CJ Discussion

Law Hum Behav (2006) 30:659–674 DOI 10.1007/s10979-006-9061-9

ORIGINAL ARTICLE

Mental Health Court Outcomes: A Comparison of Re-Arrest and Re-Arrest Severity Between Mental Health Court and Traditional Court Participants

Marlee E. Moore · Virginia Aldigé Hiday

Published online: 12 October 2006 C© American Psychology-Law Society/Division 41 of the American Psychological Association 2006

Abstract Mental health courts have been proliferating across the country since their estab- lishment in the late 1990’s. Although numerous advocates have proclaimed their merit, only few empirical studies have evaluated their outcomes. This paper evaluates the effect of one mental health court on criminal justice outcomes by examining arrests and offense severity from one year before to one year after entry into the court, and by comparing mental health court participants to comparable traditional criminal court defendants on these measures. Multivariate models support the prediction that mental health courts reduce the number of new arrests and the severity of such re-arrests among mentally ill offenders. Similar analysis of mental health court completers and non-completers supports the prediction that a “full dose” of mental health treatment and court monitoring produce even fewer re-arrests.

Keywords Mental health court . Diversion . Coerced treatment

Introduction

Over one hundred mental health courts have been established since their origins in the late 1990’s to tackle the inadequacy of the criminal justice system to deal effectively with mentally ill defendants (Redlich, Steadman, Monahan, Petrila, & Griffin, 2005). More specifically, mental health courts were created to reduce recidivism among mentally ill offenders and in so doing reduce courtloads, and local jail and prison overcrowding while insuring public safety (Goldkamp & Irons-Guynn, 2000; Petrila, Poythress, McGaha, & Boothroyd, 2000). This paper presents data from one such court to address the question of whether mental health courts reduce criminal recidivism among persons with mental illness.

This paper was presented to the American Psychology and Law Society, St. Petersburg, FL, March 2006. It is based on the first author’s doctoral dissertation.

M. E. Moore · V. A. Hiday (�) Department of Sociology and Anthropology, North Carolina State University, Raleigh, North Carolina 27695-8107 e-mail: ginny [email protected]

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The mentally ill jail and prison population has soared in the United States over the last 25 years such that persons with mental disorders constitute from 6% to 22% of all inmates, depending on definition, methodology and demographic group (Ditton, 1999; Hiday and Wales, 2003; Teplin, 1990; Teplin, Abram, & McClelland, 1996). Lack of services and admission difficulties, especially for substance abusing persons with serious mental illness, cause police to take persons with mental disorders to jail rather than to a hospital or other psychiatric facility (Teplin, 1990). This practice, often referred to as criminalization of mental illness, has persisted to the point that urban jails in some states house more persons with mental illness than do their state mental hospitals (Torrey, 1995). Despite the large numbers of mentally ill offenders in jails and prisons, most are ill equipped to provide mental health services to persons with mental illness and few do more than a minimum (Morris, Steadman, & Veysey, 1997; Schaefer & Stefancic, 2003). Seldom are offenders linked to community services upon their exit from jail (Morris et al., 1997), effectively leaving them to fend for themselves. Lack of adequate mental health treatment and needed supports for these offenders has led to a revolving door syndrome of arrest, jail or probation, and release back in the community, where, with little or no resources, re-offending starts the cycle again (Broner, Lattimore, Cowell, & Schlenger, 2004; Lamb, Weinberger, & Reston-Parham, 1996; Steadman, Cocozza, & Veysey, 1999).

Awareness of these problems brought criminal justice, mental health, and other professionals to advocate for diversion programs (Petrila et al., 2000; Steadman et al., 1999; Steadman, Morris, & Dennis, 1995). Rather than punish offenses caused by a mental illness and its effects, these programs use the leverage of the criminal justice system to obtain mental health and social services for mentally ill offenders to address the underlying problems.

Mental health courts, one such diversion program, are modeled on drug courts having 1) a separate docket for mentally ill defendants, 2) a dedicated judge, who presides at the initial hearing and subsequent monitoring sessions, 3) dedicated prosecution and defense counsel; 4) a nonadversarial team approach which involves joint decision-making between criminal justice and mental health professionals, 5) voluntary participation by defendants agreeing to follow a treatment regimen, 6) monitoring by the court, and 7) promise of dismissed charges or avoidance of incarceration, depending on whether the court follows a pre or post adjudication model (Goldkamp & Irons-Guynn, 2000; Petrila et al., 2000; Watson, Hanrahan, Luchins, & Lurigio, 2001).

Background

Because of their relatively recent development, little data exist on the effectiveness of mental health courts. What we know comes mainly from descriptive articles and a few empirical studies that focus on processes and procedures, not criminal recidivism (Boothroyd, Poythress, McGaha, & Petrila, 2003; Goldkamp & Irons-Guynn, 2000, Griffin, Steadman, & Petrila, 2002; McGaha, Boothroyd, Poythress, Petrila, & Ort, 2002; Poythress, Petrila, McGaha, & Boothroyd, 2002; Redlich, Steadman, Monahan, Petrila, & Griffin, 2005; Steadman, Davidson, & Brown, 2001).

To date, there are three published studies reporting criminal outcomes of mental health courts. Trupin and Richards (2003) compared two groups of mentally ill offenders who were referred to Seattle’s two mental health courts: those who opted in and those who opted out. The “Opt-Ins” had significantly fewer bookings over an average nine months period after entry into the courts than they did in a comparable time before entry and fewer bookings compared to the “Opt-Outs.”

The second study in Broward County, Florida, found mental health court defendants’ mean number of arrests significantly decreased from one year pre to one year post mental health court entry; however, their mean number of re-arrests, felony arrests, proportion re-arrested, and survival time to re-arrest were not significantly different than comparable defendants in

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a traditional criminal court in a nearby jurisdiction (Christy, Poythress, Boothroyd, Petrila, & Mehra, 2005). On the other hand, mental health court defendants spent significantly less time in jail for index offenses; thus, they were at risk of re-arrest longer than were the comparison group.

Cosden and colleagues (2003, 2005) went further than these two studies in designing an experimental random control trial in Santa Barbara with severely mentally ill offenders. Random assignment was for 18 months to either the mental health court with assertive community treatment (MHTC) or to traditional criminal court with treatment as usual, consisting of less intensive case management (TAU). After one year, mental health court participants had fewer convictions for new crimes than the control group. Charges of the MHTC participants who were convicted were usually related to probation violations rather than commission of a new crime; whereas charges of control group subjects tended to be for new offenses (Cosden, Ellens, Schnell, Yamini-Diouf, & Wolfe, 2003). After two years (18 months treatment and 6 months post), the small proportions of each group sent to prison for new crimes did not differ significantly. Excluding those in prison and MHTC participants jailed for noncompliance, both MHTC and TAU participants had increased bookings, and no change in either convictions or jail days. Because there was a group of offenders with disproportionately excessive bookings, convictions and jail days, Cosden and colleagues (2005) conducted a separate analysis on all others, finding a significant decline in jail days for both MHTC and TAU participants from the two years pre- participation to the two years after study entry, although finding no significant decline in either bookings or convictions, and no significant difference between MHTC and TAU on any of the three measures of criminal activity.

These three studies are important in showing that mentally ill offenders are at no increased risk for reoffending when diverted from jail following entry into a mental health court than comparable defendants in traditional criminal court; thus, they show that mental health courts are meeting their obligation of protecting public safety. These studies, however, are not as clear concerning the impact of mental health courts on criminal justice recidivism above that of traditional criminal courts. In the Seattle study, the comparison groups were self-selected which introduced unknown bias. Furthermore, reported treatment differences between the mental health court “Opt-Ins” and “Opt-Outs” show mixed results or are unclear. In the Santa Barbara study with its random control design and specified differences in treatment, MHTC participants received more intensive case management (ACT) and other supports than did control group defendants (Cosden et al., 2003, 2005). Because mentally ill offenders can be diverted to ACT absent a mental health court and because ACT programs have been shown to have more positive outcomes for persons with serious mental illness than other forms of treatment (Bond, McGrew, & Fekete, 1995; Mueser, Bond, Drake, & Resnick, 1998), it is unclear whether it was the court or the services which impacted one year convictions. In Broward County, almost half (45.2%) of mental health court defendants had no mental health services in the follow-up period and only 36% of mental health court defendants returned to the court for monitoring (Boothroyd et al., 2003). Because it is insuring access to mental health treatment and services, and the monitoring of compliance with them that are the mechanisms by which mental health courts are expected to effect change, one cannot judge the impact of mental health courts on recidivism for defendants not treated and not monitored.

Purpose

This paper evaluates the impact on criminal recidivism of one mental health court (MHC) which works with mental health providers to assure defendants receive treatment and services, and which regularly monitors compliance with treatment plans (Hiday, Moore, Lamoureaux, &

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de Magistri, 2005). We examine a mental health court in its ability to reduce not only re-offending but also recividism severity over a twelve month period for mentally ill defendants as compared to similar defendants in a traditional criminal court (TCC) who were not self-selected.

We take analyses of mental health court outcomes a step further by providing a breakdown of MHC subjects as determined by their completion status in the court. Making a distinction between MHC completers (graduates) and non-completers (those returned to TCC for adjudication of their cases) is substantively important when evaluating the effectiveness of a mental health court because it is a full “dose” of mental health court rather than a partial “dose” which is predicted to make the difference; that is, the combination of the treatment, services, structure, supervision, and encouragement under court monitoring for a sustained time is what is predicted to reduce recidivism. Making this distinction is critical because simply opting into a mental health court does not guarantee any monitoring or reception of treatment and services, much less any beneficial impact; it only provides an open door to introduce services and the structure within which a beneficial impact can occur. A different but related measure, length of time in a program, has been associated with lower levels of re-arrests and other positive outcomes for offenders involved in drug treatment programs (Peters, Haas, & Hunt, 2001; Swartz, Lurigio, & Slomka, 1996; Wexler, Falkin, & Lipton, 1990). We propose that it is not just days in mental health court which impacts recidivism because time to obtain needed treatment and services and to effect consistent compliance varies with individual clinical and social conditions. Although more time in mental health court increases the likelihood of obtaining treatment and services, and thus, the likelihood of positive changes, some defendants may never indicate a willingness to change despite their volunteering for a mental health court.

The setting

The observed MHC is located in a county in the Southeastern United States having a rural population and a small county seat in one half, with the other half having an urban population and university town with research spin-offs. It hears cases of persons with mental illness and/or substance abuse disorders who have been charged with criminal misdemeanor or felony offenses. The dedicated assistant DA screens defendants referred to MHC to ascertain they do not pose threats to public safety as determined by the nature of current offenses and criminal histories of serious violence. A violent offense in and of itself is not cause for exclusion; rather the degree and circumstances of the violence determine exclusion. Mental illness is initially determined for docketing by community or criminal justice labeling based on inappropriate behavior and/or a mental health treatment history; but is confirmed with a diagnosis after MHC screening.

The MHC, held once a month in each of the county’s two towns, hears approximately 5 new cases and monitors approximately 25 on-going cases a month at each location. Before court begins, decision-making occurs behind closed doors by the MHC Team, consisting of the dedicated judge, assistant district attorney, public defender, two private attorneys on the indigent list, and mental health liaison, and at times one or more probation officers, mental health case managers, and privately retained attorneys. Mental health clinicians have primary responsibility for design of treatment plans which may include group and individual therapy, medication, anger management, housing and employment assistance, social services, and vocational training; but the full MHC Team provides structure, supervision, and encouragement for each defendant.

Defendants who elect to go through MHC and agree to their treatment plans1 are required to come to court for monitoring monthly for at least six months. In open court the judge talks

1 Defendants’ competency is not a MHC issue because questions of a defendant’s competency to stand trial would preclude referral and participation in the MHC. Such questions would have been previously addressed by the

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with each defendant about progress over the past month and any troubles experienced. Focus is on making behavioral changes, cooperating with treatment, and solving practical problems hindering the changes and cooperation, not on psychiatric diagnosis or symptoms. Depending on compliance, the judge gives praise and encouragement, delivers a stern lecture, issues a warning or threat, or transfers the defendant back to TCC.

At the end of continuous and consistent six-months of compliance with treatment and court appearances, and no new arrests, defendants graduate from MHC, at which time all charges are dismissed or probation is ended. In cases of non-compliance, the court continues to monitor the defendant beyond six months until the MHC Team deems the defendant has fulfilled all mandated provisions and can graduate; thus, time to graduation is variable. Although having volunteered, some defendants never begin a “dose,” dropping out of MHC before treatment, as soon as the structure impinges on their behavior. The other non-completers begin a “dose” but never fully engage in treatment and/or resist the structural requirements. After numerous failed attempts to develop a working relationship with them, the MHC Team ejects them back to TCC. In all these cases, the non-completers never experience the potential benefits of compliance with the “prescribed dose.”

In TCC, cases are adjudicated in adversarial court proceedings in which defendants are found either guilty or not guilty. Those found guilty receive traditional court sanctions such as fines, probation and/or incarceration. Regardless of case outcome in TCC, defendants tend not to be connected to mental health services.

Method

Research design

Random assignment into experimental (MHC) and control group (TCC) was not feasible because eligible participants could not be denied the opportunity to participate in MHC for ethical reasons.2 We used a nonequivalent comparison group design in which the researcher selects subjects for the comparison group as alike as possible to the experimental group on crucial variables, in this case mental illness and arrest, and statistically controls for other relevant variables in analyses, in this case age, race, gender, prior criminal history, prior jail time, and severity of current charge.

Participants

The experimental group (MHC sample, N = 82) consists of all defendants who were deemed eligible and chose to participate in the MHC from September 2001 through August 2002. We do not know the number of defendants who were referred for MHC but refused by the dedicated assistant DA or were offered MHC by counsel but refused. We do know that of 115 new cases appearing on the MHC docket during the intake year, 14 returned to TCC because they were screened as not mentally ill (eight) or because they raised public safety concerns (six), 11 chose not to participate in (opted out of) MHC; and three had their charges dismissed between

TCC’s referral for competency to stand trial evaluation on the recommendation of the DA, defense counsel, judge or jail services. 2 The benefits of mental health services (Mueser et al., 2002; Ziguras & Stuart, 2000; Wahlbeck, Cheine, Essali, & Adams, 1999) assured by MHC participation and the inability to provide such services for those in TCC would mean that TCC assignment would be assignment to no treatment, an unethical protocol.

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docketing and their first hearing. We omitted five eligible participants because they classified themselves as a race other than white or African American.

The comparison group (TCC sample, N = 183) consists of similar offenders whose cases were in TCC in the same county the year before the MHC was established (1998).3 No change in court officers, law, policy, or funding was made in the county in the time interval between the two samples other than establishing the MHC and funding the MH liaison for the MHC Team. Public criminal records list 12,748 arrests representing 6231 defendants for the county in 1998. From this list the chief district court judge, who led the founding of this MHC and is one of two dedicated MHC judges, identified 185 offenders who would have been eligible for MHC had it been in existence, that is offenders who are mentally ill with or without substance abuse and pose no public safety threat. TCC sample selection is, thus, based on the judge’s knowledge of community labeling and/or treatment history which is not a scientific method of determining mental illness. It is, however, the method of initial selection into MHC, albeit by only one member of the MHC Team; but unlike MHC defendants, these selected TCC defendants had no diagnostic confirmation. Two of them were omitted because they were in the MHC sample, yielding a control group of 183 TCC defendants. As one would expect of this population (mentally ill with or without substance abuse and not a threat to public safety), the 183 averaged significantly more arrests in 1998 than those not selected, t = 2.98, 6621 df, p < .01); but their average number of arrests in the year prior to their key arrest is not significantly different from that of the MHC sample in the year prior to their key arrest, t = 1.67, 263 df).

Because only data of public record (age, race, gender, offense types, offense dates, judgments and sentences) were obtained (from the state computerized database), informed consent was not necessary. The university’s and the county mental health center’s institutional review boards (IRBs) along with court officers of the judicial district approved the research design.

Measurement

Recidivism. This variable, used to determine the court’s impact on re-arrest of defendants with mental illness, is operationalized in two ways: 1) number of new arrests occurring during the twelve months following key entry into either the MHC or TCC; and 2) a summation scale indicating recidivism severity. This scale uses offense values from the state’s “Structured Sentencing Guidelines” (N.C. Sentencing and Policy Advisory Commission, 2004) plus traffic citations which are important in MHC Team decisions. Each of sixteen states using structured sentencing guidelines ranks offenses according to its evaluation of offense seriousness for purposes of sentencing (Bureau of Justice Assistance, 2004). In North Carolina, misdemeanors have four levels of seriousness; and felonies, nine levels, with traffic citations not ranked. We coded traffic citations 1; misdemeanors, from 2 to 5 with 5 being the most serious; and felonies, from 6 to 14 with 14 being the most serious. In the case of more than one offense with an arrest, only the most serious offense was coded. For each defendant, a severity variable was computed that summed the values of the most serious offense for each new arrest (See Appendix for examples of defendants at each severity score in the range represented by our sample.).

Court type. The independent variable of central interest is the type of court which heard each defendant’s case, coded TCC (0) or MHC (1).

3 We could not use two other possible comparison groups: mentally ill offenders in a similar county in the state, without a MHC, and mentally ill offenders in the study county in TCC. In the first instance, there was no comparable county; and in the second, mentally ill offenders in the study county who were in TCC would be those who declined to participate in MHC, which would present obvious selection bias.

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Completion status. We also focus on a second independent variable, completion status. To be considered a completer, one must consistently and continuously fulfill the MHC Team’s treatment recommendations for six months and, thus, graduate. Conversely, non-completers are individuals who opt into the MHC, and never begin a treatment plan or begin one but do not successfully complete it and, thus, are returned to TCC. Three criminal history and three demographic variables (prior criminal record, jail time served pre-court, severity of key arrest offense, race, gender, and age) serve as controls.

Prior criminal record is measured as the number and severity of arrests in the twelve months prior to first entry in the MHC for the experimental group and as the number and severity of arrests in the twelve months prior to the date of key arrest in 1998 for the comparison group. Prior severity is calculated as described for recidivism severity.

Jail time served in prior year is the second indicator of severity of criminal history. It is coded as no time spent in jail (0) or some time spent in jail (1) during the 12 months prior to key arrest.

Severity of key arrest offense is assessed for MHC subjects as the severity of the most serious offense of the arrest for which a defendant was referred to MHC. For TCC subjects, it is the most serious offense of the arrest in 1998 that made a defendant eligible for sample selection. Severity of key arrest offense is categorized using the Structured Sentencing Guidelines code as described earlier.

Demographics. Race (white = 0, African-American = 1), gender (male = 0, female = 1), and age (actual years) are the control variables. An indicator of SES (income, education, occupation) is desirable, but is not available in court records.

Methods of analysis

Analyses include a descriptive bivariate summation of variables by court type and by court completion status. Descriptive statistics are used to identify similarities and differences between TCC and MHC subjects as well as within the MHC. Such a comparison sheds light on how comparable the experimental and comparison groups are at the outset of the evaluation and how similar MHC completers and non-completers are. Next, we compare the groups on our outcome variables. Last, multivariate analyses are performed using both measures of recidivism and employing different regression techniques as determined by the distribution of the dependent variables; however, each regression model uses the same independent and control variables.

Findings

Comparability of the groups

Table 1 presents an overview of the samples with demographic, criminal history, and recidivism comparisons between TCC and MHC subjects as well as between MHC completers and non- completers. One can observe significant differences between TCC and MHC subjects on age and race, but not on gender. TCC subjects are significantly younger than MHC subjects, t = 4.13, 263 df, and more heavily African American, χ2 = 5.52, 263 df.

Of the criminal history control variables the two groups are not significantly different in mean number of prior arrests, severity of key arrest offense, or percent spending time in jail in the year prior to key arrest. Average score on prior offense severity scale and number of days spent in jail in the year prior to key arrest are significantly different. TCC subjects have a higher average prior offense severity score, t = 2.14, df = 263, indicating more serious offenses in the year prior to key arrest, and averaged more days in jail in the year prior to key arrest, t = 2.65, 189 df.

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Table 1 Sample characteristics by type of court and completion status

Total sample TCC (n = 183)

Total sample MHC (n = 82)

MHC MHC- Completer (n = 52)

MHC MHC- Noncompleter (n = 30)

Recidivism Average number of times re-arrested 2.36∗∗∗ 1.10 0.58 2.03###

(Range) (0–15) (0–6) (0–6) (0–6) Average severity of recidivism 9.46∗∗∗ 3.90 2.06 7.13###

(Range) (0–72) (0–24) (0–24) (0–23) Criminal history controls

Average number of prior arrests 1.69 1.21 0.96 1.67 (Range) (0–8) (0–8) (0–8) (0–8) Average prior offense severity 6.62∗ 4.13 3.04 6.03 (Range) (0–44) (0–40) (0–25) (0–40) Average severity of key arrest 4.39 4.06 3.96 4.23 (Range) (1–13) (1–12) (1–12) (1–12) Average days in jail- prior year 7.21∗∗ 0.49 0.50 0.47 (Range) (0–330) (0–180) (0–30) (0 to 180) Percent spending time in jail in prior year 11.48% 4.88% 2.00% 10.00%

Demographic controls Average age 30.08∗∗ 35.65 36.23 34.66

Race Black 54.6%∗ 39.02% 32.69% 50.00%

Gender Men 72.68% 68.29% 69.23% 66.67%

∗p < .05, ∗∗p < .01, ∗∗∗p < .001, #p < .05, ##p < .01, ###p < .001. ∗Indicates a significant difference between court type. #Indicates a significant difference between completers and non-completers.

Almost two-thirds of MHC defendants completed treatment and behavior mandates, and graduated; while 36.6% were non-completers and returned to TCC. Over one-fourth of non- completers (26.7%) left MHC early (in the first two months) without accessing scheduled treatment or services. The other non-completers were persistently noncompliant after beginning treatment and court monitoring; thus, the MHC Team sent them back to TCC. There is no significant difference in any demographic variable or any criminal history variable between completers and non-completers.

Bivariate analysis

Both measures of recidivism, the two dependant variables, are significantly different between defendants of the two courts as seen in Table 1. TCC subjects are re-arrested significantly more often than MHC subjects during the 12 months follow-up, t = 4.21, 248 df. The same pattern appears in the recidivism severity scale: TCC subjects score significantly higher than MHC subjects on the recidivism offense severity scale, t = 4.38, 262 df. Completers and non-completers differ significantly on both measures of recidivism with non-completers being arrested more often, t = 3.47 (Satterthwaite correction for unequal variances), 41.3 df, and for more serious offenses, t = 3.16 (Satterthwaite correction for unequal variances), 42.8 df.

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Table 2 Negative binomial regression models predicting the rate of re-arrest (N = 265)

Model 1 Model 2 Model 3 Coefficient (b) Coefficient (b) Coefficient (b)

Explanatory variables IRR (se) IRR (se) IRR (se)

Mental health court 0.47∗∗∗ − 0.75 (.21) 0.53∗∗ − .62 (.20) 0.55∗∗ − .59 (.21) Prior offense severity

score 1.02∗∗ .03 (.01) 1.02∗∗ 0.03 (.01)

Severity of key arrest 1.05 .06 (.04) 1.05 0.05 (.04) Jailed prior year 1.27 .24 (.30) 1.29 0.25 (.30) Age 0.99 − .00 (.00) Race 0.99 − .00 (.18) Gender 0.96 − .03 (.20) Model chi-square 12.53∗∗∗ 25.10∗∗∗ 25.39∗∗∗

Note. IRR stands for incident rate ratio.

Standard errors (se) are in parentheses. ∗∗∗p < .001; ∗∗p < .01; ∗p < .05.

Regression analyses: Rate of re-arrest

Given the nature and distribution of the dependent variable re-arrest, a count variable with many zero values (57.3% MHC and 38.8% TCC defendants were not rearrested and thus have a zero value; 73.1% MHC completers and 30.0% non-completers were not rearrested) and, therefore, not normally distributed, negative binomial regression models are used to determine efficient, unbiased estimates of the relationship between court type and re-arrest4 (StataCorp, 2003). Table 2 presents these models, sequentially adding groups of control variables. Model 1, showing the basic bivariate relationship, indicates that MHC subjects’ rate of re-arrest is less than half (47%) that of those in TCC. In Model 2, the addition of criminal history variables slightly decreases the effect of court type but it remains significant. One also sees that the number and severity of prior offenses are significantly related to the rate of re-arrest: as the criminal history offense severity scale increases by one, the rate of re-arrest increases by 2.9%. This finding echoes other research that indicates a major predictor of future criminal behavior among mentally ill offenders is past criminal behavior (Bonta, Law, & Hanson, 1998; Ulmer, 2001). Demographic variables added in Model 3 are nonsignificant and do not change the effect of other independent variables on re-arrest.

In Table 3, completers and non-completers are compared to TCC subjects on the rate of re-arrest. Model 1 indicates that completers are re-arrested at a rate that is less than one-fourth (24%) that of TCC defendants, but non-completers are not significantly different from TCC defendants. Re-estimating the model with MHC non-completers as the reference category to compare completers with non-completers, we find completers to be re-arrested only 28% the rate of non-completers.

Model 2 adds criminal history control variables to the regression equation. Completion status in MHC remains significant; those who completed the MHC are re-arrested at a rate a little more than one-fourth (28.6%) that of TCC subjects. As in the previous analysis of MHC participation, severity of criminal history is the only criminal history control variable significantly related to

4 Poisson and negative binomial models were examined to determine the better model for predicting re-arrest. The LR statistic was significant which provides evidence of over dispersion; thus, the negative binomial model is the better model for predicting re-arrest (Long, 1997).

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Table 3 Negative binomial regression model predicting the rate of re-arrest (N = 265)

Model 1 Model 2 Model 3 Coefficient (b) Coefficient (b) Coefficient (b)

Explanatory variables IRR (se) IRR (se) IRR (se)

MHC-Completer 0.24∗∗∗ − 1.41 (.27) 0.28∗∗∗ − 1.25 (.26) 0.29∗∗∗ − 1.22 (.27) MHC-Non completer 0.86 − .15 (.27) 0.95 − .04 (.27) 0.99 − .01 (.28) Score on prior offense

severity scale 1.02∗∗ 0.02 (.01) 1.02∗∗ 0.02 (.01)

Severity of key charge 1.05 0.06 (.04) 1.05 0.05 (.04) Jailed pre-court 1.23 0.21 (.29) 1.24 0.22 (.29) Age 0.99 − 0.00 (.00) Race 1.00 0.01 (.18) Gender 0.96 − 0.03 (.20) Model χ2 25.09∗∗∗ 37.13∗∗∗ 37.46∗∗∗

Degrees of freedom 2 5 8

Note. IRR stands for incident rate ratio. ∗p < .05, ∗∗p < .01, ∗∗∗p < .001.

the rate of re-arrest; and demographic variables added in Model 3 are neither significant nor change the effect of the main independent variable on re-arrest.

Re-arrest offense severity

To examine the MHC’s impact on re-arrest severity above and beyond the probability of re-arrest for those who did have an arrest during the follow-up, two stages of modeling are necessary. The first stage uses logistic regression to obtain the odds of any re-arrest for use in the next stage of analyses. Although this step is quite similar to earlier negative binomial models, it is necessary to obtain the probability of having some score on the recidivism offense severity scale. The second stage of analyses uses OLS regression to regress all of the independent and control variables as well as the probability of re-arrest on the recidivism offense severity scale only for those who were re-arrested (N = 147). Table 4 presents these models.

Table 4 Logistic regression model predicting the odds of re-arrest and OLS regression model predicting recidivism severity by court type

Logistic regression (N = 265) OLS regression (N = 147) Odds of re-arrest Recidivism severity

Explanatory variables Odds ratio Confidence intervals Coefficient (b) SE b

Mental health court 0.63 0.88–2.81 − 7.80∗ 4.03 Prior offense severity score 1.07∗∗∗ 1.03–1.12 0.38 0.34 Severity of key arrest 1.02 0.90–1.17 1.55∗∗ 0.59 Jailed prior year 3.33 0.91–12.1 1.15 6.10 Age 0.98 0.96–1.01 − 0.06 0.14 Race 1.40 0.82–2.40 1.47 3.04 Gender 0.95 0.54–1.70 − 0.82 2.51 Probability of re-arrest − 19.98 26.90 Model χ2 38.82∗∗∗

R square 0.10 0.10

∗p < .05, ∗∗p < .01, ∗∗∗p < .001.

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Table 5 Logistic regression model predicting the odds of re-arrest and OLS regression model predicting recidivism severity by court status

Logistic regression (N = 265) OLS regression (N = 147) Odds of re-arrest Recidivism severity

Explanatory variables Odds ratio Confidence intervals Coefficient (b) SE b

MHC-Completer 0.33∗∗ 0.16–0.69 − 8.99 7.60 MHC-Non completer 1.78 0.74–4.32 − 3.88 4.17 Prior offense severity score 1.07∗∗∗ 1.03–1.12 0.22 0.31 Severity of key arrest 1.02 0.90–1.17 1.43∗∗ 0.58 Jailed prior year 3.07 0.84–11.23 − 1.45 5.53 Age 0.98 0.96–1.01 − 0.02 0.14 Race 1.32 0.77–2.30 0.53 2.75 Gender 0.39 0.52–1.69 − 0.82 2.53 Probability of re-arrest − 7.33 25.49 Model χ2 49.79∗∗∗

R square 0.13 0.09

∗p < .05, ∗∗p < .01, ∗∗∗p < .001.

In predicting the odds of being re-arrested (or having some score on the recidivism of- fense severity scale), only criminal history offense severity scale has a significant, though small effect. Lack of significant effects of MHC as compared to TCC differs from the ear- lier negative binomial model because the dichotomous coding of the dependent variable, re- arrest, results in the loss of information as compared to its previous coding as a count vari- able. When used as a count variable, re-arrest more extensively tells the story of the MHC’s effectiveness.

The second stage of modeling using OLS regression to predict the severity of recidivism only for those who were re-arrested during the follow up period indicates MHC is significant. Participants in MHC score 7.80 points lower on the recidivism offense severity scale than those in TCC controlling for other variables in the model. Severity of key arrest is also significant: as it increases by one unit, score on the recidivism offense severity scale goes up by 1.55 all else held constant.

Table 5 presents the same analysis for completers and non-completers. When looking at the odds of re-arrest, being a MHC completer and score on the criminal history severity scale are significant. Those who completed MHC have lower odds of re-arrest: one-third the odds of those in TCC, all else held constant; and when re-estimating the model with non-completers as the reference category, completers have 81% the odds of re-arrest of non-completers. In addition, as the prior offense severity scale increases by one, the rate of re-arrest increases 7%.

Stage two of the analyses predicting severity of rearrest offenses indicates only sever- ity of key arrest is significant. Among those rearrested, neither MHC completers nor non- completers are significantly different from TCC defendants on the rearrest severity scale. When the model is re-estimated with MHC non-completers as the reference category (not shown), completers are not significantly different from non-completers. That completion status is not significant indicates that the positive effect of being a MHC completer is seen in the re- duced probability of re-arrest and not in the severity of re-arrest once re-arrest is taken into account.

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670 Law Hum Behav (2006) 30:659–674

Discussion

This study examined the impact of one mental health court in reducing recidivism among mentally disordered defendants as compared to similar defendants in a traditional criminal court. Our results provide support for the expectation that mental health courts reduce the number of new arrests among this population. MHC defendants had a re-arrest rate about half that of similar defendants in TCC. Those who completed the MHC program had an even lower re-arrest rate, less than one-fourth that of TCC defendants; while that of non-completers was not significantly different from that of TCC defendants. As predicted, it was the full dose of mental health court, rather than a partial dose, which made the difference in reducing arrests. Analytically this finding is important in highlighting the need to distinguish those who do and do not complete a mental health court program of treatment, services, structure, supervision and encouragement when evaluating its success. This finding also has programmatic and political significance in pointing to the necessity of completing the program in order for a mental health court to reduce recidivism.

It could be argued that causation runs the other way, that is re-arrest caused non-completion of MHC; but three facts undermine such an argument: 1) Re-arrest alone did not lead to being sent from MHC back to TCC as members of both non-completer and completer groups were arrested at least once while participating in MHC (46.7% and 11.5% respectively); 2) arrested non-completers’ date of termination from MHC did not follow shortly the date of arrest (average number of days from re-arrest to MHC termination = 97.7, SD = 79.6); and 3) each non- completer failed to engage with treatment or had a pattern of treatment non-compliance which the MHC Team interpreted as an unwillingness to work with the MHC to change their lives. In precourt team meetings and in open court, we observed that the MHC Team’s decision to return a defendant to TCC was based on such non-engagement and/or non-compliance.

It could also be argued that MHC recidivism was less than TCC recidivism because police refrained from arresting mentally ill offenders they knew to be in MHC. Although this is a possibility, no report came to the MHC Team of police not arresting a MHC defendant who offended while participating in MHC. On the other hand, police arrested some of them as stated above. No other MHC or drug court study has reported whether re-arrest rates were lower because police knowledge of defendant participation in these specialty courts.

Unlike the three earlier MHC studies, we did not use days spent in jail after entry into the MHC as either an outcome measure or as a control for time at risk of re-arrest because defendants were seldom in jail at time of entry; and, as other MHCs, few were sanctioned for noncompliance or new offenses by being incarcerated in jail (Griffin et al., 2002; Redlich et al., 2005). Only seven defendants spent time in jail after entry into MHC, and those seven averaged 82 days in jail (One completer spent 30 days in jail; six non-completers averaged 91 days in jail). Only 18 defendants in our TCC sample spent time in jail after their key offense, averaging 132 days in jail. MHC defendants as a whole averaged 6 days more at risk in the community for offending and being arrested than the TCC sample as a whole (358 versus 352 days at risk); but still the MHC sample had significantly fewer arrests.

It should be noted that as with outpatient commitment, a court order to community treatment and services does not assure that treatment and services will be received or that the person ordered will cooperate in treatment (Hiday, Swanson, Swartz, Borum, & Wagner, 2002). Treatment and services must be available and must be accompanied by outreach and monitoring for such difficult-to-engage populations (Hiday, 2003). Unfortunately, treatment and services are in short supply in most communities; thus, a MHC, even one that closely monitors defendants, will be limited in its impact by that supply.

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Law Hum Behav (2006) 30:659–674 671

Although we did not measure treatment and services received by our sample members, we know from observation of both pre-court meetings and open court that all MHC com- pleters obtained and consistently complied with their court ordered treatment and services for a minimum of six months; and that MHC non-completers either had access to or ob- tained court ordered treatment and services until their noncompliance led to their return to TCC. In contrast, TCC sample members were unlikely to have obtained treatment and ser- vices because no program existed in the county at that earlier time to address the needs of mentally ill offenders or to divert them from the criminal justice system. Those who may have been informally diverted would not have had the structured support and mon- itoring provided to MHC defendants, which we hypothesize to be necessary for reduced recidivism.

Despite rigorous efforts to ensure the adequacy of the research design, this study has some methodological limitations. First, the two samples were not similar on all variables at the outset. Having significant differences in age, race, and prior offense severity could have im- pacted the findings; but regression modeling permitted controlling these variables. To confirm that the recidivism differences were not caused by initial sample differences, we conducted Paired T Tests of Matched Samples using subsamples from the two courts matched on race and criminal history severity scale score (not shown). In these pre-post test analyses, MHC defendants had no significant decline in arrests or severity; but TCC defendants got worse, hav- ing significant increases in both their average number and severity of arrests (Moore & Hiday, 2005).

A second limitation was not having random assignment leaving the adequacy of sample selection for TCC defendants contingent on the chief district court judge’s ability to assess which defendants would have been selected for MHC had it been in existence at that time. Because the court is located in two small towns in one relatively small county and the judge has long served on the bench, he is familiar with a majority of defendants processed in criminal court; however, he would have missed persons with mental illness arrested in the county that year who were transient or temporary residents, who had only one lifetime offense, or whose mental illness was not publicly labeled. Although he may have remembered, and thus selected, those with more notable symptoms, such selection bias should not have affected the dependent variables because clinical factors have little effect on recidivism (Bonta et al., 1998). On the other hand, selection bias from the judge’s remembering those who appeared more frequently in court would be expected to affect recidivism; but our comparison sample did not have more prior arrests. It did have greater severity of prior offenses which we controlled in the multivariate analyses.

Third, caution should be taken because official measures of criminal offending were used for the outcome; thus, any criminal activity that went undetected by police is not included in the dependent variable. Using self-report data as well as official records, Christy and col- leagues (2005) found mental health court defendants to have significantly fewer violent acts at eight months than traditional criminal court defendants despite the two groups’ being no different on arrests. Finally, we followed defendants for only one year after entry into the MHC. Although all of them had graduated or been returned to TCC, follow-up time after that was limited, ranging from 0 to 11 months. How long will a mental health court’s effect on recidivism last? To the extent that graduates continue to receive helpful supports (treatment and services), and continue with their behavioral changes, one can expect continued reduced recidivism. Given the chronicity of severe mental illness and the multiple disadvantages of many of their lives, such supports will be needed well into the future if the reduced recidivism is to continue.

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672 Law Hum Behav (2006) 30:659–674

Appendix

Examples of most serious offense of each re-arrest for three defendants at each severity score in the range represented by our sample members

Severity score

Examples of defendants

1 one arrest = expired registration one arrest = window tinting violation one arrest = reckless driving

2 one arrest = trespassing one arrest = shoplifting one arrest = violation of a court order

3 one arrest = resisting arrest one arrest = defrauding an innkeeper one arrest = carrying a concealed weapon

4 one arrest = possession of drug paraphernalia one arrest = misdemeanor larceny two arrests = trespassing and public urination

5 one arrest = assault one arrest = breaking and entering two arrests = carrying a concealed weapon and urinating in public

6 two arrests = injury to real property and disorderly conduct two arrests = misdemeanor larceny and public urination two arrests = resisting arrest and concealment of merchandise

7 one arrest = obtaining property by false pretenses (felony) three arrests = trespassing, resisting arrest, and open container three arrests = shoplifting, worthless check, beer on a public street

8 one arrest = forgery two arrests = larceny and possession of marijuana three arrests = larceny, intoxicated and disruptive, and trespassing

9 two arrests = felony larceny and trespassing three arrests = possession of stolen goods, traffic violation, and fictitious information to a police officer

three arrests = forgery, concealment of merchandise, disorderly conduct 10 two arrests = felony breaking and entering, and worthless check

two arrests = assault on a female, assault three arrests = violation of a protective order, resisting arrest, intoxicated and disruptive

Acknowledgments The authors wish to thank Stacy de Coster, Rodney Engen, Anne Schiller, Catherine Zimmer, Heathcote Wales, and Kathleen Hartford for their insightful criticism and suggestions.

References

Bond, G. R., McGrew, J. H., & Fekete, D. M. (1995). Assertive outreach for frequent users of psychiatric hospitals: A meta-analysis. Journal of Mental Health Administration, 22, 4–16.

Bonta, J., Law, M., & Hanson, K. (1998). The prediction of criminal and violent recidivism among mentally disordered offenders: A meta-analysis. Psychological Bulletin, 123, 123–142.

Boothroyd, R. A., Poythress, N. G., McGaha, A., & Petrila, J. (2003). The Broward mental health court: Process, outcomes and service utilization. International Journal of Law and Psychiatry, 26, 55–71.

Springer

Law Hum Behav (2006) 30:659–674 673

Broner, N., Lattimore, P. K., Cowell, A. J., & Schlenger, W. E. (2004). Effects of diversion on adults with co- occurring mental illness and substance use: Outcomes from a national multi-site study. Behavior Sciences and the Law, 22, 519–541.

Bureau of Justice Assistance. (2004). National Assessment of Structured Sentencing. (Available at www.ncjrs.org/pdffiles/strsent.pdf).

Christy, A., Poythress, N. G., Boothroyd, R. A., Petrila, J., & Mehra, S. (2005). Evaluating the efficiency and community safety goals of the Broward County mental health court. Behavioral Sciences and the Law, 23, 1–17.

Cosden, M., Ellens, J., Schnell, J., Yamini-Diouf, Y., & Wolfe, M. (2003). Evaluation of a mental health court with assertive community treatment. Behavioral Sciences and the Law, 21, 415–427.

Cosden, M., Ellens, J., Schnell, J., & Yamini-Diouf, Y. (2005). Efficacy of a mental health treatment court with assertive community treatment. Behavioral Sciences and the Law, 23, 199–214.

Ditton, P. M. (1999). Mental health treatment of inmates and probationers. Bureau of Justice Special Reports, U.S. Department of Justice, NCJ: 174463.

Goldkamp, J., & Irons-Guynn, C. (2000). Emerging Judicial Strategies for the Mentally Ill in the Criminal Caseload: Mental Health Courts in Fort Lauderdale, Seattle, San Bernardino, and Anchorage. Bureau of Justice Assistance NCJ: 182504.

Griffin, P. A., Steadman, H. J., & Petrila, J. (2002). The use of criminal charges and sanctions in mental health courts. Psychiatric Services, 53, 1285–1289.

Hiday, V. A. (2003). Outpatient commitment: The state of empirical research on its outcomes. Psychology, Public Policy and Law, 9, 8–32.

Hiday, V. A., Moore, M. E., Lamoureaux, M., & de Magistri, J. (2005). North Carolina’s mental health court. Popular Government, 70(3), 24–29.

Hiday, V. A., Swanson, J. W., Swartz, M. S., Borum, R., & Wagner, H. R. (2002). Impact of outpatient commitment on victimization of persons with severe mental illness. American Journal of Psychiatry, 159, 1403–1411.

Hiday, V. A., & Wales, H. W. (2003). Civil commitment and arrests. Current Opinion in Psychiatry, 16, 575–580. Lamb, H., Weinberger, L., & Reston-Parham, C. (1996). Court intervention to address the mental health needs of

mentally ill offenders. Psychiatric Services, 47(3), 275–281. Long, J. S. (1997). Regression Models for Categorical and Limited Dependent Variables. Thousand Oaks, CA:

Sage. McGaha, A., Boothroyd, R. A., Poythress, N. G., Petrila, J., & Ort, R. G. (2002). Lessons from the Broward

County mental health court evaluation. Evaluation and Program Planning, 25, 125–135. Moore, M. E., & Hiday, V. A. (2005, July). Evaluation of a Mental Health Court: Recidivism Offense Outcomes

for Matched Samples. Paper presented at the International Congress of Law and Mental Health, Paris, France. Morris, S., Steadman, J., & Veysey, B. (1997). Mental health services in United States jails: A survey of innovative

practices. Criminal Justice and Behavior, 24(1), 3–19. Mueser, K. T., Corrigan, P. W., Hilton, D. W., Tanzman, B., Schaub, A.,Gingerich, S., et al. (2002). Ilness

management and recovery: A review of the research. Psychiatric Services, 53, 1272–1284. Mueser, K. T., Bond, G. R., Drake, R. E., & Resnick, S. G. (1998). Models of community care for severe mental

illness: A review of research on case management. Schizophrenia Bulletin, 24, 37–74. North Carolina Sentencing and Policy Advisory Commission. (2004). Structured Sentencing Training and Ref-

erence Manual. (Available at www.nccourts.org/courts/CRS/Councils/spac/Documents/trainingandreference manual2004.pdf)

Peters, R., Haas, A., & Hunt, W. (2001). Treatment ‘dosage’ effects in drug court programs. In J. Hennessy & N. Pallone (Eds.), Drug Courts in Operation: Current Research. NY: Haworth Press.

Peters, R. H., & Osher, F. C. (2004). Co-occurring Disorders and Specialty Courts (2nd ed.) Delmar, NY: The National Gains Center.

Petrila, J., Poythress, N. G., McGaha, A., & Boothroyd, R. A. (2000). Preliminary observations from an evaluation of the Broward County Florida mental health court. Court Review (fall), 20–28.

Poythress, N. G., Petrila, J., McGaha, A., & Boothroyd, R. A. (2002). Perceived coercion and procedural justice in mental health court. International Journal of Law and Psychiatry, 25, 517–533.

Redlich, A. D., Steadman, H. J., Monahan, J., Petrila, J., & Griffin, P. A. (2005). The second generation of mental health courts. Psychology, Public Policy and the Law, 11(4), 527–538.

Schaefer, N., & Stefancic, A. (2003). Alternative to prison programs for the mentally ill offender. Journal of Offender Rehabilitation, 38(2), 41–55.

StataCorp. (2003). Stata Statistical Software: Release 8.0. College Station, TX: Stata Corporation. Steadman, H. J., Cocozza, J., & Veysey, B. (1999). Comparing outcomes for diverted and nondiverted jail detainees

with mental illness. Law and Human Behavior, 23(6), 615–627. Steadman, H. J., Davidson, S., & Brown, C. (2001). Mental health courts: Their promise and unanswered questions.

Psychiatric Services, 52, 457–458.

Springer

674 Law Hum Behav (2006) 30:659–674

Steadman, H. J., Deane, M., Morrissey, J., Westcott, M., Salasin, S., & Shapiro, S. (1999). A SAMHSA research initiative assessing the effectiveness of jail diversion programs for mentally ill persons. Psychiatric Services, 50(12), 1620–1623.

Steadman, H. J., Morris, S., & Dennis, D. (1995). The diversion of mentally ill persons from jails to community based services: A profile of programs. American Journal of Public Health, 85(12), 1630–1635.

Steadman, H. J., Redlich, A. D., Griffin, P., Petrila, J., & Monahan, J. (2005). From referral to disposition: Case processing in seven mental health courts. Behavioral Sciences and the Law, 23, 215–226.

Swartz, J., Lurigio, A., & Slomka, S. (1996). The impact of IMPACT: An assessment of the effectiveness of a jail-based treatment program. Crime and Delinquency, 42(4), 553–573.

Teplin, L. A. (1990). The prevalence of serious mental disorder among male urban jail detainees: Comparison with the epidemiologic catchment area program. American Journal of Public Health, 80, 663–669.

Teplin, L. A., Abram, K. M., & McClelland, G. M. (1996). The prevalence of psychiatric disorder among incarcerated women: 1. Pretrial jail detainees. Annals of General Psychiatry, 53, 505–512.

Torrey, E. F. (1995). Jails and prisons: America’s new mental hospitals. American Journal of Public Health, 85, 1611–1613.

Trupin, E., & Richards, H. (2003). Seattle’s mental health courts: Early indicators of effectiveness. International Journal of Law and Psychiatry, 26, 33–53.

Ulmer, J. (2001). Intermediate sanctions: A comparative analysis of the probability and severity of recidivism. Sociological Inquiry, 71(2), 164–193.

Wahlbeck, K., Cheine, M., Essali, A., & Adams, C. (1999). Evidence of clozapine’s effectiveness in schizophrenia: A systematic review and meta-analysis of randomized trials. American Journal of Psychiatry, 156, 990–999.

Watson, A., Hanrahan, P., Luchins, D., & Lurigio, A. (2001). Mental health courts and the complex issue of mentally ill offenders. Psychiatric Services, 52(4), 477–481.

Wexler, H., Falkin, G., & Lipton, D. (1990). Outcome evaluation of a prison therapeutic community for substance abuse treatment. Criminal Justice and Behavior, 17(1), 71–92.

Ziguras, S. J., & Stuart, G. W. (2000). A meta-analysis of the effectiveness of mental health case management over 20 years. Psychiatric Services, 51, 1410–1421.

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