offenders with SMI on community supervision. In 2002, the Council of State Governments recommended the implementation of specialty caseloads in response to the problem of supervision failure for this population and the growing concerns about the consequences of offenders with SMI becoming more deeply entrenched in the criminal justice system. At the time of this recommendation, there was unfortunately no data to support the effectiveness of implementing this type of caseload, nor did the recommendation include directives for establishing specialty caseloads. Since that time, Skeem et al. (2006) conducted a national survey of specialty mental health probation. This study provided some basic insight into what these caseloads look like in practice.

Although there is heterogeneity in how specialty mental health caseloads are implemented across jurisdictions, they do share five distinct features: (1) reduced caseload sizes, relative to non-specialty caseloads, (2) caseloads comprised solely of offenders with SMI, (3) officer interest or training in mental health, (4) coordination of internal (i.e., probation) and external (i.e., treatment) resources, and (5) emphasis on problem-solving over sanctioning (Skeem et al. 2006). Additionally, specialty mental health community supervision places a very strong emphasis on mental health treatment (psychiatric medications and therapy). In doing so, as argued elsewhere (see Skeem et al. 2011), these programs make an implicit assumption that symptom reduction can lead to improved criminal justice outcomes.

Perhaps the most rigorous examination of specialty probation performed to date is that recently completed by Skeem and colleagues. In this study, 183 offenders with SMI on specialty mental health probation were matched to 176 probationers with SMI on traditional probation on the following criteria: age, gender, race, time on probation, and index offense. Probationers and their supervising probation officers were followed over the course of 1 year. During this time, probationers completed three semi-structured interviews – one approximately 2 months after beginning probation and again 6 and 12 months later. Officers completed questionnaires on the same schedule. Participants’ official criminal justice outcomes (FBI arrests rap sheets and violation and termination reports filed with the court) were collected 2 years post baseline.

Two important preliminary findings have emerged from this study. First, what officers do in specialty supervision differs from what they do in traditional supervision. Specifically, specialty probation officers used more problem-solving strategies than threats and sanctions, had better skills in navigating and working with outside social service agencies (i.e., “boundary spanning”), and established better relationships with their supervisees than officers in traditional probation supervision (Manchak et al. 2007). Additionally, offenders with SMI on specialty probation received more evidence-based integrated dual diagnosis treatment (i.e., treatment that targets mental health and substance use symptoms simultaneously) than those on traditional probation (Manchak et al. 2010). Second, specialty probation reduced recidivism but not for reasons that were expected. Effectiveness of specialty probation was not mediated by probationers’ symptom reduction but by high-quality officer-probationer relationships characterized by firmness, caring, and trust (Skeem et al. 2010). These findings would suggest that the implicit model guiding practices like specialty supervision may be flawed; effective officer practices – not treatment – appear to be essential for affecting outcomes for offenders with SMI.

Moving Research Into Practice: Prescribing Evidence-Based Practices


The available research on specialty caseloads underscores the importance of what is already being emphasized in correctional intervention with general offenders: “Core Correctional Practices” (CCP). First discussed by Andrews and Kiessling (1980), these practices place strong emphasis on how correctional interventions are implemented. Appropriate use of authority, modeling, behavioral reinforcement, and problem-solving are viewed as essential CCPs. Additionally, CCPs entail linking offenders to needed community resources and services. Perhaps most important, however, is the establishment of strong relationships between supervisees and probation and parole officers; these relationships are most effective when they are characterized by warmth, flexibility, empathy, openness, mutual respect, and liking and use “directive, solution-focused, structured, non-blaming, or contingency-based communication” (Dowden and Andrews 2004, p. 208). A meta-analysis of 273 effect sizes shows that the relationship component correlates strongly with average effect sizes in recidivism reduction (r =.25), and the additional CCP components enumerated above can increase this correlation (r= .41–.47; Dowden and Andrews 2004).

Other work that has come to dominate the landscape of general correctional intervention, and which is slowly beginning to take hold in policy recommendations with offenders with SMI (see Prins & Draper, 2009), is the application of the principles of effective intervention: risk, need, and responsivity (RNR). These principles suggest that (1) intensity of supervision should be matched to the offender’s individual level of risk (risk principle), (2) supervision should focus on the primary criminogenic risk factors known to relate to recidivism (need principle), and (3) the manner in which supervision is delivered should be consistent with the offender’s learning style and abilities (responsivity principle). Like CCP, adherence to the RNR model can substantially reduce recidivism risk among general offenders. One meta-analysis, for example, found an average reduction of 20–38 % (depending on how many principles were applied) among high-risk offenders (Andrews and Dowden 2006). Additionally, the more time officers spend discussing criminogenic needs in supervision, the greater the reduction in recidivism (Bonta et al. 2008).

Although little is known about how well officers use RNR practices when supervising offenders with SMI, there is some evidence that suggests they may intuitively apply these principles without being specifically trained to do so. In an investigation of a specialty mental health probation agency, Eno Louden et al. (2012) examined audiotaped meetings between 83 probation officer-probationer pairs and coded them for adherence to these principles. Although the most common topic discussed in these meetings was issues related to probationers’ general mental health, officers also discussed probationers’ criminogenic needs. One-third of meetings (33.7 %) included discussion of criminogenic needs that are most predictive of recidivism (antisocial attitudes, antisocial personality, criminogenic peers), and three-quarters of these meetings (75.9 %) also included discussion of criminogenic needs moderately predictive of recidivism (financial problems, employment, family problems, and substance abuse). Thus, supervision practices in specialty mental health caseloads may already adhere in some respects to important components of RNR.


Even though officers may unintentionally employ the evidence-based practices of RNR and interact with supervisees in ways consistent with core correctional practices, greater recidivism reduction for offenders with SMI is more likely achieved through officer training and effective implementation practices. There are several important steps that must be taken to do so effectively. First, researchers must be able to communicate their findings to practitioners in a manner that is not only accessible but also conveys the value of adopting new evidence-based practices. Directors and frontline staff must recognize the short-and long-term benefits of these practices and be committed to ensuring their implementation. Second, agencies need to be provided with guidance in the application of these practices. Without proper training, certain evidence-based practices may be misinterpreted or misapplied, therefore undermining their intended goal of recidivism reduction. Finally, safeguards must be in place to ensure the sustainability of the evidence-based practices. For example, procedures should be in place for training new hires and maintaining quality control in the long term.

Several scholars in the USA and Canada are already making strides in bridging this researchpractice gap. Researchers at George Mason University and the University of Cincinnati have been actively involved in training correctional officers in the application and use of RNR and CCP using innovative implementation strategies and rigorous training protocols. Agencies such as Policy Research Associates and the National GAINS Center have also made significant contributions to both research and practice by disseminating their findings on correctional programs for offenders with SMI, in particular. Such programs are essential in translating the research evidence into real-world practice in an accurate, ethical, and efficient manner.


The research supporting the various routes to supervision failure among offenders with SMI has informed the current policy model recommended by the Council of State Governments for managing this population on probation or parole. This model provides a classification system for offenders with SMI where offenders are classified and managed based on their individual level of criminogenic risk, issues with substance abuse/dependence, and the severity of the individual mental health symptoms and functioning (D’Amora et al. 2012). In accordance with the risk principle, the model recommends that services in each domain be contingent upon severity of problems. For example, high criminogenic risk is matched by more intensive supervision that adheres to the RNR principles. Severe substance problems are met with intensive substance abuse treatment and, if coupled with mental illness, integrated dual diagnosis treatment. Finally, for those with severe mental health symptoms and poor psychosocial functioning, more intensive psychiatric treatment is proscribed. For offenders who are “high” in mental health, substance use, and criminogenic risk, integration of intensive services and supervision is recommended.

Extensive evidence now indicates that there is little utility in emphasizing the role of mental illness in recidivism, except for a small minority of offenders with SMI. As policy and practice shifts away from mental illness as the master status around which correctional interventions and programming are designed, future research should seek to identify new approaches to reducing recidivism for offenders with SMI. Even more, efforts should be made to identify the mechanisms by which (i.e., mediators) and the conditions under which (moderators) current evidence-based practices operate. Doing so can maximize recidivism reduction for this population. Current and forthcoming research examining the effectiveness of practices like specialty caseloads and RNR will continue to help refine the policy model guiding interventions and improve outcomes for offenders with SMI.


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