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Abstract

Objective:

This preliminary study tested the efficacy of an evidence-based correctional intervention (Thinking for a Change) with an adapted delivery to incarcerated people with mental illness.

Methods:

A small-scale randomized controlled trial (N=47 men) was conducted. Outcomes were changes in aggression, number of behavioral infractions, and days in administrative segregation. Treatment targets were impulsivity, interpersonal problem-solving skills, and attitudes supportive of crime. Linear mixed-effects models were used to examine within-person and between-group differences over time, and nonparametric tests were used to examine between-group differences in criminal legal outcomes postintervention.

Results:

Statistically significant within-person differences were found for all treatment targets and for one study outcome (aggression). Statistically significant differences in impulsivity were found between the experimental and control groups (B=–7.10, p=0.02).

Conclusions:

Existing evidence-based correctional interventions can affect the lives of people with mental illness. Accelerated research in this area may benefit people with mental illness at high risk for criminal legal system involvement.

HIGHLIGHTS

Posttreatment, participants in the experimental group demonstrated significant improvements in interpersonal problem-solving skills, impulsivity, attitudes associated with criminal behavior, and aggression.
Posttreatment, participants in the experimental group demonstrated statistically greater improvement in impulsivity relative to the control group.
These findings highlight the importance of ensuring that individuals with mental illness can access and participate in interventions targeting the risk factors most closely associated with criminal legal system involvement.
Research (1) has found that people with mental illness face the same risk factors for recidivism as individuals without mental illness. These risk factors, termed criminogenic risks, are derived from the risk-need-responsivity (RNR) model (2) and include antisocial personality, antisocial behavior, antisocial cognitions, antisocial associates, substance use, marital and family circumstances, employment and education, and leisure and recreation. Other studies (3, 4) have demonstrated that justice-involved individuals with mental illness have increased criminogenic risk and that these factors mediate their risk for recidivism. This evidence supports the importance of interventions for this population that engage criminogenic risk factors as primary treatment targets, particularly given the limited success of existing services in reducing criminal legal system involvement among people with mental illness (5).
A meta-analysis (6) has established that interventions targeting criminogenic risk factors reduce recidivism by 20%–55% in the general correctional population. Furthermore, a systematic review (7) has identified nine such interventions already being used for people with mental illness. Results from that systematic review were preliminary but suggested that this class of interventions is associated with significant reductions in violence, aggression, and criminal recidivism among people with mental illness. Yet, the review (7) found that only half the interventions had been adapted for use with people with mental illness. This limitation is notable, given the RNR model’s emphasis on tailoring intervention delivery to the distinct learning and treatment needs of specific populations, such as people with mental illness (2).
One approach to increasing the responsiveness of criminogenically focused interventions for people with mental illness is to incorporate alternative strategies, such as the Targeted Service Delivery Approach (TSDA), into the delivery of existing interventions (8). The TSDA aims to compensate for neurocognitive and social impairments associated with mental illness during the delivery of the underlying intervention. To accomplish this goal, the TSDA uses five therapeutic strategies (repetition and frequent summarizing, amplification, active coaching, low-demand practice, and maximization of participation) during the delivery of existing evidence-based correctional interventions to maximize the ability of people with mental illness to fully engage with and benefit from these interventions. Details on the TSDA and examples of its incorporation into the delivery of correctional interventions have been published (8).
This report advances the literature on the development of criminogenically focused interventions for people with mental illness by presenting findings from a preliminary small-scale randomized controlled trial (RCT) on the effectiveness of Thinking for a Change (T4C) (9)—an evidence-based, criminogenically focused, correctional intervention—in conjunction with the TSDA (8) for people with mental illness in prison. The primary objective of this study was to examine the intervention’s impact on the primary treatment outcomes (aggression, number of behavioral infractions, and days in administrative segregation). Each of these outcomes is a primary concern in incarcerated populations, and aggression and institutional misconduct are indicators of postrelease offending (2, 10, 11). The secondary objective was to explore the intervention’s impact on key treatment targets (impulsivity, interpersonal problem-solving skills, and attitudes supportive of crime), which the RNR model identifies as important change mechanisms for interventions seeking to reduce criminal recidivism (2).

Methods

This study reports results from an RCT that was the second phase of a two-part study. This RCT included a small-scale pilot study of a newly adapted intervention. The original study design planned for four intervention cycles. However, two cycles were halted before the experimental treatment was successfully initiated, the first time because of administrative issues within the prison system and the second time because of COVID-19. Consequently, an intent-to-treat analysis was used for the two successfully initiated intervention cycles, which took place between January 2019 and December 2020. The study was approved by the institutional review board of the University of North Carolina at Chapel Hill. Written informed consent was obtained from all participants.
The experimental intervention had two components: T4C, version 3 (9)—an existing evidence-based, criminogenically focused intervention—and the TSDA (8). To support our goal of assessing the potential efficacy of the newly adapted intervention, study team members with at least a master’s degree in social work or an equivalent degree delivered the intervention. T4C is a highly structured, 25-session, group-based cognitive-behavioral therapy program, delivered in a closed format to 10–12 people up to twice a week across 14 weeks. This intervention comprises three interrelated modules: social skills, cognitive restructuring activities, and a problem-solving method for managing interpersonal conflict. The TSDA was used in conjunction with T4C to compensate for the neurocognitive and social impairments that impeded participants’ engagement with the intervention content (which remained unchanged).
The control condition included standard prison treatment and programming. In this study, standard prison mental health services included crisis services focused on addressing suicidal thoughts and behaviors and other mental health symptoms, psychiatric evaluations, consultations, medication management, and individual counseling to help stabilize mental illness so that a person could function appropriately in the prison environment. Study participants in both the experimental and control groups were eligible to receive standard prison treatment and programming. Prison staff made all decisions regarding individuals’ eligibility and the allocation of the services and programming offered by the prison.
Forty-seven people participated in the two intervention cycles, which took place in a men’s prison facility in the southeastern United States. At the beginning of each recruitment cycle, correctional staff provided the research team with a list of all potentially eligible participants at the facility, and study staff completed all recruitment activities. A description of recruitment efforts for this study has been reported (12).
Study inclusion criteria required that individuals be ages 18 years or older and have a mental illness (schizophrenia, schizoaffective disorder, or other psychotic disorder; bipolar disorder; or major depression), moderate to high criminogenic risk, and ≥1 year remaining in their prison sentence. Exclusion criteria included intellectual or developmental disability, restrictions that precluded involvement in group gathering spaces, and participation in T4C during the previous 6 months.
Study data were collected through four face-to-face interviews (screening, baseline, and 3 and 6 months after baseline) and a review of administrative records at 9 months after baseline. Study eligibility was determined through a screening interview, during which sociodemographic information was collected via participant self-report. An envelope method was used to randomly allocate eligible participants immediately following study enrollment. This random assignment method comprised consecutively numbered sealed envelopes with security linings to conceal group assignment from study staff and participants. Each envelope was assigned a study condition according to a randomization table. Study staff distributed envelopes in sequential order, noting participants’ study IDs on the outside of each envelope. The contents of the envelopes were then reconciled with the randomization table to ensure the integrity of the randomization process. All study interviews were conducted by research staff, who had a master’s degree in social work or an equivalent degree and were trained in the administration of all study measures by the study’s principal investigator (A.B.W.), a licensed mental health professional.
Mental health diagnoses were assessed by using the Mini-International Neuropsychiatric Interview (MINI) (13), a short, structured diagnostic interview that was developed and standardized on the basis of the Composite International Diagnostic Interview. The version of the MINI administered at study screening was informed by the DSM-5 and ICD-10.
Criminogenic risk level was assessed by using the Level of Service/Case Management Inventory during the screening interview. This tool is one of the world’s most frequently used and reviewed correctional assessment instruments.
Level of aggression was measured at baseline and at 3 months (i.e., treatment completion) by using the 12-item Buss-Perry Aggression Questionnaire–Short Form. Items on this questionnaire are scored on a 6-point Likert scale, with possible total scores ranging from 12 to 72 and higher scores reflecting more aggression (14).
A dichotomous variable was created by using prison administrative data to indicate receipt of at least one behavioral infraction for disciplinary reasons during the 6-month posttreatment period (i.e., between 3 and 9 months after baseline). Prison administrative data were used to calculate the cumulative number of days each participant spent in administrative segregation during the 6 months after completion of treatment.
Treatment targets were measured at baseline and 3 months (i.e., treatment completion). Interpersonal problem solving was measured via the 52-item Social Problem-Solving Inventory–Revised: Long (SPSI-R:L). Responses are recorded with a 5-point Likert scale. Raw scores for the entire scale were computed with the SPSI-R:L raw score derivation sheet. Total SPSI-R:L raw scores range from 0 to 20, with higher scores corresponding to more positive social problem-solving skills (15).
Attitudes were measured via the 46-item part B of the Measures of Criminal Attitudes and Associates instrument, which assesses attitudes and beliefs associated with criminal behavior. Responses are recorded in an agree versus disagree format (agree=1 and disagree=0, except for seven items that are reverse-coded). Scores range from 0 to 46, with higher scores indicating more supportive attitudes about crime (16).
Impulsivity was measured via the 30-item Barratt Impulsiveness Scale. Items are scored on a 4-point Likert scale, with scores ranging from 30 to 120. Higher scores indicate greater impulsiveness (17).
All analyses were conducted in SAS, version 9.4. First, chi-square tests were used to assess differences in behavioral infractions between study conditions (experimental vs. control) during the 6-month posttreatment period, and then nonparametric Wilcoxon rank sum tests were used to assess differences in median number of days spent in administrative segregation. Next, differences in treatment targets and study outcomes at treatment completion were examined with linear mixed-effects models via “PROC MIXED” in SAS. These models were used to examine change from baseline to postintervention in estimated mean scores within and between the experimental and control groups. Each model included fixed effects for group, time, and a group × time interaction term, with a random intercept specified for each participant. The group × time interaction term represented the treatment effect.

Results

The 47 men participating in the study had a mean±SD age of 41.6±9.9 years and a mean length of incarceration of 12.4±7.7 years. Thirteen participants identified as Black or African American (28%), 17 identified as White (36%), and 17 (36%) identified as more than one race, other, or unknown. Approximately one in 10 participants also identified as Hispanic. In terms of psychiatric diagnoses, 13 (28%) participants had a diagnosis of schizophrenia, schizoaffective disorder, or other psychotic disorder; 15 (32%) had bipolar disorder; and 19 (40%) had major depression. Finally, 37 (79%) participants had a “high” or “very high” criminogenic risk score, and 28 (60%) were incarcerated for a violent offense.
Table 1 shows the results of the linear mixed-effects models at treatment completion. The first section of the table demonstrates that the changes in estimated mean score for participants in the experimental group were all statistically significant and showed a trend in the desired direction. The third section of the table shows the treatment effects, which can be interpreted as the difference in the average change for each measure between the experimental and control conditions from baseline to 3 months. Whereas participants in the experimental condition (N=24) experienced a statistically significant decline in impulsivity (7.61 units) from baseline to 3 months, participants in the control group (N=23) had a nonsignificant average decline of 0.51 units. The associated treatment effect of −7.10 units was statistically significant. Additional analyses of the two remaining study outcomes, administrative segregation and behavioral infractions, during the 6 months following treatment completion found no statistically significant differences by study condition.
TABLE 1. Differences in the aggression outcome and the three treatment targets in the experimental and control groups at treatment completiona
 Experimental group (N=24)Control group (N=23)Treatment effectb
Treatment target or outcomeBc95% CIpBc95% CIpBc95% CIp
Aggression (AQ)−4.81−9.49 to −.13.04−2.68−7.33 to 1.96.25−2.12−8.72 to 4.47.52
Criminal attitude (MCAA)−5.32−8.54 to −2.11<.01−1.68−4.80 to 1.45.28−3.65−8.13 to .84.11
Impulsivity (BIS)−7.61−11.73 to −3.49<.001−.51−4.64 to 3.61.80−7.10−12.93 to −1.27.02
Interpersonal problem solving (SPSI-R:L)1.38.40 to 2.36<.01.68−.30 to 1.66.17.71−.68 to 2.09.31
a
AQ, 12-item Buss-Perry Aggression Questionnaire–Short Form; MCAA, 46-item Measures of Criminal Attitudes and Associates; BIS, 30-item Barratt Impulsiveness Scale; SPSI-R:L, 52-item Social Problem-Solving Inventory–Revised: Long.
b
Linear mixed-effect models were used to examine the difference between experimental and control groups in terms of the average change in scores from baseline to 3 months.
c
The unstandardized regression coefficient, which is called an estimate for fixed-effect terms.

Discussion

The results demonstrated that people with mental illness can engage in and benefit from existing evidence-based criminogenically focused interventions, which offer the potential to produce positive impacts in a number of domains (e.g., impulsivity). These findings underscore the need for continued and accelerated research in this area through large-scale randomized explanatory trials.
Of note, the participants in the experimental group experienced statistically significant changes in all three of the intervention’s key treatment targets, which represent dynamic aspects of criminogenic risk factors. These findings demonstrated that these treatment targets can be effectively influenced among people with mental illness. In addition, because prior research has found that reduced impulsivity can lead to substantial reduction in criminal legal recidivism (2), our findings provide a promising avenue for future research.
We found no differences in the number of behavioral infractions or days in administrative segregation between the experimental and control groups, despite prior research demonstrating that interventions such as T4C can positively affect these outcomes. These findings suggest the need for further research on these outcomes among incarcerated people with mental illness, with an emphasis on how they relate to criminal legal outcomes after release.
The goal of this small-scale study was to explore the effects of an adapted intervention on treatment targets and outcomes to determine whether larger-scale studies are warranted. Given the preliminary nature of this research, several limitations deserve consideration. First, although two cycles of the intervention were successfully completed, the original research design was not implemented as intended. Second, the use of treatment as usual as the control condition calls for caution in applying the findings to other treatment settings. Third, this research could not assess whether the T4C was more effective with the TSDA or alone. In addition, instances of behavioral infractions and time in administrative segregation may have reflected factors beyond the participants’ control, and the connection between these outcomes and community-based recidivism requires further research. The delivery of the intervention by study staff also may have affected the outcomes. Given the additional therapeutic support provided by the TSDA and the generally limited availability of mental health professionals in prisons, future research on this intervention will require implementation strategies to support its sustainability and scalability in prisons and other criminal legal settings. Finally, the criminogenically focused intervention chosen for this study, like all interventions of its class, was developed for use in correctional settings. Further research is needed to determine the best way to increase the reach and impact of similar interventions in community-based mental health settings.

Conclusions

To address the entrenchment of people with mental illness in the criminal legal system, policy makers must expand the continuum of services available to this population. This continuum must include interventions that directly target the risk factors most closely associated with criminal legal system involvement. The results of this study showed that, with support, people with mental illness and moderate-to-high levels of criminogenic risk factors can benefit from existing criminogenically focused interventions. Informed by decades of science, these existing interventions provide an evidence-based approach to addressing the criminogenic risk factors found among justice-involved people with mental illness. This research has provided support for the potential efficacy of a short-term, self-contained intervention in augmenting traditional mental health services.

Footnote

Trial registration: ClinicalTrials.gov: NCT03713398.

REFERENCES

1.
Bonta J, Law M, Hanson K: The prediction of criminal and violent recidivism among mentally disordered offenders: a meta-analysis. Psychol Bull 1998; 123:123–142
2.
Bonta J, Andrews DA: The Psychology of Criminal Conduct, 6th ed. New York, Routledge, 2017
3.
Wilson AB, Ishler KJ, Morgan R, et al: Examining criminogenic risk levels among people with mental illness incarcerated in US jails and prisons. J Behav Health Serv Res (Epub Nov 5, 2020)
4.
Matejkowski J, Ostermann M: Serious mental illness, criminal risk, parole supervision, and recidivism: testing of conditional effects. Law Hum Behav 2015; 39:75–86
5.
Skeem JL, Manchak S, Peterson JK: Correctional policy for offenders with mental illness: creating a new paradigm for recidivism reduction. Law Hum Behav 2011; 35:110–126
6.
Landenberger NA, Lipsey MW: The positive effects of cognitive-behavioral programs for offenders: a meta-analysis of factors associated with effective treatment. J Exp Criminol 2005; 1:451–476
7.
Parisi A, Wilson AB, Villodas M, et al: A systematic review of interventions targeting criminogenic risk factors among persons with serious mental illness. Psychiatr Serv 2022; 73:897–909
8.
Wilson AB, Farkas K, Bonfine N, et al: Interventions that target criminogenic needs for justice-involved persons with serious mental illnesses: a targeted service delivery approach. Int J Offender Ther Comp Criminol 2018; 62:1838–1853
9.
Bush J, Glick B, Taymans J, et al. Thinking for a Change. Washington, DC, US Department of Justice, National Institute of Corrections, 2011
10.
French SA, Gendreau P: Reducing prison misconducts: what works! Crim Justice Behav 2006; 33:185–218
11.
Cochran JC, Mears DP, Bales WD, et al: Does inmate behavior affect post-release offending? Investigating the misconduct-recidivism relationship among youth and adults. Justice Q 2014; 31:1044–1073
12.
Phillips J, Wilson AB, Villodas ML, et al: Feasibility of recruiting in prisons during a randomized controlled trial with people with serious mental illness. Clin Trials 2023; 20:22–30
13.
Sheehan DV, Lecrubier Y, Sheehan KH, et al: The Mini-International Neuropsychiatric Interview (MINI): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. J Clin Psychiatry 1998; 59(suppl 20):22–33
14.
Bryant FB, Smith BD: Refining the architecture of aggression: a measurement model for the Buss–Perry Aggression Questionnaire. J Res Pers 2001; 35:138–167
15.
D’Zurilla TJ, Nezu AM: Development and preliminary evaluation of the Social Problem-Solving Inventory. Psychol Assess 1990; 2:156–163
16.
Mills JF, Kroner DG, Forth AE: Measures of Criminal Attitudes and Associates (MCAA): development, factor structure, reliability, and validity. Assessment 2002; 9:240–253
17.
Patton JH, Stanford MS, Barratt ES: Factor structure of the Barratt Impulsiveness Scale. J Clin Psychol 1995; 51:768–774

Information & Authors

Information

Published In

Go to Psychiatric Services
Go to Psychiatric Services
Psychiatric Services
Pages: 1072 - 1076
PubMed: 37070261

History

Received: 11 July 2022
Revision received: 21 December 2022
Accepted: 2 February 2023
Published online: 18 April 2023
Published in print: October 01, 2023

Keywords

  1. Criminal legal
  2. Jails and prisons/mental health services
  3. Recidivism

Authors

Details

Amy Blank Wilson, Ph.D., M.S.W. [email protected]
School of Social Work (Wilson, Dohler) and Center for Excellence in Community Mental Health, Department of Psychiatry (Ginley), University of North Carolina at Chapel Hill, Chapel Hill; Department of Social Work, University of Minnesota Duluth, Duluth (Phillips); Department of Social Work, George Mason University, Fairfax, Virginia (Villodas); Center on Mindfulness and Integrative Health Intervention Development, College of Social Work, University of Utah, Salt Lake City (Parisi).
Jonathan Phillips, Ph.D., M.S.W.
School of Social Work (Wilson, Dohler) and Center for Excellence in Community Mental Health, Department of Psychiatry (Ginley), University of North Carolina at Chapel Hill, Chapel Hill; Department of Social Work, University of Minnesota Duluth, Duluth (Phillips); Department of Social Work, George Mason University, Fairfax, Virginia (Villodas); Center on Mindfulness and Integrative Health Intervention Development, College of Social Work, University of Utah, Salt Lake City (Parisi).
Melissa L. Villodas, Ph.D., M.S.W.
School of Social Work (Wilson, Dohler) and Center for Excellence in Community Mental Health, Department of Psychiatry (Ginley), University of North Carolina at Chapel Hill, Chapel Hill; Department of Social Work, University of Minnesota Duluth, Duluth (Phillips); Department of Social Work, George Mason University, Fairfax, Virginia (Villodas); Center on Mindfulness and Integrative Health Intervention Development, College of Social Work, University of Utah, Salt Lake City (Parisi).
Anna Parisi, Ph.D., M.S.W.
School of Social Work (Wilson, Dohler) and Center for Excellence in Community Mental Health, Department of Psychiatry (Ginley), University of North Carolina at Chapel Hill, Chapel Hill; Department of Social Work, University of Minnesota Duluth, Duluth (Phillips); Department of Social Work, George Mason University, Fairfax, Virginia (Villodas); Center on Mindfulness and Integrative Health Intervention Development, College of Social Work, University of Utah, Salt Lake City (Parisi).
Ehren Dohler, M.S.W.
School of Social Work (Wilson, Dohler) and Center for Excellence in Community Mental Health, Department of Psychiatry (Ginley), University of North Carolina at Chapel Hill, Chapel Hill; Department of Social Work, University of Minnesota Duluth, Duluth (Phillips); Department of Social Work, George Mason University, Fairfax, Virginia (Villodas); Center on Mindfulness and Integrative Health Intervention Development, College of Social Work, University of Utah, Salt Lake City (Parisi).
Caroline Ginley, M.S.W.
School of Social Work (Wilson, Dohler) and Center for Excellence in Community Mental Health, Department of Psychiatry (Ginley), University of North Carolina at Chapel Hill, Chapel Hill; Department of Social Work, University of Minnesota Duluth, Duluth (Phillips); Department of Social Work, George Mason University, Fairfax, Virginia (Villodas); Center on Mindfulness and Integrative Health Intervention Development, College of Social Work, University of Utah, Salt Lake City (Parisi).

Notes

Send correspondence to Dr. Wilson ([email protected]).

Competing Interests

The authors report no financial relationships with commercial interests.

Funding Information

This work was supported by NIMH (grant R34-MH-111855).The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

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