This article was downloaded by: [Gebze Yuksek Teknoloji Enstitïsu ] On: 22 December 2014, At: 15:42 Publisher: Routledge Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK
Journal of Offender Rehabilitation Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/wjor20
What Factors Work in Mental Health Court? A Consumer Perspective a
Kelli E. Canada & Alana J. Gunn
b
a
School of Social Work , University of Missouri , Columbia , Missouri , USA b
School of Social Service Administration , University of Chicago , Chicago , Illinois , USA Published online: 08 Jul 2013.
To cite this article: Kelli E. Canada & Alana J. Gunn (2013) What Factors Work in Mental Health Court? A Consumer Perspective, Journal of Offender Rehabilitation, 52:5, 311-337, DOI: 10.1080/10509674.2013.801387 To link to this article: http://dx.doi.org/10.1080/10509674.2013.801387
PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http://www.tandfonline.com/page/termsand-conditions
Journal of Offender Rehabilitation, 52:311–337, 2013 Copyright © Taylor & Francis Group, LLC ISSN: 1050-9674 print/1540-8558 online DOI: 10.1080/10509674.2013.801387
What Factors Work in Mental Health Court? A Consumer Perspective
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KELLI E. CANADA School of Social Work, University of Missouri, Columbia, Missouri, USA
ALANA J. GUNN School of Social Service Administration, University of Chicago, Chicago, Illinois, USA
Mental health court (MHC) participation is associated with reduced recidivism and increased access to services but there is little empirical support for the factors that impact outcomes. Previous research supports the importance of social support in recovery and reducing criminal recidivism for populations similar to the population served by MHCs. This research project used mixed-methodology to explore MHC participant perceptions (n = 26) of factors important in recovery and estimated the associations between social support and outcomes (n = 80). Although social support was not associated with outcomes quantitatively, social support emerged as a salient theme in the qualitative analysis. Participants reported support, structure, accountability, treatment, and instilling motivation as key factors in recovery and recidivism. KEYWORDS criminal justice system, mental health court, serious mental illnesses, social support
A substantial portion of individuals in custody are people with serious mental illnesses. Research shows approximately 16% of jail detainees and 16% of individuals in state prisons self-reported having an emotional illness or experiencing overnight stays in a psychiatric facility (Lurigio, 2000). Once incarcerated, people with serious mental illnesses are at a higher risk of victimization (Blitz, Wolff, & Shi, 2008) and spending more time in custody
Financial support was provided by grant P20 MH085981 from the National Institute of Mental Health. Address correspondence to Kelli E. Canada, School of Social Work, University of Missouri, 706 Clark Hall, Columbia, MO 65211, USA. E-mail: [email protected] 311
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(Ditton, 1999) in comparison to people without mental illnesses. People with mental illnesses are also at risk of having an exacerbation of symptoms while in custody. Mental health court (MHC) programs were created, in part, to divert people with mental illnesses from prison to community-based treatment in order to reduce some of the negative impacts associated with incarceration. MHCs are expanding across the nation but the evidence base is scant and involves substantial gaps in research. Although some research shows MHC participation can reduce future recidivism and increase mental health service use (Herinckx, Swart, Ama, Dolezal, & King, 2005; Steadman, Redlich, Callahan, Clark Robbins, & Vesselinov, 2011; Burns, Hiday, & Ray, 2013), it is unclear what mechanisms are impacting or influencing outcomes. Research involving populations similar to people served by MHCs has shown that the quality and strength of the relationship with an individual’s probation officer is a central factor in both compliance and positive outcomes (Skeem, Eno Louden, Polaschek, & Camp, 2007). Although MHC researchers have speculated that participants benefit from MHCs when relationships among team members and social supports are strong (Herinckx et al., 2005), these associations have not yet been empirically tested. The current study aims to address several unanswered questions by exploring MHC participant perspectives regarding the key factors in promoting change and by investigating the role, if any, that social support plays in recovery and recidivism. In order to both explore participant perspectives and estimate the association between social support and outcomes, a mixed-method design that draws from multiple data sources is utilized to address research questions and contextualize data. The qualitative portion explores participants’ perspectives of the key factors involved in change within the context of MHC programs. The quantitative analysis complements the qualitative analysis by estimating the strength of associations between social support and service use, treatment adherence, and days spent in jail.
Social Support Network House, Umberson, and Landis (1988) defined social support as “a positive, potentially health promoting or stress-buffering, aspect of relationships” (p. 302). Barrera and Ainlay (1983) conceptualized social support as verbal or nonverbal information or advisement and tangible resources or actions provided by the people in one’s social network, which can have emotional and behavioral impacts on the recipient. There are four domains of support in relationships including emotional (i.e., esteem, trust, concern, listening), instrumental (i.e., aid in the form of money, time, labor), informational (i.e., advice, suggestions), and appraisal (i.e., feedback, affirmation; House et al., 1988).
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Some researchers conceptualize social support at a network level (Lincoln, 2008). This may be especially beneficial in order to examine the system of social support in an individual’s life, which may be particularly important among vulnerable populations. A social support network involves both informal and formal network members. An informal support network refers to family members, peers, friends, and/or acquaintances, whereas a formal support network refers to organizational entities, service providers, and other professionals involved in an individual’s life to promote sustainability and growth. Social support is thought to impact outcomes through two functions: leverage and coping. Among people with mental illnesses, social support, especially from formal networks, may influence outcomes through leverage, which can increase individuals’ resources and facilitate upward social mobility (Briggs, 1998). Social support can also shape outcomes through a coping or buffering mechanism (Rogers, Anthony, & Lyass, 2004). Social support can reduce stress and hardships and buffer against chronic stress (House, 1981; Briggs, 1998). The coping function of social support is especially important for individuals who are chronically poor (Briggs, 1998); the resources gained through social support systems can alter one’s views of stressors. These resources can promote self-efficacy and enhance an individual’s ability to problem solve (Rogers et al., 2004), which increases one’s ability to cope. SOCIAL SUPPORT AND OUTCOMES The perception of having social support and that people are willing to help in a time of need is thought to impact one’s self-esteem, stability, and feelings of control over the environment (Cohen & Syme, 1985); social support is also thought to impact health-promoting behaviors (House et al., 1988) and rule abidance for some individuals (Skeem et al., 2007). Although much of research links social support with physical health outcomes, mental health outcomes like distress, depression, and anxiety are also associated with the receipt of support (Turner & Brown, 2010). Turner and Brown (2010) argue that support may only be as helpful as the degree by which it is perceived. One’s perception of support is thought to be especially protective in buffering the impact of chronic stress and distress, which supports the use of measures to capture individual perceptions of social support and qualitative analyses to assess the individual variation inherent in support as utilized in the current study. Social support plays an important role in treatment and recovery among individuals with mental illnesses. Research shows among people with chronic mental illnesses, network support improved overall measures of functioning. Specifically, social support improves the use of formal services (Lam & Rosenheck, 1999), increases treatment adherence (DiMatteo, 2004), reduces
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distress (Lincoln, 2008), influences recovery (Cohen & Syme, 1985), and impacts the course of schizophrenia (Buchanan, 1995), while an absence of support can increase psychiatric hospitalizations and substance use at least among populations with chronic illnesses (Swindle, Heller, & Frank, 2000). Peer support, in particular, is associated with enhanced quality of life, selfesteem, psychological symptoms, and network satisfaction (Davidson et al., 2001). In fact peer provided support services were just as effective as nonpeer services and significantly related to fewer hospitalizations and use of crisis-oriented services (Clarke et al., 2000). Although much of the literature suggests supportive networks promote positive outcomes, some research calls into question social supports’ utility throughout the continuum of treatment. Westreich, Heitner, Cooper, Galanter, and Guedji (1997) examined the role of social support among patients in a brief inpatient addiction rehabilitation program. Researchers report that in the early stages of treatment, perceptions of low social support from family members were related to greater completion of a voluntary inpatient program suggesting that social support from family members is not always beneficial to treatment completion and adherence. These findings also suggest the need for further research that examines the complexities of support giving and receipt for individuals recovering from illness and addiction, as this study aims to do. There has been increased attention given to the importance of social support networks in the lives of people who are involved in the criminal justice system. Research on social support among people in custody demonstrates that receiving social support improves the successful completion of parole and improves post-release family unification (Schafer, 1994) and reduces recidivism (Bales & Mears, 2008). Similar to people in recovery from addictions and mental illness, peer support also plays an important role in promoting outcomes like reduced substance use and recidivism among people who are re-entering the community (Andreas, Ja, & Wilson, 2010). Although there is a trend in research towards examining social support in treatment and social support among individuals who are in custody, little research has focused on the role of social support when serious mental illness intersects with the criminal justice system. One study investigated the social support systems of women re-entering their communities post incarceration with co-occurring disorders of mental illness and substance abuse. Findings of the study revealed that women who reported higher levels of social support reported less depression and felt more empowered (Salina, Lesondak, Razzano, & Parent, 2011). The purpose of the current study is to address unanswered questions in MHC research regarding key factors involved in change and contribute to knowledge regarding the social support networks of individuals with an intersection of mental health challenges and criminal justice involvement.
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Based on social support theory and existing research, it is expected that the quantitative analysis will reveal that MHC participants’ perceptions of their social support network will be associated with treatment adherence, use of social services, and the number of days spent in jail. As is customary in qualitative analysis, the qualitative portion of this study is not theory and hypothesis driven. Rather, semi-structured interviews included questions meant to inductively explore consumer experiences with the MHC in order to better understand what factors impact change from consumer perspectives.
METHODS The Setting MHC participants from two Midwestern counties (referred to as Court A and B) were recruited for this study between September 2010 and April 2011. Court A was established in 2004 and operates out of five different sites within the county while Court B was established in 2005 and includes a single site. Both MHCs in this study were located in an urban environment; however, Court B also covers a suburban and rural area. Courts A and B have a dedicated docket for people with mental illnesses and a single judge is assigned to that docket. Both courts utilize a team approach, such that the judge, caseworkers, probation officers, court administrators, and attorneys meet frequently with one another to discuss participants’ adherence to program requirements. Participant eligibility is similar between the two courts (i.e., voluntary, most charges were non-violent/nonvictim, exclusion of developmental disorders). However, Court A only accepts participants with felony charges; Court B accepts felony charges primarily but does allow for misdemeanor charges as well. Court A is largely post-conviction, meaning individuals must plead guilty in a traditional court prior to MHC participation. MHC participants from Court A serve approximately 2 years under MHC supervision. Court B has participants with both preconviction (i.e., individual does not plead guilty prior to MHC participation) and postconviction agreements. In comparison to Court A, Court B has a wider range of supervision times with as little as one year to as much as three years. Both MHCs require participants to engage in mental health and substance use (when needed) treatment. The two courts offered similar services including outpatient mental health treatment (e.g., psychiatrist appointments, medication monitoring, psychiatric nurse home visiting, group therapy, individual therapy), inpatient and outpatient substance use treatment, vocational programs, support groups, and peer-recovery groups. Court A relies on a network of community treatment providers to supply the needed mental health and substance use treatment. The MHC staff work with
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community providers and MHC participants to monitor and supervise engagement in treatment. Court B also utilizes treatment providers, but those providers work within one agency and work as a team directly with court personnel. In order to monitor participants, both courts require frequent contact with participants through formal court hearings and regular appointments with the MHC team. The MHC teams use rewards to encourage compliance and sanctions to deter problem behaviors. Both courts offered a similar range of incentives. Sanctions for non-compliance could include increased reporting to MHC staff, increased frequency of urine screening, community service, and in extreme cases overnight stays in jail. Rewards include verbal incentives such as adulation from the MHC team to more tangible incentive such as reduced court appearances, overnight passes to stay with family, and ultimately graduation from the program. Participants who entered the MHC under a pre-conviction agreement often had their charges dropped or reduced once they successfully completed the program.
Eligibility and Sampling In the current study, eligible participants were adults enrolled in the MHC between two and eighteen months and who were not in custody. Ninety-one participants met eligibility criteria and were invited to participate through the distribution of flyers by the researcher or MHC staff. Eighty participants (88%) consented to study participation (40 from each court) for the structured interview. The 11 eligible participants who were not enrolled did not participate because they did not return the researcher’s phone call, did not have a working number, or presented with paranoid delusions that interfered with the consent process. During the consent process prior to the structured interview, participants were asked if they were interested in participating in a second interview. Seventy-nine participants consented to recruitment for the second interview. Thirty-five individuals were purposively sampled and invited via phone to participate. Purposive sampling occurs when the researcher selects cases strategically to provide depth into the phenomenon under study; the cases selected were meant to include study participants who were most able to engage in a dialogue regarding their experiences with the MHC in order to shed light on the concepts under study (Kemper, Stringfield, & Teddlie, 2003). The subsample was additionally selected based on sex, criminal history, and substance use as these factors have impacted recidivism in past studies (Hartwell, 2004). Of the 35 individuals sampled, 26 consented to participate (13 from each court). The nine individuals who did not consent to participation, did not show up to the scheduled interview, did not return the initial phone call to schedule the follow-up interview, or did not provide a working phone number.
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Procedures All eligible people who consented to participating in the research project met with the researcher for an interview at a location convenient for the participant. The structured interview consisted of standardized measures and questions regarding demographics, attitudes toward medications, symptomatology, and perceptions of support. Participants also provided consent for the researcher to collect administrative data regarding treatment adherence, the number of days spent in custody, and the number of social services used each month for 6 months following their structured interview. Participants who consented to participation in the semi-structured interview, met with the researcher one to four months after their initial interview. The second interview consisted of open-ended questions regarding participants’ experiences with the MHC and their perspectives regarding the factors that are important in promoting change. The appropriate Institutional Review Board reviewed and approved all forms and procedures in working with human subjects.
Measurement INDEPENDENT AND CONTROL VARIABLES Participants self-reported background characteristics including demographics, mental illness diagnosis, legal history, and number of months in the MHC. Standardized measures were used to assess symptom severity, attitudes towards psychiatric medications, and perceptions of support among participants’ core network members, MHC judge, MHC caseworker, and participants’ primary community treatment provider. Symptom severity, which was used as a control variable in analyses, was assessed using the Anchored Brief Psychiatric Rating Scale (BPRS; Overall & Gorham, 1962). The BPRS is an 18-item measure with symptom severity reported on a 7-point scale (1 = not reported; 7 = very severe). The scales are reliable based on inter-rater reliability testing with scales ranging from r(144) = 0.52 through 0.90 (Overall & Gorham, 1962). Each item includes a description of the symptom and a descriptive anchor. Participants’ attitudes regarding medication were measured using the Attitudes Toward Psychiatric Medication Scale (ATPMS; Streicker, Amdur, & Dincin, 1986), a five-item instrument measuring perceptions of the effectiveness of psychiatric medications. The ATPMS is grouped with questions assessing effectiveness and questions assessing side effects; both sets of questions have good internal consistency, 0.80 and 0.61, respectively, among people with serious mental illnesses (Streicker et al., 1986). In order to estimate participants’ perceived network support, participants were first asked to list up to five people in their lives excluding treatment and court staff. Participants were instructed to identify the core people in their life. The social support scale of the Social Support and Undermining
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Scale (SSUS; Vinokur, Caplan, & Schul, 1987) was used to estimate perceptions of social support. The social support portion of the scale includes eight questions measuring the perception of support (i.e., emotional, instrumental, appraisal, and informational support). Internal consistency estimates of the scales range from a Cronbach alpha of 0.81 to 0.87 (Vinokur et al., 1987). Questions are rated on a 5-point scale (1 = not at all; 5 = a great deal). Participants answered questions on the SSUS for each of their identified network members (up to five) and their formal network (i.e., MHC caseworker, the MHC judge, and the primary treatment provider). Estimates of perceived support from core network and formal network members were summed and averaged for analytic purposes. DEPENDENT VARIABLES Measurement of three dependent variables occurred for each of 6 months following participant interviews. Members of the MHC team provided the researcher with the number of days the participant spent in jail and the number of services the participant utilized per month including individual/ group therapy, non-clinical groups (e.g., skill building, GED preparation, 12-step, vocational training), psychiatric visits, and substance use treatment. In addition, MHC caseworkers assessed treatment adherence each month using a 4-point scale (1 = never follows treatment recommendations; 4 = always or almost always follows treatment recommendations). The monthly variables were summed over the six months to create three single continuous variables for days in jail, service utilization, and treatment adherence.
Data Analysis A concurrent triangulation mixed-method design was utilized to address research questions. In a concurrent triangulation mixed-method design, the study is constructed in order to explore phenomena and test for relationships between factors (Creswell, Plano Clark, Gutmann, & Hanson, 2003). Results of the quantitative analysis are directly compared and contrasted with the emerging themes in the qualitative analysis. QUALITATIVE ANALYSIS In order to analyze participants’ experiences with the MHC, a thematic analysis was conducted. Thematic analysis is an approach used to identify, analyze, organize, interpret, and present patterns or themes within data (Braun & Clarke, 2006). Themes are intended to capture “something important about the data in relation to the research question, and represents some level of patterned response or meaning within the data set” (Braun & Clarke, 2006, p. 82). Themes and the interpretation of these themes are generated recursively.
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The researcher asked open-ended questions regarding participants’ general experience with the MHC (e.g., “In your experience with the MHC, what works? What doesn’t work?”) and provided opportunity for participants to discuss anything about their experience that they perceived as important (e.g., “Is there anything you would like to tell me about regarding your participation in the MHC?”). Follow-up questions based on responses varied from participant to participant. In order to conduct the thematic analysis, the transcribed interviews were analyzed line-by-line; references to factors thought to impact individual change were coded. References were then analyzed line-by-line until salient themes emerged. The qualitative analysis was organized using Nvivo software version nine. QUANTITATIVE ANALYSIS Correlations were calculated between continuous dependent and independent variables. Bivariate analyses and theory-driven variable selection strategies were employed to identify parsimonious linear regression models in order to examine the association between perceived social support and service use, treatment adherence, and days in jail. Attitudes towards psychiatric medications, number of months in the MHC, symptom severity reported during research interviews, and MHC were used as control variables in the final models. Control variables were selected based on their theoretical significance, statistical significance in bivariate analyses (p < .05), and variable stability (both skewness and kurtosis). Although sex, criminal history, and substance use were identified in previous research to impact recidivism (Hartwell, 2004), these factors were not significant in bivariate analyses in this study and thus not used as controls. Participants with missing data were not included in the analysis. All quantitative analyses were conducted using SPSS predictive software version 20.0.
RESULTS Sample Description Table 1 presents the demographic characteristics of the study sample. Over half of the study participants were male (55%) and African American (56.3%). The average age of participants was 39.6 (SD = 12.1) years old. Nearly half of participants in the study reported to be in a relationship (48.8%). On average, study participants completed 11.3 (SD = 2.5) years of education. Very few participants worked at the time of the baseline interview (5%); just over half of the participants received Supplemental Security Income (SSI) or Social Security Disability Insurance (SSDI). At the time of the initial interview, participants were in the MHC program for an average of 7.6 months. After the
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K. E. Canada and A. J. Gunn TABLE 1 Sample Description (n = 80)
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Demographics
%*
N
Sex Female Race African American Bi-racial Caucasian Latino Native American
45
36
56 5 34 4 1
45 4 27 3 1
Relationship status Single In a relationship, not married Married Divorced/widowed
46 40 9 5
37 32 7 4
4 1
3 1
Program retention Graduated/remained active Terminated/missing Receiving SSI or SSDI Substance use diagnosis
90 10 51 84
72 8 41 67
Mental illness diagnosis Bipolar Schizophrenia spectrum Depression Major depression Other (ADHD, GAD, phobia)
59 30 5 3 5
47 23 4 2 4
Primary charge Retail theft/burglary Drug related Battery/assault Felony violent crime
44 21 18 87 14
35 17 14 69 11
Employment Part-time Full-time
M Age in years (range 19–65) Education in years (range 3–16) Months in MHC (range 2–18) Core network members (range 0–5) Arrests in 2 years prior to MHC (range 1–14)
39.6 11.3 7.6 2.7 2.9
SD 12.1 2.5 5.2 1.2 2.4
*Categories may not equal 100% due to rounding.
6-month follow-up period, 10% of the study sample was terminated unsuccessfully or went missing four or more months of the follow-up period. A participant is considered missing when the MHC staff is unable to locate the participant.
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The majority of individuals in the current study reported a primary diagnosis of bipolar disorder (58.8%). Of study participants, 90% reported a primary diagnosis that is considered to be a serious mental illness (i.e., bipolar disorder, major depression, schizophrenia, or schizoaffective disorder). The majority of study participants also reported a co-occurring substance use disorder (83.8%). The majority of participants were not experiencing severe psychiatric symptoms during the 7 days preceding the structured interview. The average rating of symptoms among participants was highest for anxiety, depression, and feelings of guilt. The majority of participants agreed or strongly agreed that medication is necessary, helps to manage stress, prevents psychiatric hospitalizations, controls symptoms, and improves self-esteem. Participants were asked to list up to five people who they consider to be their core group of family and friends. On average, study participants reported 2.7 people in their informal networks. This is comparable to a study using the same method of data collection and involving a very similar population who reported an average of 2.9 core network members (Skeem, Eno Louden, Manchak, Vidal, & Haddad, 2008). Participants perceived moderate social support from informal network members, M = 32.85, SD = 6.45, on a scale with a maximum rating of 40. Participants perceived slightly less support among formal network members, M = 29.56, SD = 7.58; these differences were statistically-significantly, t(77) = 4.82, p < .01. When looking at participants’ entire social network (formal and informal combined), participants perceived moderate support, M = 30.75, SD = 6.61. In the 2 years prior to MHC participation, participants were arrested, on average, 2.9 times. Participants reported the charge that led to their participation in the MHC. Most participants were arrested for retail theft or burglary charges (43.8%), drug related charges (21.3%), or battery and assault (17.4%). A small percentage of participants were charged with prostitution, criminal damage to property, trespassing, driving on a revoked license, forgery, probation violation, and resisting arrest (17.4%). The majority of charges were considered felonies (86.3%). Some participants reported that their charge was considered violent (13.8%). COURT DIFFERENCES All factors listed in Table 1 were examined for between court differences. Independent t-tests indicate that participants from Court A are, on average, older, t(78) = 2.49, p = .02, d = 0.55, and reported being arrested more often, t(78) = 2.38, p = .02, d = 0.55, in comparison to participants from Court B. Participants also differed in race, χ2 (1, n = 80) = 9.45, p
Journal of Offender Rehabilitation Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/wjor20
What Factors Work in Mental Health Court? A Consumer Perspective a
Kelli E. Canada & Alana J. Gunn
b
a
School of Social Work , University of Missouri , Columbia , Missouri , USA b
School of Social Service Administration , University of Chicago , Chicago , Illinois , USA Published online: 08 Jul 2013.
To cite this article: Kelli E. Canada & Alana J. Gunn (2013) What Factors Work in Mental Health Court? A Consumer Perspective, Journal of Offender Rehabilitation, 52:5, 311-337, DOI: 10.1080/10509674.2013.801387 To link to this article: http://dx.doi.org/10.1080/10509674.2013.801387
PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform. However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content. Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis. The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. Terms & Conditions of access and use can be found at http://www.tandfonline.com/page/termsand-conditions
Journal of Offender Rehabilitation, 52:311–337, 2013 Copyright © Taylor & Francis Group, LLC ISSN: 1050-9674 print/1540-8558 online DOI: 10.1080/10509674.2013.801387
What Factors Work in Mental Health Court? A Consumer Perspective
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KELLI E. CANADA School of Social Work, University of Missouri, Columbia, Missouri, USA
ALANA J. GUNN School of Social Service Administration, University of Chicago, Chicago, Illinois, USA
Mental health court (MHC) participation is associated with reduced recidivism and increased access to services but there is little empirical support for the factors that impact outcomes. Previous research supports the importance of social support in recovery and reducing criminal recidivism for populations similar to the population served by MHCs. This research project used mixed-methodology to explore MHC participant perceptions (n = 26) of factors important in recovery and estimated the associations between social support and outcomes (n = 80). Although social support was not associated with outcomes quantitatively, social support emerged as a salient theme in the qualitative analysis. Participants reported support, structure, accountability, treatment, and instilling motivation as key factors in recovery and recidivism. KEYWORDS criminal justice system, mental health court, serious mental illnesses, social support
A substantial portion of individuals in custody are people with serious mental illnesses. Research shows approximately 16% of jail detainees and 16% of individuals in state prisons self-reported having an emotional illness or experiencing overnight stays in a psychiatric facility (Lurigio, 2000). Once incarcerated, people with serious mental illnesses are at a higher risk of victimization (Blitz, Wolff, & Shi, 2008) and spending more time in custody
Financial support was provided by grant P20 MH085981 from the National Institute of Mental Health. Address correspondence to Kelli E. Canada, School of Social Work, University of Missouri, 706 Clark Hall, Columbia, MO 65211, USA. E-mail: [email protected] 311
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(Ditton, 1999) in comparison to people without mental illnesses. People with mental illnesses are also at risk of having an exacerbation of symptoms while in custody. Mental health court (MHC) programs were created, in part, to divert people with mental illnesses from prison to community-based treatment in order to reduce some of the negative impacts associated with incarceration. MHCs are expanding across the nation but the evidence base is scant and involves substantial gaps in research. Although some research shows MHC participation can reduce future recidivism and increase mental health service use (Herinckx, Swart, Ama, Dolezal, & King, 2005; Steadman, Redlich, Callahan, Clark Robbins, & Vesselinov, 2011; Burns, Hiday, & Ray, 2013), it is unclear what mechanisms are impacting or influencing outcomes. Research involving populations similar to people served by MHCs has shown that the quality and strength of the relationship with an individual’s probation officer is a central factor in both compliance and positive outcomes (Skeem, Eno Louden, Polaschek, & Camp, 2007). Although MHC researchers have speculated that participants benefit from MHCs when relationships among team members and social supports are strong (Herinckx et al., 2005), these associations have not yet been empirically tested. The current study aims to address several unanswered questions by exploring MHC participant perspectives regarding the key factors in promoting change and by investigating the role, if any, that social support plays in recovery and recidivism. In order to both explore participant perspectives and estimate the association between social support and outcomes, a mixed-method design that draws from multiple data sources is utilized to address research questions and contextualize data. The qualitative portion explores participants’ perspectives of the key factors involved in change within the context of MHC programs. The quantitative analysis complements the qualitative analysis by estimating the strength of associations between social support and service use, treatment adherence, and days spent in jail.
Social Support Network House, Umberson, and Landis (1988) defined social support as “a positive, potentially health promoting or stress-buffering, aspect of relationships” (p. 302). Barrera and Ainlay (1983) conceptualized social support as verbal or nonverbal information or advisement and tangible resources or actions provided by the people in one’s social network, which can have emotional and behavioral impacts on the recipient. There are four domains of support in relationships including emotional (i.e., esteem, trust, concern, listening), instrumental (i.e., aid in the form of money, time, labor), informational (i.e., advice, suggestions), and appraisal (i.e., feedback, affirmation; House et al., 1988).
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Some researchers conceptualize social support at a network level (Lincoln, 2008). This may be especially beneficial in order to examine the system of social support in an individual’s life, which may be particularly important among vulnerable populations. A social support network involves both informal and formal network members. An informal support network refers to family members, peers, friends, and/or acquaintances, whereas a formal support network refers to organizational entities, service providers, and other professionals involved in an individual’s life to promote sustainability and growth. Social support is thought to impact outcomes through two functions: leverage and coping. Among people with mental illnesses, social support, especially from formal networks, may influence outcomes through leverage, which can increase individuals’ resources and facilitate upward social mobility (Briggs, 1998). Social support can also shape outcomes through a coping or buffering mechanism (Rogers, Anthony, & Lyass, 2004). Social support can reduce stress and hardships and buffer against chronic stress (House, 1981; Briggs, 1998). The coping function of social support is especially important for individuals who are chronically poor (Briggs, 1998); the resources gained through social support systems can alter one’s views of stressors. These resources can promote self-efficacy and enhance an individual’s ability to problem solve (Rogers et al., 2004), which increases one’s ability to cope. SOCIAL SUPPORT AND OUTCOMES The perception of having social support and that people are willing to help in a time of need is thought to impact one’s self-esteem, stability, and feelings of control over the environment (Cohen & Syme, 1985); social support is also thought to impact health-promoting behaviors (House et al., 1988) and rule abidance for some individuals (Skeem et al., 2007). Although much of research links social support with physical health outcomes, mental health outcomes like distress, depression, and anxiety are also associated with the receipt of support (Turner & Brown, 2010). Turner and Brown (2010) argue that support may only be as helpful as the degree by which it is perceived. One’s perception of support is thought to be especially protective in buffering the impact of chronic stress and distress, which supports the use of measures to capture individual perceptions of social support and qualitative analyses to assess the individual variation inherent in support as utilized in the current study. Social support plays an important role in treatment and recovery among individuals with mental illnesses. Research shows among people with chronic mental illnesses, network support improved overall measures of functioning. Specifically, social support improves the use of formal services (Lam & Rosenheck, 1999), increases treatment adherence (DiMatteo, 2004), reduces
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distress (Lincoln, 2008), influences recovery (Cohen & Syme, 1985), and impacts the course of schizophrenia (Buchanan, 1995), while an absence of support can increase psychiatric hospitalizations and substance use at least among populations with chronic illnesses (Swindle, Heller, & Frank, 2000). Peer support, in particular, is associated with enhanced quality of life, selfesteem, psychological symptoms, and network satisfaction (Davidson et al., 2001). In fact peer provided support services were just as effective as nonpeer services and significantly related to fewer hospitalizations and use of crisis-oriented services (Clarke et al., 2000). Although much of the literature suggests supportive networks promote positive outcomes, some research calls into question social supports’ utility throughout the continuum of treatment. Westreich, Heitner, Cooper, Galanter, and Guedji (1997) examined the role of social support among patients in a brief inpatient addiction rehabilitation program. Researchers report that in the early stages of treatment, perceptions of low social support from family members were related to greater completion of a voluntary inpatient program suggesting that social support from family members is not always beneficial to treatment completion and adherence. These findings also suggest the need for further research that examines the complexities of support giving and receipt for individuals recovering from illness and addiction, as this study aims to do. There has been increased attention given to the importance of social support networks in the lives of people who are involved in the criminal justice system. Research on social support among people in custody demonstrates that receiving social support improves the successful completion of parole and improves post-release family unification (Schafer, 1994) and reduces recidivism (Bales & Mears, 2008). Similar to people in recovery from addictions and mental illness, peer support also plays an important role in promoting outcomes like reduced substance use and recidivism among people who are re-entering the community (Andreas, Ja, & Wilson, 2010). Although there is a trend in research towards examining social support in treatment and social support among individuals who are in custody, little research has focused on the role of social support when serious mental illness intersects with the criminal justice system. One study investigated the social support systems of women re-entering their communities post incarceration with co-occurring disorders of mental illness and substance abuse. Findings of the study revealed that women who reported higher levels of social support reported less depression and felt more empowered (Salina, Lesondak, Razzano, & Parent, 2011). The purpose of the current study is to address unanswered questions in MHC research regarding key factors involved in change and contribute to knowledge regarding the social support networks of individuals with an intersection of mental health challenges and criminal justice involvement.
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Based on social support theory and existing research, it is expected that the quantitative analysis will reveal that MHC participants’ perceptions of their social support network will be associated with treatment adherence, use of social services, and the number of days spent in jail. As is customary in qualitative analysis, the qualitative portion of this study is not theory and hypothesis driven. Rather, semi-structured interviews included questions meant to inductively explore consumer experiences with the MHC in order to better understand what factors impact change from consumer perspectives.
METHODS The Setting MHC participants from two Midwestern counties (referred to as Court A and B) were recruited for this study between September 2010 and April 2011. Court A was established in 2004 and operates out of five different sites within the county while Court B was established in 2005 and includes a single site. Both MHCs in this study were located in an urban environment; however, Court B also covers a suburban and rural area. Courts A and B have a dedicated docket for people with mental illnesses and a single judge is assigned to that docket. Both courts utilize a team approach, such that the judge, caseworkers, probation officers, court administrators, and attorneys meet frequently with one another to discuss participants’ adherence to program requirements. Participant eligibility is similar between the two courts (i.e., voluntary, most charges were non-violent/nonvictim, exclusion of developmental disorders). However, Court A only accepts participants with felony charges; Court B accepts felony charges primarily but does allow for misdemeanor charges as well. Court A is largely post-conviction, meaning individuals must plead guilty in a traditional court prior to MHC participation. MHC participants from Court A serve approximately 2 years under MHC supervision. Court B has participants with both preconviction (i.e., individual does not plead guilty prior to MHC participation) and postconviction agreements. In comparison to Court A, Court B has a wider range of supervision times with as little as one year to as much as three years. Both MHCs require participants to engage in mental health and substance use (when needed) treatment. The two courts offered similar services including outpatient mental health treatment (e.g., psychiatrist appointments, medication monitoring, psychiatric nurse home visiting, group therapy, individual therapy), inpatient and outpatient substance use treatment, vocational programs, support groups, and peer-recovery groups. Court A relies on a network of community treatment providers to supply the needed mental health and substance use treatment. The MHC staff work with
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community providers and MHC participants to monitor and supervise engagement in treatment. Court B also utilizes treatment providers, but those providers work within one agency and work as a team directly with court personnel. In order to monitor participants, both courts require frequent contact with participants through formal court hearings and regular appointments with the MHC team. The MHC teams use rewards to encourage compliance and sanctions to deter problem behaviors. Both courts offered a similar range of incentives. Sanctions for non-compliance could include increased reporting to MHC staff, increased frequency of urine screening, community service, and in extreme cases overnight stays in jail. Rewards include verbal incentives such as adulation from the MHC team to more tangible incentive such as reduced court appearances, overnight passes to stay with family, and ultimately graduation from the program. Participants who entered the MHC under a pre-conviction agreement often had their charges dropped or reduced once they successfully completed the program.
Eligibility and Sampling In the current study, eligible participants were adults enrolled in the MHC between two and eighteen months and who were not in custody. Ninety-one participants met eligibility criteria and were invited to participate through the distribution of flyers by the researcher or MHC staff. Eighty participants (88%) consented to study participation (40 from each court) for the structured interview. The 11 eligible participants who were not enrolled did not participate because they did not return the researcher’s phone call, did not have a working number, or presented with paranoid delusions that interfered with the consent process. During the consent process prior to the structured interview, participants were asked if they were interested in participating in a second interview. Seventy-nine participants consented to recruitment for the second interview. Thirty-five individuals were purposively sampled and invited via phone to participate. Purposive sampling occurs when the researcher selects cases strategically to provide depth into the phenomenon under study; the cases selected were meant to include study participants who were most able to engage in a dialogue regarding their experiences with the MHC in order to shed light on the concepts under study (Kemper, Stringfield, & Teddlie, 2003). The subsample was additionally selected based on sex, criminal history, and substance use as these factors have impacted recidivism in past studies (Hartwell, 2004). Of the 35 individuals sampled, 26 consented to participate (13 from each court). The nine individuals who did not consent to participation, did not show up to the scheduled interview, did not return the initial phone call to schedule the follow-up interview, or did not provide a working phone number.
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Procedures All eligible people who consented to participating in the research project met with the researcher for an interview at a location convenient for the participant. The structured interview consisted of standardized measures and questions regarding demographics, attitudes toward medications, symptomatology, and perceptions of support. Participants also provided consent for the researcher to collect administrative data regarding treatment adherence, the number of days spent in custody, and the number of social services used each month for 6 months following their structured interview. Participants who consented to participation in the semi-structured interview, met with the researcher one to four months after their initial interview. The second interview consisted of open-ended questions regarding participants’ experiences with the MHC and their perspectives regarding the factors that are important in promoting change. The appropriate Institutional Review Board reviewed and approved all forms and procedures in working with human subjects.
Measurement INDEPENDENT AND CONTROL VARIABLES Participants self-reported background characteristics including demographics, mental illness diagnosis, legal history, and number of months in the MHC. Standardized measures were used to assess symptom severity, attitudes towards psychiatric medications, and perceptions of support among participants’ core network members, MHC judge, MHC caseworker, and participants’ primary community treatment provider. Symptom severity, which was used as a control variable in analyses, was assessed using the Anchored Brief Psychiatric Rating Scale (BPRS; Overall & Gorham, 1962). The BPRS is an 18-item measure with symptom severity reported on a 7-point scale (1 = not reported; 7 = very severe). The scales are reliable based on inter-rater reliability testing with scales ranging from r(144) = 0.52 through 0.90 (Overall & Gorham, 1962). Each item includes a description of the symptom and a descriptive anchor. Participants’ attitudes regarding medication were measured using the Attitudes Toward Psychiatric Medication Scale (ATPMS; Streicker, Amdur, & Dincin, 1986), a five-item instrument measuring perceptions of the effectiveness of psychiatric medications. The ATPMS is grouped with questions assessing effectiveness and questions assessing side effects; both sets of questions have good internal consistency, 0.80 and 0.61, respectively, among people with serious mental illnesses (Streicker et al., 1986). In order to estimate participants’ perceived network support, participants were first asked to list up to five people in their lives excluding treatment and court staff. Participants were instructed to identify the core people in their life. The social support scale of the Social Support and Undermining
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Scale (SSUS; Vinokur, Caplan, & Schul, 1987) was used to estimate perceptions of social support. The social support portion of the scale includes eight questions measuring the perception of support (i.e., emotional, instrumental, appraisal, and informational support). Internal consistency estimates of the scales range from a Cronbach alpha of 0.81 to 0.87 (Vinokur et al., 1987). Questions are rated on a 5-point scale (1 = not at all; 5 = a great deal). Participants answered questions on the SSUS for each of their identified network members (up to five) and their formal network (i.e., MHC caseworker, the MHC judge, and the primary treatment provider). Estimates of perceived support from core network and formal network members were summed and averaged for analytic purposes. DEPENDENT VARIABLES Measurement of three dependent variables occurred for each of 6 months following participant interviews. Members of the MHC team provided the researcher with the number of days the participant spent in jail and the number of services the participant utilized per month including individual/ group therapy, non-clinical groups (e.g., skill building, GED preparation, 12-step, vocational training), psychiatric visits, and substance use treatment. In addition, MHC caseworkers assessed treatment adherence each month using a 4-point scale (1 = never follows treatment recommendations; 4 = always or almost always follows treatment recommendations). The monthly variables were summed over the six months to create three single continuous variables for days in jail, service utilization, and treatment adherence.
Data Analysis A concurrent triangulation mixed-method design was utilized to address research questions. In a concurrent triangulation mixed-method design, the study is constructed in order to explore phenomena and test for relationships between factors (Creswell, Plano Clark, Gutmann, & Hanson, 2003). Results of the quantitative analysis are directly compared and contrasted with the emerging themes in the qualitative analysis. QUALITATIVE ANALYSIS In order to analyze participants’ experiences with the MHC, a thematic analysis was conducted. Thematic analysis is an approach used to identify, analyze, organize, interpret, and present patterns or themes within data (Braun & Clarke, 2006). Themes are intended to capture “something important about the data in relation to the research question, and represents some level of patterned response or meaning within the data set” (Braun & Clarke, 2006, p. 82). Themes and the interpretation of these themes are generated recursively.
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The researcher asked open-ended questions regarding participants’ general experience with the MHC (e.g., “In your experience with the MHC, what works? What doesn’t work?”) and provided opportunity for participants to discuss anything about their experience that they perceived as important (e.g., “Is there anything you would like to tell me about regarding your participation in the MHC?”). Follow-up questions based on responses varied from participant to participant. In order to conduct the thematic analysis, the transcribed interviews were analyzed line-by-line; references to factors thought to impact individual change were coded. References were then analyzed line-by-line until salient themes emerged. The qualitative analysis was organized using Nvivo software version nine. QUANTITATIVE ANALYSIS Correlations were calculated between continuous dependent and independent variables. Bivariate analyses and theory-driven variable selection strategies were employed to identify parsimonious linear regression models in order to examine the association between perceived social support and service use, treatment adherence, and days in jail. Attitudes towards psychiatric medications, number of months in the MHC, symptom severity reported during research interviews, and MHC were used as control variables in the final models. Control variables were selected based on their theoretical significance, statistical significance in bivariate analyses (p < .05), and variable stability (both skewness and kurtosis). Although sex, criminal history, and substance use were identified in previous research to impact recidivism (Hartwell, 2004), these factors were not significant in bivariate analyses in this study and thus not used as controls. Participants with missing data were not included in the analysis. All quantitative analyses were conducted using SPSS predictive software version 20.0.
RESULTS Sample Description Table 1 presents the demographic characteristics of the study sample. Over half of the study participants were male (55%) and African American (56.3%). The average age of participants was 39.6 (SD = 12.1) years old. Nearly half of participants in the study reported to be in a relationship (48.8%). On average, study participants completed 11.3 (SD = 2.5) years of education. Very few participants worked at the time of the baseline interview (5%); just over half of the participants received Supplemental Security Income (SSI) or Social Security Disability Insurance (SSDI). At the time of the initial interview, participants were in the MHC program for an average of 7.6 months. After the
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K. E. Canada and A. J. Gunn TABLE 1 Sample Description (n = 80)
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Demographics
%*
N
Sex Female Race African American Bi-racial Caucasian Latino Native American
45
36
56 5 34 4 1
45 4 27 3 1
Relationship status Single In a relationship, not married Married Divorced/widowed
46 40 9 5
37 32 7 4
4 1
3 1
Program retention Graduated/remained active Terminated/missing Receiving SSI or SSDI Substance use diagnosis
90 10 51 84
72 8 41 67
Mental illness diagnosis Bipolar Schizophrenia spectrum Depression Major depression Other (ADHD, GAD, phobia)
59 30 5 3 5
47 23 4 2 4
Primary charge Retail theft/burglary Drug related Battery/assault Felony violent crime
44 21 18 87 14
35 17 14 69 11
Employment Part-time Full-time
M Age in years (range 19–65) Education in years (range 3–16) Months in MHC (range 2–18) Core network members (range 0–5) Arrests in 2 years prior to MHC (range 1–14)
39.6 11.3 7.6 2.7 2.9
SD 12.1 2.5 5.2 1.2 2.4
*Categories may not equal 100% due to rounding.
6-month follow-up period, 10% of the study sample was terminated unsuccessfully or went missing four or more months of the follow-up period. A participant is considered missing when the MHC staff is unable to locate the participant.
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The majority of individuals in the current study reported a primary diagnosis of bipolar disorder (58.8%). Of study participants, 90% reported a primary diagnosis that is considered to be a serious mental illness (i.e., bipolar disorder, major depression, schizophrenia, or schizoaffective disorder). The majority of study participants also reported a co-occurring substance use disorder (83.8%). The majority of participants were not experiencing severe psychiatric symptoms during the 7 days preceding the structured interview. The average rating of symptoms among participants was highest for anxiety, depression, and feelings of guilt. The majority of participants agreed or strongly agreed that medication is necessary, helps to manage stress, prevents psychiatric hospitalizations, controls symptoms, and improves self-esteem. Participants were asked to list up to five people who they consider to be their core group of family and friends. On average, study participants reported 2.7 people in their informal networks. This is comparable to a study using the same method of data collection and involving a very similar population who reported an average of 2.9 core network members (Skeem, Eno Louden, Manchak, Vidal, & Haddad, 2008). Participants perceived moderate social support from informal network members, M = 32.85, SD = 6.45, on a scale with a maximum rating of 40. Participants perceived slightly less support among formal network members, M = 29.56, SD = 7.58; these differences were statistically-significantly, t(77) = 4.82, p < .01. When looking at participants’ entire social network (formal and informal combined), participants perceived moderate support, M = 30.75, SD = 6.61. In the 2 years prior to MHC participation, participants were arrested, on average, 2.9 times. Participants reported the charge that led to their participation in the MHC. Most participants were arrested for retail theft or burglary charges (43.8%), drug related charges (21.3%), or battery and assault (17.4%). A small percentage of participants were charged with prostitution, criminal damage to property, trespassing, driving on a revoked license, forgery, probation violation, and resisting arrest (17.4%). The majority of charges were considered felonies (86.3%). Some participants reported that their charge was considered violent (13.8%). COURT DIFFERENCES All factors listed in Table 1 were examined for between court differences. Independent t-tests indicate that participants from Court A are, on average, older, t(78) = 2.49, p = .02, d = 0.55, and reported being arrested more often, t(78) = 2.38, p = .02, d = 0.55, in comparison to participants from Court B. Participants also differed in race, χ2 (1, n = 80) = 9.45, p
