2022 Painting the Current Picture – Highlights & Insights

Painting the Current Picture A National Report on Treatment Courts in the United States

Highlights & Insights

Kristen DeVall, Ph.D. Christina Lanier, Ph.D. Lindsay J. Baker, M.A.

Painting the Current Picture A National Report on Treatment Courts in the United States

Highlights & Insights

Kristen DeVall, Ph.D.1 Christina Lanier, Ph.D.1 Lindsay J. Baker, M.A. 1 The first two authors are listed alphabetically and both authors contributed equally to the preparation of this monograph.

Painting the Current Picture: A National Report on Treatment Courts in the United States, Highlights & Insights This project was supported by Grant No. 2019-DC-BX-K002 awarded by the Bureau of Justice Assistance.

The Bureau of Justice Assistance is a component of the Department of Justice’s Office of Justice Programs, which also includes the Bureau of Justice Statistics, the National Institute of Justice, the Office of Juvenile Justice and Delinquency Prevention, the Office for Victims of Crime, and the SMART Office. Points of views or opinions in this document are those of the author and do not necessarily represent the official position or policies of the U.S. Department of Justice.

All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the National Drug Court Resource Center.

Kristen DeVall, Ph.D., Co-Director Christina Lanier, Ph.D., Co-Director National Drug Court Resource Center University of North Carolina Wilmington 680 S. College Road Wilmington, NC 28403-5978 (910) 962-2440 ndcrc.org Cover design by Ben Yerby Publication design by Ben Yerby Prepared by the National Drug Court Resource Center Drug courts perform their duties without manifestation, by word or conduct, of bias or prejudice, including, but not limited to, bias or prejudice based upon race, religion, gender, national origin, disability, age, sexual orientation, language, or socioeconomic status.

Copyright © 2022 National Drug Court Resource Center

Acknowledgements The National Drug Court Resource Center (NDCRC) would like to extend gratitude and thanks to everyone involved in this important project. We sincerely appreciate the efforts of the individuals and organizations within the states/territories that completed the survey. This information serves as the basis for the publication and is critical to our understanding of treatment courts.

NDCRC appreciates the Bureau of Justice Assistance at the U.S. Department of Justice whose support made this project and publication possible.

The authors sincerely thank Paul Gregory, Ph.D., David J. Hartmann, Ph.D., Doug B. Marlowe, J.D., Ph.D., and David Wright, Ph.D. for serving as peer reviewers and offering insights and suggestions. Additional thanks go to Savannah Bryson for assisting with data collection, Ben Yerby, M.A., for designing the report, as well as the NDCRC staff and the University of North Carolina Wilmington for their support of this effort.

About the Authors Kristen E. DeVall, Ph.D., received her Ph.D. in sociology from Western Michigan University in 2008. At present she is the co-director of the National Drug Court Resource Center & a professor of sociology and criminology at the University of North Carolina Wilmington. She has conducted evaluations of numerous treatment court programs and other criminal justice initiatives since 2004. Several statewide evaluations have involved the collection and analysis of both quantitative and qualitative data, as well as the merging of large datasets. Dr. DeVall has also garnered over $14 million in grant funding from SAMHSA, BJA, OJJDP, as well as state and local entities to support various treatment courts & other criminal justice programs. In addition, she worked as a case manager for a community corrections program for seven years. Providing direct services to individuals involved with the criminal justice system allowed her to see firsthand how the system operates and identify opportunities for system-level and policy change. Overall, her work seeks to bridge the gap between academia and practitioners, as well as influence the development of evidencebased policies and practices.

Christina Lanier, Ph.D., is the co-director of the National Drug Court Resource Center and a professor of sociology and criminology at the University of North Carolina Wilmington. She received her Ph.D. in sociology from the University of Delaware in 2006. She has extensive experience in the area of program evaluation and has conducted several evaluations of treatment courts, as well as other criminal justice programs such as the Swift and Sure Sanctions Probation Program (SSSPP) in Michigan and the North Carolina Treatment Alternatives for Safe Communities (TASC). Additionally, Dr. Lanier has secured over $10 million in federal (OJJPD, BJA, and SAMHSA), state, and local agencies. Her research has been published in Substance Use and Misuse, The Prison Journal, Violence Against Women, Homicide Studies, International Journal of Offender Therapy and Comparative Criminology, and The Australian and New Zealand Journal of Criminology. Dr. Lanier’s focus is on linking the work of researchers with practitioners to develop policy and implement social change.

Lindsay Baker, M.A., earned a M.A. in Criminology from the University of North Carolina Wilmington in 2022.

During her time as a student, Lindsay garnered experience in the areas of restorative justice and reentry which ultimately sparked her interest in treatment court work. Lindsay served as a graduate fellow with the NDCRC and is now employed there as a Social Science Researcher. In this role, Lindsay assists with the collection, analysis, and dissemination of treatment court data to multiple audiences. As part of the NDCRC’s team, Lindsay seeks to highlight the importance of therapeutic jurisprudence and treatment in the justice system.

Contents Acknowledgements

iv

About the Authors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv

Introduction

1

What are Treatment Courts?

2

Figure 1: Milestones in the Development of Treatment Courts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Survey Methodology

5

Response Rates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Growth of Treatment Courts

6

Figure 2: Number of Treatment Courts in the United States from 1989 to 2019 . . . . . . . . . . . . . . . . . . . 6

Treatment Court Appropriations

7

Table 1: Treatment Court Federal Appropriations (in millions) FY2014–2019 . . . . . . . . . . . . . . . . . . . . . . 7 Figure 3: Number of Treatment Courts in the U.S. and Territories (2019) . . . . . . . . . . . . . . . . . . . . . . . . . 8

All Adult & Juvenile Program Participants

10

Table 2: All Adult & Juvenile Program Participants in 2019 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Table 3: Adult & Juvenile Program Participants by Court Type in 2019 . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Issues to Consider

12

Table 4: Comparison of ADC Participants with Other Criminal Justice Populations by Race/ Ethnicity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 Table 5: Comparison of JTC Participants with Other Criminal Justice Populations by Race/Ethnicity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Table 6: Select Substance Use & Treatment Access Indicators from 2019 National Survey of Drug Use and Health (SAMHSA) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 Table 7: % of States/Territories Reporting Specific Drugs of Use by Treatment Court Participants by Court Type (2019) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

References

20

Appendices

23

Appendix A: Treatment Courts by Type and State/Territory (2019) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

Introduction The 2019 issue of the Painting the Current Picture: A National Report on Treatment Courts in the United States (hereafter referred to as PCP) represents the sixth time an in-depth analysis of treatment court programs across the United States has been conducted. The current version was conducted by the National Drug Court Resource Center (NDCRC), located at the University of North Carolina Wilmington (UNCW). All previous iterations of this survey (2004, 2005, 2008, 2011, 2016) were conducted by the National Association of Drug Court Professionals (NADCP). The monograph has continued the long-standing tradition of providing a detailed snapshot of the treatment court field within the United States. Especially noteworthy is that these data provide the authors with the ability to monitor trends and to highlight similarities and differences in the findings obtained over time. The monograph also provides a synopsis of the most recent scholarly literature on treatment courts. Summaries of the extant literature for each treatment court type include a brief overview of the history and structure, best practice standards, guiding principles, effectiveness and cost-benefit findings, and directions for future research.

New to the 2019 PCP monograph is an organization of information by treatment court type. While aggregate data regarding all treatment court programs is provided, several interesting trends are revealed when examining data by program type and age group served. Similar to the 2014 PCP, there are important lessons for the field to consider and on which action should be taken. These lessons include: First, the type and quality of data being gathered regarding treatment courts varies greatly across states/ territories. Data availability and quality have great implications for the type of research questions we can answer about treatment courts, our ability to monitor trends over time, and to obtain an accurate picture of what is happening in the field.

Second, racial/ethnic disparities in both enrollment in and graduation from treatment courts continues to be an issue within the treatment court field. This finding was highlighted in the 2014 PCP monograph. In 2019, the National Association of Drug Court Professionals and National Center for State Courts published the Equity & Inclusion: Equivalent Access Assessment & Toolkit, with support from the Office of National Drug Control Policy (ONDCP). In the same year, American University, with BJA funding, launched the Racial & Ethnic Disparities (RED) Assessment Tool. Both of these tools are designed to assist jurisdictions with identifying and addressing disparities.

Third, for the past 10-15 years much attention and resources have been paid to the opioid epidemic and how treatment courts are well-positioned to address the needs of high-risk/high-need individuals with an opioid use disorder. However, what has received less attention is the fact that in some regions/jurisdictions, stimulant use has been and continues to be the prevalent drug of use among individuals. A small body of research has demonstrated that treatment courts are effective in addressing the needs of this population of individuals as well (Farrell et al 2019; Jones et al 2019; Lanier & DeVall, 2017).

These issues represent opportunities for the field to continue the legacy of using data to make informed decisions in order to advance the mission of treatment courts. These issues are not insurmountable. With a commitment to excellence in mind and the necessary resources, improvements can be made. Strategies are currently being implemented to address these areas for needed enhancements.

INTRODUCTION

1

What are Treatment Courts?

The legacy of treatment courts began in 1989 in Miami-Dade County (FL). At the time, the United States was embroiled in the “war on drugs” and large percentages of individuals being processed through criminal justice systems across the country had similar characteristics: 1) a substance use disorder that contributed to criminal behavior; 2) had cycled through the criminal justice system one or more times previously; and 3) were charged with non-violent crimes. A small but determined group of criminal justice practitioners came together and openly expressed dissatisfaction with the traditional criminal justice system that was ineffective at reducing recidivism. They argued that the strategies being utilized did not focus on nor address the underlying criminogenic needs of justice-involved individuals. To this end, they sought to design a strategy for more effectively intervening in the lives of these individuals so as to stop the revolving door cycle in/out of the criminal justice system in which so many individuals were stuck. Out of these efforts the drug court model was born.

The adult drug court model is one criminal justice initiative that quickly obtained bi-partisan support in part because it helped courts better assess and manage system-wide court backlogs. Based upon the positive results, additional resources were made available, and programs began expanding to jurisdictions across the U.S. In an effort to provide guidance regarding what the drug court model entailed, NADCP, the Bureau of Justice Assistance (BJA) and the Drug Court Programs Office (DCPO) co-authored Defining Drug Courts: The Key Components in 1997. In addition, the Drug Court Programs Office (DCPO), established in 1995, and merged with BJA in 2003, supported a recidivism study, along with NIJ, and began to assess the impact of treatment courts (Roman et al. 2003). The authors found that drug court graduates had a recidivism rate (measured as an arrest resulting from a criminal charge) of only 16.4% one-year after program completion and a rate of only 27.5% two years after completion. Again, in 2011, the NIJ/DOJ funded the Multisite Adult Drug Court Evaluation (NIJ, 2012). This study was a 5-year longitudinal process, impact, and cost evaluation of 23 drug courts and six comparison courts in eight states. The results of this evaluation led to the development of the Research 2 Practice initiative, a BJA/NIJ sponsored endeavor, which identified seven evidence-based components for a successful drug court program (BJA & NIJ, 2012).

Since 1989, the drug court model has served as the foundation for the development of other treatment court programs designed to serve specific target populations that have underlying substance use disorders which have contributed to their involvement in the criminal justice, juvenile justice, or child welfare systems.

Over the past 30 years, numerous milestones have been achieved within the treatment court movement (see Figure 1).

2

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Figure 1: Milestones in the Development of Treatment Courts1

1989 • First drug court opens in Miami, Florida

1996 • First NADCP mentor drug court established • First felony domestic violence court opens in Brooklyn, New York

1992 • First women’s drug court opens in Kalamazoo, Michigan

1997 • First tribal healing to wellness court opens in Fort Hall, Idaho

1993 • First community court opens in Brooklyn, New York

1994 • Congress passes Violent Crime Control and Law Enforcement Act (the “Crime Bill”) • National Association of Drug Court Professionals (NADCP) founded

1995 • Drug Courts Program Office (DCPO) established in U.S. Department of Justice

• NADCP, DCPO, and the Bureau of Justice Assistance (BJA) release Defining Drug Courts: The Key Components • First mental health court opens in Broward County, Florida

1998 • National Drug Court Institute (NDCI) founded

2000 • American Bar Association releases Proposed Standard 2.77 — Procedures in Drug Treatment Courts

• First DWI court opens in Doña Ana, New Mexico • First juvenile drug court opens in Visalia, California • First family drug court opens in Reno, Nevada

2001 • NADCP and National Council of Juvenile and Family Court Judges release 16 Strategies for Juvenile Drug Courts • First juvenile mental health court opens in Santa Clara County, California

1

Adapted from Marlowe et al. (2016) with additions from 2015–2019.

Figure 1 (Cont.): Milestones in the Development of Treatment Courts1

2002 • DCPO merges into BJA

2007 • National Center for DWI Courts (NCDC) founded

2008 • First veterans treatment court opens in Buffalo, New York

2010 • National Drug Court Resource Center opens

2015 • Volume II of Best Practice Standards published

2017 • 10 Key Components of Veterans Treatment Courts published • First opioid court opens in Buffalo, New York

2018 • Best Practice Standards vols. I & II (revised) published • Spanish translations of Best Practice Standards vols. I & II published

• Justice for Vets founded

2019 2011 • Multisite Adult Drug Court Evaluation finds that drug courts reduce crime and substance abuse and improve family functioning and employment

2013 • Volume I of Best Practice Standards published

2014 • Tribal Healing to Wellness Courts: The Key Components published

1

Adapted from Marlowe et al. (2016) with additions from 2015–2019.

• Family Treatment Court Best Practice Standards published

Survey Methodology The 2019 Painting the Current Picture: A National Report on Treatment Courts in the United States survey was disseminated to state/territory treatment court coordinators on July 30, 2020, using Qualtrics, a web-based survey platform. Respondents were asked to complete the survey instrument by September 30, 2020. However, due to myriad challenges brought on by the COVID-19 pandemic, data collection did not conclude until February 28, 2021. This provided respondents with seven full months to complete the electronic survey. Prior to beginning this survey project, the PCP survey instrument was submitted to the Office of Management and Budget (OMB) for approval. In addition, the University of North Carolina Wilmington (UNCW) Institutional Review Board reviewed the project protocol and survey instrument to ensure compliance with human subjects’ protection. Approval was granted by both external entities.

The PCP survey was distributed to the designated state/territory coordinator(s) in all 50 states, the District of Columbia, Guam, Northern Mariana Islands, and Puerto Rico. For states/territories where the designated coordinator could complete the survey on behalf of all programs within their state/jurisdiction, they were asked to answer the questions for the entire state/territory. However, in states/territories where these data were not available (e.g., where there was no statewide management information system), the state/ territory coordinator was asked to send the survey instrument to local treatment court administrators/ coordinators to complete. National Drug Court Resource Center (NDCRC) staff then aggregated all data received from these local personnel to create a state/territory profile/summary. Respondents were asked to provide data for 2019 (January 1, 2019–December 31, 2019).

The survey asked about various treatment court types for both adults and juveniles. More specifically, the programs included in the analysis are: adult drug courts (ADC), DUI/DWI courts, family treatment courts (FTC), mental health courts (MHC), veterans treatment courts (VTC), juvenile drug treatment courts (JDTC), and juvenile mental health courts (JMHC)2.

Response Rates Respondents from 52 of 54 states/territories responded to the PCP survey. New Jersey and Wisconsin did not respond to the PCP survey. However, five respondents only provided the number of operational treatment courts (by type) but did not answer any additional survey questions. Therefore, the overall response rate for the 2019 PCP is 87.0%. It should be noted that jurisdictions do not collect data in the same way and the reliability of data collection varies greatly across states/territories. Some items were not applicable to all jurisdictions and/or treatment court types. Therefore, only valid jurisdictions were included in the denominator when calculating response rates and percentages.

2 The following programs were excluded from this analysis: adult and juvenile co-occurring disorder, adult opioid intervention, adult reentry, adult other, and juvenile truancy.

SURVEY METHODOLOGY

5

Growth of Treatment Courts Figure 2 presents the growth of treatment courts over the past thirty years (1989–2019). As can be seen, there has been an exponential increase in the number of programs during this time. It should be noted that data were not available for 2015–2018. In 2016 and 2019, there were transitions in the entities managing the NDCRC. To strengthen the quality of the data being collected, a set of new survey tools were developed that involved obtaining the Office of Budget and Management (OMB) approval. In addition, there were delays caused by the COVID-19 pandemic.

As of December 31, 2019, 3,8563 treatment courts were operational within the United States (90.8% of these programs serviced adults and 9.2% serviced juveniles). This represents a 12% increase in the number of operational programs over the previous five years. However, this increase was largely among adult programs (17%), as compared to juvenile where there was a 22% decrease in the total number of programs. Figure 3 displays the total number of operational treatment courts by state/territory. Appendix A presents the number of programs by program type for each state/territory.

Of these 3,856 programs, adult drug courts continue to be the most prevalent model, comprising close to half (44.0%; n=1,696) of all treatment courts. Other prevalent models included: adult mental health courts (12.7%), veterans treatment courts (12.4%), family treatment courts (8.7%), juvenile drug courts (7.9%), and DUI/DWI courts (6.7%). The remaining treatment court models together represented 7.6% of all treatment courts.

Federal drug treatment court programs were excluded from this study. Given the specific focus of the current study, readers should be cautioned against comparing the total number of problem-solving court programs (reported in 2014) with the total number of treatment court programs reported in this study. In addition, two states (i.e., New Jersey and Wisconsin) did not provide data for this study.

Figure 2: Number of Treatment Courts in the United States from 1989 to 2019

3

6

This total includes THWCs, but excludes juvenile truancy courts.

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Treatment Court Appropriations Federal appropriations for treatment courts have been earmarked within the budgets for the U.S. Department of Justice (DOJ) and the Substance Abuse and Mental Health Services Administration (SAMHSA) (Sacco, 2018; U.S. General Services Administration, n.d.; SAMHSA, n.d.). Funding has grown over the years, but it is notable that the appropriations increased by 74% between 2014 and 2019 (Table 1). More specifically, DOJ appropriations increased by 122% and SAMHSA appropriations increased by 33%. During this five-year period, appropriations for veterans treatment courts increased by 450% and adult drug courts (Drug Court Programs) by 90%. This increase in federal funding over time is notable and a testament to the important work treatment courts do to address the needs of criminal-justice system-involved individuals with a substance use disorder in order to address needs that will assist communities in ensuring public safety and reducing recidivism. In addition to these funding streams, starting in FY2017, Congress started appropriating funds under the Comprehensive Opioid, Stimulant, and other Substance Abuse Program (COSSAP), which also supports family treatment courts; law enforcement-led diversion and deflection programs with referral to treatment; and prosecution and court-based diversion programs serving individuals identified as lower risk and need.

Table 1: Treatment Court Federal Appropriations (in millions) FY2014–2019 FY 2014

FY 2015

FY 2016

FY 2017

FY 2018

FY 2019

Change between 2014–2019

US Department of Justice Drug Court Discretionary $ 40.50 $ Grant Program Veterans Treatment Courts $

4.00 $

41.00 $ 42.00 $ 43.00 $ 5.00 $

6.00 $

75.00 $

77.00

7.00 $ 20.00 $ 22.00

DOJ sub-total $ 44.50 $ 46.00 $ 48.00 $ 50.00 $ 95.00 $

90% 450%

99.00

122%

52.75 $ 50.00 $ 60.00 $ 58.00 $ 70.00 $ 70.00

33%

97.25 $

74%

Substance Abuse & Mental Health Administration SAMHSA sub-total $

Total appropriations $ (in millions)

TREATMENT COURT APPROPRIATIONS

96.0 $ 108.0 $ 108.0 $ 165.0 $

169.0

7

Figure 3: Number of Treatment Courts in the U.S. and Territories (2019)

All Adult & Juvenile Program Participants A total of 140,402 adult and juvenile individuals were enrolled in the 3,7474 treatment court programs that were operational during 2019 (see Table 2). A total of 61,927 participants had a disposition (either successful or unsuccessful) and 71,368 individuals were still enrolled in the programs as of December 31, 2019. Among participants with a disposition, 59.7% graduated. Of interest to scholars, practitioners, and other treatment court stakeholders is the demographic profile of these participants. Unfortunately, not all states/territories provided demographic data regarding participants. What follows is a summary of the demographic characteristics of treatment court participants in terms of gender and race/ethnicity based on available data. Table 3 presents these data by by treatment court type.

Table 2: All Adult & Juvenile Program Participants in 2019 All

Adult

Juvenile

3,8561

3,500

356

140,402

136,771

3,631

59.7

59.7

62.1

Male

66.7

66.5

70.3

Female

33.3

33.4

29.7

Black/African American

19.3

19.1

26.6

Caucasian/White

71.4

71.6

60.8

American Indian/Alaskan Native

2.4

2.3

4.0

Asian/Pacific Islander

1.5

1.4

3.5

Other

5.5

5.5

5.1

Male

62.1

62.2

60.1

Female

58.5

58.4

61.7

Black/African American

57.3

57.3

58.3

Caucasian/White

61.5

61.5

62.1

American Indian/Alaskan Native

58.9

59.5

46.5

Asian/Pacific Islander

66.4

65.2

80.4

Other

57.6

57.7

52.9

# of Courts # of Participants Graduation Rate (%)

Participants by Gender (%)

Participants by Race (%)

Graduation Rate by Gender (%)

Graduation Rate by Race (%) 2

1

This total includes THWCs, however THWC participant information were not included in this table.

2

Due to great variation in how states/territories measured ethnicity (i.e., Hispanic/Latinx), these data were excluded from this table.

4

10

This total excludes THWCs.

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Table 3: Adult & Juvenile Program Participants by Court Type in 2019 ADC

DUI/ DWI

FTC

VTC

MHC

JDTCP

JMHC

1,696

257

335

480

490

305

46

90,990

13,072

6,993

9,592

15,494

3,108

523

56.5

80.1

47.2

76.7

57.2

60.4

72.5

Male

66.2

75.3

24.8

92.7

63.2

72.6

57.8

Female

33.8

24.6

75.2

7.2

36.7

27.4

42.0

Black/African American

16.3

21.2

12.2

27.4

31.3

25.1

35.4

Caucasian/White

74.3

70.3

76.6

65.9

59.3

61.4

57.1

American Indian/Alaskan Native

2.4

3.1

2.4

0.8

2.4

4.5

0.5

Asian/Pacific Islander

1.2

2.7

2.0

1.6

1.5

4.1

0.2

Other

5.9

2.7

6.8

4.3

5.5

4.9

6.8

Male

58.0

78.9

52.7

77.3

58.2

58.0

73.0

Female

57.6

79.3

49.1

79.2

57.9

58.3

72.0

Black/African American

54.8

76.9

37.3

74.2

48.0

53.9

73.0

Caucasian/White

58.7

81.1

51.9

78.0

57.4

60.6

70.7

American Indian/Alaskan Native

62.0

61.3

33.3

77.8

53.3

43.9

100.0

Asian/Pacific Islander

61.7

75.0

62.2

74.1

61.4

80.0

100.0

Other

57.5

64.2

40.4

78.0

56.4

48.1

68.8

Alcohol

63.0

100.0

54.5

91.2

80.6

80.0

70.0

Cocaine/crack

19.6

9.7

12.1

20.6

12.9

6.7

10.0

Heroin

30.4

16.1

30.3

14.7

16.1

6.7

10.0

Marijuana

58.7

77.4

57.6

73.5

71.0

93.3

90.0

Methamphetamine

67.4

41.9

75.8

55.9

61.3

56.7

30.0

Opioids

50.0

29.0

51.5

23.5

38.7

26.7

—

# of Courts # of Participants Graduation Rate (%)

Participants by Gender (%)

Participants by Race (%)

Graduation Rate by Gender (%)

Graduation Rate by Race (%) 1

Drugs of Use (%)

1

Due to great variation in how states/territories measured ethnicity (i.e., Hispanic/Latinx), these data were excluded from this table.

ALL ADULT & JUVENILE PROGRAM PARTICIPANTS

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Issues to Consider Results from the Painting the Current Picture: A National Report on Treatment Courts in the United States revealed three areas to be addressed, which include data collection and management needs, equity and inclusion needs, and enhanced focus on stimulants as drugs of use and concern. What follows is a detailed discussion of the issue, relevance for treatment court stakeholders, and suggestions for improvement.

Treatment Court Data: Availability & Quality Pursuant to Adult Drug Court Best Practice Standards Standard #10, Monitoring & Evaluation, “The Drug Court routinely monitors its adherence to best practice standards and employs scientifically valid and reliable procedures to evaluate its effectiveness” (NADCP, 2018b). Moreover, the best practice standards and essential elements for other treatment court types (i.e., DUI/DWI, family treatment courts, veterans treatment courts, juvenile drug treatment courts, and adult mental health courts) also include provisions for monitoring and evaluation. However, the first step toward fully realizing this best practice standard (BPS) is for programs to systematically collect the demographic and programmatic data necessary to examine whether programs are operating with fidelity to the model and producing the intended outcomes. While the focus for BPS #10 is on the external evaluation of programs, the same data needed for evaluation can also be used by program staff and administrators to “…monitor their everyday operations, report essential performance information, identify areas of success, and bring to light problem areas or ways to improve” (Rempel, 2010, p. 2). Additionally, these data can be used to make decisions regarding resource allocation and identifying programmatic needs which can be used to justify grant funding applications.

Regardless of the data collection strategy developed/implemented, the quality of data being collected is of utmost importance. To this end, it is critical that all team members responsible for data collection have been trained on how to gather this information and that a systematic process has been implemented to ensure consistency across individuals and over time. This is especially important given that the treatment court model involves data from multiple sources (e.g., treatment, probation, recovery support service providers, etc.). To this end, clearly defining which team members are responsible for data collection is imperative to ensuring the data are consistent and reliable. For example, if drug/alcohol testing results are to be entered into the data collection system every Friday, it is imperative that team members responsible for entering these data follow this protocol. One strategy for ensuring consistent and timely data entry is to conduct routine audits of the data system. Moreover, this process will allow for the correction of data errors and entering any missing data. The quality of data collected directly impacts the ability of programs to make data-informed decisions, as well as the ability of external evaluators to conduct process and outcome evaluations.

At present only 59.6% of states/territories have a statewide management information system which stores demographic and programmatic information regarding treatment court participants. Therefore, more than one-third of states/territories do not have a statewide data collection strategy and storage system in place.

Within these jurisdictions, local programs are responsible for determining which data to collect and how best to store this information. This has resulted in measures being defined differently and/or not being collected.

For example, participant race and ethnicity measures were not defined consistently across all states/ territories. Some jurisdictions defined race and ethnicity separately (as two measures), whereas others combined the terms into one measure. This resulted in an inability to fully examine variations in treatment court access and graduation for all racial/ethnic groups. According to the Center for Court Innovation (2013), “The creation of a statewide data tracking system will enable states [and territories] to engage in rigorous research and evaluation efforts—either state-led or in collaboration with external evaluators” (p.

5). In summary, the treatment court field would benefit greatly from two significant improvements within this area: 1. 100% of states/territories implement a statewide management information system used to track treatment court participant data.

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2. The establishment of standardized definitions for all key measures used to examine treatment court program processes and outcomes.

One effort underway to address this issue is the Strengthening the Foundation initiative, an advisory panel of national experts, funded by BJA. The panel has been charged with guiding the development of a new conceptual framework for the evaluation of treatment courts. Their objectives are to develop universal performance indicators to support treatment court evaluations, assess individual states data collection capacity, and identify gaps and recommendations for building capacity. BJA State-Based Training and Technical Assistance Program provides technical assistance to states in building data capacity and BJA encourages states to request funding through its treatment court program to support data collection.

Equity & Inclusion: Racial & Ethnic Disparities in Treatment Courts An area that continues to draw attention within treatment courts is equity and inclusion. As noted in the Adult Drug Court Best Practice Standard Vol. 1 (2018a), “[D]rug courts have an affirmative legal and ethical obligation to provide equal access to their services and equivalent treatment for all individuals (p. 12).” In other words, courts should not discriminate based on race, ethnicity, gender, religion, sexual orientation, disability, etc. Many treatment courts have indeed made concerted efforts to address the inequities identified within their courts. Most recently, some treatment courts have begun utilizing AU’s RED tool and/ or NADCP’s Equity and Inclusion Toolkit, to assist in identifying areas of inequity. Specific uses of the Toolkit information include: developing program marketing plans, analyzing treatment court access process, developing time task plans. In addition, several states are working to incorporate the Equity and Inclusion Assessment Tool within an existing statewide database system. Moreover, discussions are underway regarding the creation of a juvenile equity and inclusion toolkit. While progress has been made, the issue of equal access to treatment courts is still one to be addressed.

Research suggests that there may be a discrepancy in the experience of participants based on their race/ ethnicity. Findings from several studies have revealed differences in admission rates, as well as graduation rates by race/ethnicity (Dannerbeck et al., 2006; DeVall & Lanier, 2012; Gallagher, 2013; Ho et al., 2018; McKean & Warren-Gordon, 2011; Nicosia et al., 2013; Sechrest & Shicor, 2001; Shannon et al., 2018; Sheeran & Heideman, 2021). In their study of diversion outcomes among a male sample, Nicosia et al. (2013) found that Black and Hispanic males were significantly less likely to receive diversion to drug treatment court as compared to similarly situated White males. Relatedly, Sheeran and Heidman’s (2001) examination of admittance rates in a Milwaukee drug treatment court revealed that non-Hispanic Blacks were 44% less likely to be admitted to the court even after controlling for other measures. Interestingly, the authors also examined the reasons reported for participants being rejected by race/ethnicity. Non-Hispanic Black individuals were more likely to be deemed ineligible for reasons such as prior criminal record or the nature of the current charge. As noted by Sheeran and Heidman (2001) “…exclusionary criteria may be limiting the reach of the program and…could be modified to reduce the disproportionate impact of certain eligibility and requirements” (p. 12). However, while these studies did find significant variations in who is accepted into treatment court, it is important to note that others have found that to not be the case (e.g., Ho et al., 2018).

Research examining graduation rates has also identified differences in outcomes based on race/ethnicity.

DeVall and Lanier’s study of a mid-Western treatment court found that non-White participants had a graduation rate of 22.3%, which was significantly lower than that of White participants at 40.7%. Black participants had 40% lower odds of graduating as compared to White participants in Ho et al.’s (2018) study of 142 treatment courts. Studies have found that even after controlling for factors such as prior charges, drug of use, etc. Black participants are significantly less likely to successfully complete treatment court (Gallagher, 2013; Sheeran & Heidman, 2021).

Research investigating disparities in juvenile treatment courts have had results similar to that of adult treatment courts with regard to race/ethnicity. Studies have found that Caucasian/White individuals are represented at a much higher percentage than other racial/ethnic groups (Barnes et al., 2009; Stein et al., 2013; Stein et al., 2015; Sullivan et al., 2016; Tanner-Smith et al., 2016). For example, Stein et al.’s (2015) ISSUES TO CONSIDER

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metal-analytic review of 31 JDTC studies revealed that Caucasian/White participants constituted, on average, 61.3% of the courts’ populations. Similarly, Tanner-Smith et al.’s (2016) meta-analysis of 46 studies found that the average percentage of Caucasian/Whites across studies was 67.0%. Graduation rates across race/ethnicity have also been found. Applegate and Santana (2000) found that African American/Black youth were 2.7 times less likely to graduate as compared to youth that were not African American/Black.

Caucasian/White participants were more likely to graduate as compared to minority participants in Stein et al.’s (2013) review of 41 studies on JDTC. It is important to note, however, that some research has revealed no effect of race/ethnicity on JDTC admission and/or graduation (Barnes et al., 2009; Mackin et al., 2010).

Given the identified issues related to race/ethnicity, presented below is an overview of the percentage of individuals represented in treatment courts by race/ethnicity and other criminal justice populations. While statistical comparisons are not made, an examination of the proportion of representation can provide a picture of the overall distribution by race/ethnicity.

Table 4 provides comparisons of ADC participants with other criminal justice populations by race and ethnicity. Based on the data reported, individuals identified as Caucasian/ White constituted 71.6% of all adult treatment court participants in 2019, while making up 69.8% of all individuals arrested for a drug offense and only 54.0% of probationers. In contrast, individuals identified as Black/African American made up only 19.1% of all adult treatment court participants but accounted for 27.4% of drug offense arrestees and 30.0% of probationers. Additionally, Black/African Americans constituted 33.6% of persons in jail.

Thus, depending on the comparison population, Black/African Americans are under-represented in adult treatments courts by 9% to almost 15%. These data suggest an over-representation of Caucasian/White participants and an under-representation of Black/African American participants. Similar trends are found when examining those individuals who were identified as Hispanic/Latinx, however, these data should be interpreted with caution given the inconsistency of collection of participants’ ethnicities.

Table 4: Comparison of ADC Participants with Other Criminal Justice Populations by Race/Ethnicity Caucasian/ White1

Black/ African American1

American Indian/ Alaskan Native1

Asian/ Pacific Islander1

Hispanic/ Latinx

Adult Treatment Courts

71.6

19.1

2.3

1.4

10.0

US Population (2019) 2

60.0

12.4

0.7

5.8

18.4

Any offense

67.5

27.9

2.8

1.6

19.8

Drug offense

69.8

27.4

1.4

1.5

21.9

Probationers 4

54.0

30.0

1.0

1.0

13.0

Parolees 4

45.0

38.0

1.0

1.0

15.0

Persons in Jail 5

49.4

33.6

1.4

1.0

14.6

Persons in Prison (sentenced)6

30.6

32.8

—

—

23.2

Comparison Population

Arrestees 3

1

Does not include individuals of Hispanic or Latinx ethnicity. 2 US Census Bureau, 2019 American Community Survey (Ruggles et al., 2021).

3

Uniform Crime Report, 2019 (US DOJ, FBI). 4 Probation and Parole in the United States, 2019 (Oudekerk & Kaeble, 2021).

5

Jail Inmates in 2019, (Zeng & Minton, 2021). 6 Prisoners in 2019, (Carson, 2020)

When examining graduation rates by race and ethnicity among adults, there appears to be a high rate of variability across groups and court types. Among all adult treatment courts, the reported graduation rate 14

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for participants identified as Caucasian/White was 61.3%, whereas the rate for those identified as Black/ African American was 57.3%. Looking more closely at the court specific graduation rates, a similar trend is observed. For example, the overall graduation rate for ADCs reporting race/ethnicity was 58.2%. and those participants identified as Caucasian/White within ADCs had a graduation rate of 58.8%. However, Black/ African American participants had a rate of 54.8%. Within FTCs, there is even a greater difference with Caucasian/White participants reported graduation rate at 51.9% and Black/African Americans at 33.3%.

The overall graduation rate among MHCs providing data on race/ethnicity was 54.7%, while Black/African American participants had a rate of 48.0% and Hispanic/Latinx participants had a rate of 44.1%. Overall, the graduation rate, regardless of court type, was much lower for Black/African American and Hispanic/Latinx participants.

Looking at race and ethnicity among juvenile treatment court participants, findings reveal both over and under-representation when compared to other criminal justice populations (see Table 5). For example, participants identified as Black/African American made up 26.6% of juvenile treatment court participants in 2019 but only 21.4% of drug offense arrestees. However, this same group constituted 33.5% of juveniles on probation. Caucasian/White participants were both under-represented when compared to drug offense arrestees and over-represented when compared to the juvenile probation population. Participants identified as American Indian/Alaskan Native or Asian/Pacific Islander were over-represented in juvenile treatment courts compared to all other criminal justice populations.

Table 5: Comparison of JTC Participants with Other Criminal Justice Populations by Race/Ethnicity

Comparison Population

Caucasian/ White1

Black/ African American1

American Indian/ Alaskan Native1

Asian/ Pacific Islander1

Hispanic/ Latinx

Juvenile Treatment Courts

60.8

26.6

4.0

3.5

28.1

US Population (2019) 2

49.9

13.7

0.8

5.6

25.4

Any offense

62.5

33.9

2.2

1.4

23.6

Drug Offense

74.8

21.4

2.2

1.6

30.1

Probationers 4

44.4

33.5

1.7

1.2

19.2

Confined/Placement 5

33.3

40.6

2.0

1.0

2.6

Arrestees 3

1

Racial categories do not include individuals of Hispanic or Latinx ethnicity. 2 Kids Count Data Center, https://datacenter.kidscount.org.

3

Uniform Crime Report, 2019 (US DOJ, FBI). 4 Sickmund et al. (2021) https://www.ojjdp.gov/ojstatbb/ezajcs/.

5

Sickmund et al. (2021) https://www.ojjdp.gov/ojstatbb/ezacjrp/.

The trends in graduation rates among juvenile treatment courts by race and ethnicity show outcomes both similar and divergent from adult treatment courts. Juvenile drug treatment court participants identified as Caucasian/White had a graduation rate of 60.6% but Black/African Americans’ graduation rate was only 53.9%. Conversely, among juvenile mental health court participants, Black/African Americans had a higher graduation rate (73.0%) than their Caucasian/White counterparts (70.7%).

While some progress has been made in increasing equity and inclusion in treatment courts, these data suggest that there is still work to be done. Treatment court programs should closely examine their participant data to identify if disparities exist within their program. If there is evidence of disparities, programs should develop a plan to ensure that all persons regardless of race/ethnicity, gender, sexual orientation, religion, disability, etc. are able to access and have the opportunity to successfully complete the program. One area that should be examined based on the research presented is eligibility and exclusion criteria. Do the current ISSUES TO CONSIDER

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criteria automatically exclude certain groups? These “…criteria may be limiting the reach of the program…”

(Sheeran & Heideman, 2021). As noted by Marlowe (2013), programs should also review their screening and assessment tools to ensure the tools are neither culturally nor racially biased. Moreover, researchers argue that the integration of culturally competent treatment and interventions are crucial to ensuring all participants are successful (Gallagher, 2013; McKean & Warren-Gordon 2011; Sheeran & Heideman, 2021).

This was evident in Ho et al.’s (2018) examination of the relationship between treatment court practices and racial disparities in graduation. The results revealed that “…the provision of family/domestic counseling…” as a practice significantly decreased the racial gap in graduation. The authors argue that “…the focus on family/domestic counseling on the family and others who are most important to Black participants may be particularly effective” (2018, p. 28).

BJA strongly encourages applicants to include a plan for collecting and examining access and retention data to ensure disparities do not exist for race, color, religion, national origin, sexual orientation, gender, gender identity, or disability in admission protocols or elsewhere in the treatment court program.

Programs are encouraged to use AU’s RED tool and/or NADCP’s Equity and Inclusion Toolkit to identify areas of inequity.

The Rise in Stimulant Use: The Role of Treatment Courts in Addressing this Issue For the past several years, the opioid epidemic has dominated the proverbial landscape from media coverage, discourse regarding substance use disorders, to the enactment of state and federal policies focused on reducing substance use among adults and youth. An unprecedented number of resources have been devoted to addressing this trend. The devastating toll this epidemic has had on individuals, families, and communities cannot be overstated. However, another epidemic of sorts has co-existed, but received much less attention overall, involving stimulants (e.g., methamphetamine, cocaine/crack cocaine, and prescription stimulants).

According to SAMHSA (2020) nearly 2 million people (ages 12+) had used methamphetamine in the past year, and 1 million met the DSM-V criteria for a methamphetamine use disorder (a significant increase).

Additionally, the National Institute on Drug Abuse (2019, p. 5) reported that “Nationwide, overdose deaths from the category of drugs that includes methamphetamine increased by 7.5 times between 2007 and 2017, about 15 percent of all drug overdose deaths involved the methamphetamine category in 2017, and 50 percent of those deaths also involved an opioid.” Interestingly, Artigiani et al. (2018) reported that methamphetamine use and overdose death figures vary significantly by region in the United States. More specifically, the Midwest and West regions of the U.S. had the highest rates. Jones et al. (2019) found similar significant regional differences when examining methamphetamine use among individuals using heroin entering treatment. Odds of treatment admissions reporting methamphetamine use were more than 47 times higher in the West and almost 8 times higher in the Midwest (as compared to the Northeast).

When examining rates of substance use by racial category, notable differences are revealed. The Center for Behavioral Health Statistics and Quality (2021) examined the 2019 National Survey of Drug Use and Health data. Table 6 summarizes these findings and reveals that American Indian/Alaskan Native and individuals identifying as two or more races, consistently report the highest past year use of various substances as compared to other groups. Additionally, these same two groups (i.e., American Indian/Alaskan Native and individuals identifying as two or more races) have the highest percentages of individuals with illicit drug, alcohol use, and substance use disorders in the past year. These findings correspond with the findings of Meinhofer et al.’s (2020) study of Adoption and Foster Care Analysis and Reporting System (AFCARS) from 2008-2017. The results revealed that home removals due to parental drug use increased in the general population and across all racial/ethnic groups during this time. However, the increase was most pronounced among Native American/Alaskan Native children.

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Table 6: Select Substance Use & Treatment Access Indicators from 2019 National Survey of Drug Use and Health (SAMHSA)

White

Black/ African American

American Indian/ Alaskan Native

Native Hawaiian/ Other Pacific Islander

Two or more races

Methamphetamine use

0.7

0.2

2.4

1.1

1.1

Misuse of prescription pain relievers

4.2

3.6

5.2

4.3

5.8

Fentanyl product misuse

0.1

—

—

—

0.2

Illicit drug use disorder

2.9

3.4

4.8

3.0

5.0

Alcohol use disorder

5.8

4.8

8.3

4.9

6.6

Substance use disorder

7.8

7.1

11.2

6.8

9.9

…in the past year among individuals 12 and older

In response to this alarming trend, researchers have begun more closely examining rates of stimulant use within the U.S. and worldwide. Farrell et al. (2019) found that cocaine and amphetamines are widely used worldwide, available supplies of these substances are increasing, and the use of these substances creates serious challenges for public health officials. High-income North American countries had the highest prevalence rates for both cocaine dependence and amphetamine dependence. Jones et al. (2019) examined rates of methamphetamine use among individuals seeking substance use treatment for heroin use between 2008-2017. Alarmingly, they found that “Methamphetamine use among heroin treatment admissions in the United States increased from one in 50 primary heroin treatment admissions to one in 8 admissions in 2017” (p. 347).

Based on these data, we examined the most often reported substances used by treatment court participants by court type (per PCP survey respondents). Of interest was whether there were differences in the types of substances used by court type and the prevalence of stimulant use among participants. Table 7 provides a summary of these data. What is noteworthy is the high percentage of respondents across several court types reporting the use of stimulants among treatment court participants. More specifically, 100% of FTC respondents, 93.5% of ADC respondents, and 83.3% of MHC respondents indicated participants were using stimulants. Within these court types, stimulants were reported by the highest percentage of respondents as compared with other substances (e.g., heroin/opioids). In VTCs, stimulants were reported by 81.5% of respondents, which was the second highest percentage behind alcohol. This trend of high stimulant use is observed among adult treatment court programs, but not within juvenile programs. Stimulants were the third highest substance of use reported by PCP respondents behind marijuana and alcohol within juvenile drug courts and juvenile mental health courts.

ISSUES TO CONSIDER

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Table 7: % of States/Territories Reporting Specific Drugs of Use by Treatment Court Participants by Court Type (2019)

Alcohol

Cocaine/ Crack Cocaine

Heroin/ opioids

Marijuana

Methamphetamine

Total Stimulants1

Adult Drug Court (n=52)

63.0

19.6

80.4

58.7

67.4

93.5

DUI/DWI Court (n=36)

100.0

9.7

75.1

77.4

41.9

58.1

Family Treatment Court (n=38)

54.5

12.1

81.8

57.6

75.8

100.0

Mental Health Court (n=39)

80.6

12.9

54.8

71.0

61.3

83.3

Veterans Treatment Court (n=44)

91.2

20.6

38.2

73.5

55.9

81.5

Juvenile Drug Court (n=39)

80.0

6.7

33.4

93.3

56.7

70.1

Juvenile Mental Health Court (n=14)

70.0

10.0

10.0 (heroin only)

90.0

30.0

50.0

Treatment Court Type

Adult

Juvenile

“Total stimulants” category includes: cocaine/crack cocaine, methamphetamine, & prescription stimulants (not presented in table).

Conversations and action steps designed to address substance use within the U.S. must consider what works with addressing opioid use disorders, stimulant use disorders, and poly drug use. Farrell et al. (2019) note that “The current standard of care for stimulant dependence is primarily psychosocial interventions combined with case management. However, the majority of evidence does not support their effectiveness when compared to treatment-as-usual” (p. 1658). Also noteworthy is that there are no medications for addiction treatment (MAT) available to treat stimulant dependence, manage withdrawal, or prevent returns to use. However, MAT has been found to effectively treat individuals with opioid and alcohol use disorders.

Research findings are consistent in terms of what works in addressing the needs of individuals with stimulant use disorders. More specifically, programming that involves the following elements is most effective: evidence-based clinical treatment (i.e., Matrix Model, Motivational Interviewing, cognitive behavioral therapy), contingency management, and community reinforcement. Research has found that treatment court programs incorporating these elements, operating with fidelity to the model, and in accordance with identified best practice standards, achieve the best outcomes (Farrell et al., 2019; Jones et al., 2019; SAMHSA 2020;). The few studies conducted to date that explicitly examined treatment court programs’ effectiveness with participants using methamphetamine revealed positive results (Huddleston, C.W., 2005; Lanier & DeVall, 2017; Marinelli-Casey et al., 2008; SAMHSA, 2016).

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In summary, it would behoove treatment court team members to engage in dialogue around how their programs are addressing the needs of individuals. Given the national data presented above, treatment courts should examine drug of use trends by race/ethnicity and gender. Specific attention should be paid to what treatment modalities are available to participants who may be using (or have used) both opioids and stimulants. The research is unequivocal regarding “what works” to address stimulant use disorders, so it is imperative that programs provide participants with access to these services. In addition, additional research on the effectiveness of treatment court programs with individuals reporting stimulant, opioid, and poly drug use disorders is needed.

ISSUES TO CONSIDER

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References Artigiani E.H., McCandlish, D., & Wish, E.D. (2018). Methamphetamine: A regional drug crisis. National Drug Early Warning System. https://cesar.umd.edu/sites/cesar.umd.edu/files/pubs/ndews-scsmethamphetamine-report-september-2018-final.pdf Barnes, J. C., Ventura Miller, H., & Miller, J. M. (2009). Identifying leading characteristics associated with juvenile drug court admission and success: A research note. Youth Violence and Juvenile Justice, 7(4), 350-360. http://dx.doi.org/10.1177/1541204009334630 Bureau of Justice Assistance and National Institute of Justice. (2012). Seven program design features: Adult drug court principles, research, and practice (pp. 1–20). https://www.ojp.gov/pdffiles1/nij/248701. pdf Center for Behavioral Health Statistics and Quality. (2021). Racial/ethnic differences in substance use, substance use disorders, and substance use treatment utilization among people aged 12 or older (2015-2019). Substance Abuse and Mental Health Services Administration. https://www.samhsa. gov/data/ Center for Court Innovation (2013). Developing a statewide drug court data tracking system: The why, what, and how of it. https://www.courtinnovation.org/sites/default/files/documents/ drugcourtdatasystem.pdf Carson, E. A. (2020). Prisoners in 2019. Bureau of Justice Statistics. https://bjs.ojp.gov/content/pub/pdf/ p19.pdf Dannerbeck, A., Harris, G., Sundet, P., & Lloyd, K. (2006) Understanding and responding to racial differences in drug court outcomes. Journal of Ethnicity in Substance Abuse, 5(2), 1-22. https://doi.org/10.1300/ J233v05n02_01 DeVall, K. E., & Lanier, C. L. (2012). Successful completion: An examination of factors influencing drug court completion for white and non-white male participants. Substance Use & Misuse, 47(10), 1106-1116. http://dx.doi.org/10.3109/10826084.2012.680171 Farrell, M. Martin, N.K., Stockings, E, Borquez, A., Cepeda, J.A., Degenhardt, L. Ali, R., Tran, L. Rehm, J., Torrens, M., Shoptaw, S. & McKetin, R. (2019). Responding to global stimulant use: Challenges and opportunities. The Lancet, 394(10209), 1652-1667. https://doi.org/10.1016/S0140-6736(19)32230-5 Gallagher, J. R. (2013) Drug court graduation rates: Implications for policy advocacy and future research.

Alcoholism Treatment Quarterly, 31(2), 241-253. https://doi.org/10.1080/07347324.2013.772019 Ho, T., Carey, S. M., & Malsch, A. M. (2018). Racial and gender disparities in treatment courts: Do they exist and is there anything we can do to change them? Journal for Advancing Justice, 1(1), 5-34. https:// advancejustice.org/wp-content/uploads/2018/06/AJ-Journal.pdf Huddleston, C. W. (2005). Drug courts: An effective strategy for communities facing methamphetamine.

National Drug Court Institute. https://www.ojp.gov/pdffiles1/bja/209549.pdf Jones, C. M., Underwood, N., & Compton, W. M. (2019). Increases in methamphetamine use among heroin treatment admissions in the United States, 2008–17. Addiction, 115(2), 347-353. https://doi. org/10.1111/add.14812 Lanier, C., & DeVall, K. E. (2017). How’d you do it? Applying structural ritualization theory to drug treatment courts. Journal of Drug Issues, 47(2), 289–308. https://doi.org/10.1177/0022042616687119

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Mackin, J. R., Lucas, L. M., Lambarth, C. H., Herrera, T. A., Waller, M. S., Carey, S., & Finigan, M. W. (2010). Baltimore County juvenile drug court outcome and cost evaluation. Portland, OR: NPC Research. https://mdcourts.gov/sites/default/files/import/opsc/dtc/pdfs/evaluationsreports/ baltimorecountyjuveniledcoutcome-costreport.pdf Marinelli-Casey, P., Gonzales, R., Hillhouse, M., Ang, A., Zweben, J., Cohen, J., Hora, P.F., & Rawson, R.A. (2008).

Drug court treatment for methamphetamine dependence: Treatment response and posttreatment outcomes. Journal of Substance Abuse, 34(2), 242-248. https://doi.org/10.1016/j.jsat.2007.04.005 McKean, J., & Warren-Gordon, K. (2011) Racial differences in graduation rates from adult drug treatment courts. Journal of Ethnicity in Criminal Justice, 9(1), 41-55. https://doi.org/10.1080/15377938.2011.

535469 Meinhofer, A., Onuoha, E., Anglero-Diaz, Y., & Keyes, K.M. (2020). Parental drug use and racial and ethnic disproportionality in the U.S. foster care system. Children and Youth Services Review, 118, 1-4. https://doi.org/10.1016/j.childyouth.2020.105336 National Association of Drug Court Professionals. (2018a). Adult Drug Court Best Practice Standards Volume I. https://www.nadcp.org/wp-content/uploads/2018/12/Adult-Drug-Court-Best-PracticeStandards-Volume-I-Text-Revision-December-2018-1.pdf National Association of Drug Court Professionals. (2018b). Adult Drug Court Best Practice Standards Volume II. https://www.nadcp.org/wp-content/uploads/2018/12/Adult-Drug-Court-Best-PracticeStandards-Volume-2-Text-Revision-December-2018-1.pdf National Institute on Drug Abuse. (2019). Methamphetamine research report (pp. 1–22). U.S. Department of Health and Human Services. Retrieved from https://nida.nih.gov/download/37620/ methamphetamine-research-report.pdf?v=59d70e192be11090787a4dab7e8cd390 National Institute of Justice. (2012, November 4). NIJ’s multisite adult drug court evaluation. NIJ: National Institute of Justice. https://nij.ojp.gov/topics/articles/nijs-multisite-adult-drug-court-evaluation Nicosia, N., MacDonald, J. M., & Arkes, J. (2013). Disparities in criminal court referrals to drug treatment and prison for minority men. American Journal of Public Health, 103(6), e77-e84. https://dx.doi. org/10.2105%2FAJPH.2013.301222Probation and Parole in the United States, 2019 (Oudekerk & Kaeble, 2021) Oudekerk, S. & Kaeble, D. (2021). Probation and parole in the United States, 2019. Bureau of Justice Statistics. https://bjs.ojp.gov/sites/g/files/xyckuh236/files/media/document/ppus19.pdf Rempel, M. (2010). Action research: Using information to improve your drug court. Center for Court Innovation. https://www.courtinnovation.org/sites/default/files/Action%20Research.pdf Ronan, S. M., Collins, P. A., & Rosky, J. W. (2009). The effectiveness of Idaho DUI and misdemeanor/DUI courts: Outcome evaluation. Journal of Offender Rehabilitation, 48(2), 154–166. https://doi. org/10.1080/10509670802641030 Ruggles, S., Flood, S., Foster, S., Goeken, R.,Pacas, J., Schouweiler, M., & Sobek, M. (2021) IPUMS USA (Version 11.0) [Data set]. IPUMS. https://doi.org/10.18128/D010.V11.0 Sacco, L.N. (2018). Federal support for drug courts: In brief. Congressional Research Service. https://sgp. fas.org/crs/misc/R44467.pdf Sechrest, D. K., & Shicor, D. (2001). Determinants of graduation from a day treatment drug court in California: A preliminarystudy. Journal ofDrug Issues, 31(1), 129–147. https://doi.org/10.1177/002204260103100108

REFERENCES

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Shannon, L. M., Jones, A. J., Nash, S., Newell, J., & Payne, C. M. (2018). Examining racial disparities in program completion and post-program recidivism rates: Comparing Caucasian and non-Caucasian treatment court participants. Journal for Advancing Justice, 1, 63-88. https://advancejustice.org/ wp-content/uploads/2018/06/AJ-Journal.pdf Sheeran, A. M., & Heideman, A. J. (2021). The effects of race and ethnicity on admission, graduation, and recidivism in the Milwaukee County adult drug treatment court. Social Sciences, 10(7), 261-278. https://doi.org/10.3390/socsci10070261 Sickmund, M., Sladky, A., and Kang, W. (2021). Easy access to juvenile court statistics: 1985-2019. [Data set]. https://www.ojjdp.gov/ojstatbb/ezajcs/ Sickmund, M., Sladky, T.J., Puzzanchera, C., and Kang, W. (2021). Easy access to the census of juveniles in residential placement. [Data set]. https://www.ojjdp.gov/ojstatbb/ezacjrp/ Stein, D. M., Deberard, S., & Homan, K. (2013). Predicting success and failure in juvenile drug treatment court: A meta-analytic review. Journal of substance abuse treatment, 44(2), 159-168. https://doi. org/10.1016/j.jsat.2012.07.002 Stein, D. M., Homan, K. J., & DeBerard, S. (2015). The effectiveness of juvenile treatment drug courts: A meta-analytic review of literature. Journal of Child & Adolescent Substance Abuse, 24(2), 80-93. https://doi.org/10.1080/1067828X.2013.764371 Substance Abuse & Mental Health Services Administration. (n.d.) SAMHSA budget archives. https://www. samhsa.gov/about-us/budget/archive Substance Abuse and Mental Health Services Administration. (2016). Children affected by methamphetamine program: Implementation progress and performance measurement report. https://ncsacw.samhsa. gov/files/CAM_Final_Report_508.pdf Substance Abuse and Mental Health Services Administration (2020). Treatment of stimulant use disorders. https://store.samhsa.gov/sites/default/files/SAMHSA_Digital_Download/PEP20-06-01001_508.pdf Sullivan, C. J., Blair, L., Latessa, E., & Sullivan, C. C. (2016). Juvenile drug courts and recidivism: Results from a multisite outcome study. Justice Quarterly, 33(2), 291–318. https://doi.org/10.1080/07418825.20 14.908937 Tanner-Smith, E. E., Lipsey, M. W., & Wilson, D. B. (2016). Juvenile drug court effects on recidivism and drug use: a systematic review and meta-analysis. Journal of Experimental Criminology, 12(4), 477– 513. https://doi.org/10.1007/s11292-016-9274-y U.S. Department of Justice. (2020). Crime in the United States, 2019. https://ucr.fbi.gov/crime-in-theu.s/2019/crime-in-the-u.s.-2019/home.

U.S. General Services Administration. (n.d.) Enacted federal budgets. https://www.gsa.gov/reference/ reports/budget-performance/enacted-federal-budgets.

Zeng, Z. & Minton, T.D. (2021). Jail inmates in 2019. Bureau of Justice Statistics. https://bjs.ojp.gov/content/ pub/pdf/ji19.pdf

22

PAINTING THE CURRENT PICTURE

Appendices See "Treatment Courts by Type and State/Territory (2019)" on page 24

APPENDICES

23

12

49

86

30

1

5

1

56

51

1

6

35

69

44

10

11

71

32

6

24

32

75

38

Arkansas

California

Colorado

Connecticut

Delaware

District of Columbia

Florida

Georgia

Guam

Hawaii

Idaho

Illinois

Indiana

Iowa

Kansas

Kentucky

Louisiana

Maine

Maryland

Massachusetts

Michigan

Minnesota

Drug

Arizona

DWI/DUI

5

14

31 17

75

2

32

3

2

3

3

6

1

1

1

3

Co-occurring Disorder

3

8

3

4

6

1

24

4

2

15

3

8

1

5

3

7

12

12

2

1

1

21

13

11

38

2

2

4

31

8

7

1

1

4

4

8

29

11

1

35

31

1

3

7

50

2

4

3

1

1

2

9

12

1

1

18

Re-entry

14

14

3

2

Opioid Intervention

3

5

3

6

1

2

1

1

3

1

11

10

7

1

8

27

6

7

2

4

7

1

1

27

20

6

4

1

19

31

3

7

48

16

4

1

28 1

Other

1

Hybrid Drug/ DUI1

Alaska

Family 11

Mental Health

13

Tribal Healing to Wellness3

26

Veterans

1

1

12

2

10

2

6

1

4

4

1

8

20

3

27

16

6

11

Drug

55

Juvenile

6

1

2

5

1

3

2

11

1

1

Mental Health

Alabama

State

Adult

Appendix A: Treatment Courts by Type and State/Territory (2019)

71

196

48

50

13

77

79

19

37

104

122

69

16

6

163

157

2

17

1

76

303

99

43

20

121

State/Territory Total Other

Co-occurring Disorder

3

10

1

7

4

5

6

0

27

62

46

65

27

3

38

28

29

Tennessee

Texas

Utah

Vermont

Virginia

Washington

West Virginia 1

7

2

1

2

6

3

4

1

3

21

1

1

490

15

13

1

13

20

8

2

10

22

24

87

29

12

1

2

1

9

7

2

32

10

3

5

1

25

5

3

257

351

THWC totals are as of December 31, 2020. 4 Totals for the THWCs were available, but not provided for the other treatment court types.

1,696

3

Total

Hybrid drug/DUI courts are a subset of ADCs and not count separately in the total line tallies. 2 NR = Not reported.

1

335

5

18

7

16

14

2

1

5

1

2

480

10

South Dakota

1

15

22

109

31

South Carolina

10

7

4

26

1

1

Rhode Island

14

2

5

4

1

10

Puerto Rico

14

56

Pennsylvania

2

2

34

Wyoming

30

Oregon

2

34

4

35

6

50

Oklahoma

6

4

1

1

Wisconsin

113

Ohio

7

30

305

4

18

11

7

5

24

6

13

1

5

5

7

19

6

3

7

5

46

4

2

1

3,856

21

64

53

101

74

5

69

194

75

21

59

4

10

129

65

95

260

1

17

59

215

1

7

8

22

1

6

5

N. Mariana Islands

14

2

7

20

2

33

North Dakota

7

96

5

2

2

42

29

4

11

6

2

2

North Carolina

4

9

4

2

4

137

96

10

10

3

2

9

4

New York

10

New Hampshire

8

4

5

15

40

73

26

Nevada

1

2

15

11

32

20

Nebraska

6

32

1

New Mexico

14

Montana

23

3

NR2

80

Missouri

1

New Jersey

25

Mississippi