Criminal recidivism in three models of mandatory drug treatment

Journal of Substance Abuse Tre

Regular article

Criminal recidivism in three models of mandatory drug treatment

Douglas Young, (M.S.)a,*, Reginald Fluellen, (Ph.D.)b, Steven Belenko, (Ph.D.)c

aBureau of Governmental Research, University of Maryland, College Park, 4511 Knox Rd, Suite 301, College Park, MD 20740, USAbNational Black Leadership Commission on AIDS, 105 East 22nd Street, Suite 711, New York, NY 10010, USA

cTreatment Research Institute at the University of Pennsylvania, 600 Public Ledger Building, 150 South Independence Mall West,

Philadelphia, PA 19106-3475, USA

Received 17 November 2003; received in revised form 26 May 2004; accepted 20 August 2005

Abstract

Although research has generally been supportive of compulsory treatment programs for drug abusers, findings remain mixed, and

few studies have assessed the impacts of different coercive program elements. This study compared criminal recidivism outcomes of

350 clients mandated to the same long-term residential treatment facilities from three different legal sources. On several measures of

recidivism, including long-term re-arrest rates that controlled for time at risk, clients mandated from two highly structured programs were

found to recidivate at less than half the rate of comparison group clients. This group effect was upheld in multivariate models that

controlled for pre-treatment differences and other factors related to recidivism. Combined with results of a previous retention study

involving these clients, the findings provide support for the use of structured protocols for informing clients in mandatory programs about

legal contingencies of participation and enforcing contingencies through frequent contact between legal agents and treatment staff. D 2004

Elsevier Inc. All rights reserved.

Keywords: Mandatory treatment; Recidivism; Coercion; Courts

1. Introduction

Severe budgetary constrictions caused by recent eco-

nomic trends have left state and local policy makers

searching for strategies to cut and contain costs. The sud-

den budget-mandated release of 567 prisoners in Kentucky

in December 2002 dramatically signified a growing con-

sensus that sole reliance on incarceration, particularly for

nonviolent crimes, is prohibitively expensive public policy.

These budgetary trends will likely give new impetus to in-

terest in cheaper, community-based treatment alternatives

for the vast numbers of substance-abusing offenders in-

volved in the criminal justice system (Arrestee Drug Abuse

Monitoring Program [ADAM], 2000; Bureau of Justice

Statistics, 2001; Maguire & Pastore, 1999). A number of

existing models and programs aim to provide this function

0740-5472/04/$ – see front matter D 2004 Elsevier Inc. All rights reserved.

doi:10.1016/j.jsat.2004.08.007

* Corresponding author. Tel.: +1 301 403 8334; fax: +1 301 403 4404.

E-mail address: [email protected] (D. Young).

at different points in the criminal justice system. In opera-

tion since the 1970s, Treatment Alternatives to Street Crime

(TASC) programs have the most extensive history in this

role (Anglin, Longshore, & Turner, 1999). TASC programs

operate as a bridge between the justice and treatment

systems, providing case management and brokering serv-

ices. TASC may work at the bfront endQ of the system with

offenders under court or probation supervision, or with

parolees upon release from prison. Local TASC programs

may also operate within the larger context of two other

justice-based treatment models spawned largely by federal

funding, Breaking the Cycle (BTC), and drug treatment

courts. BTC programs target all substance-abusing offenders

entering a particular legal jurisdiction, emphasizing assess-

ment, treatment matching, drug testing, and graduated

sanctions for non-compliance with supervision orders

(Harrell, Hirst, & Mitchell, 2000). Drug courts, which

now number over 1,000 nationally, typically target first- or

second-time offenders charged with relatively minor crimes

who have drug problems. Facilitated by court-based case

atment 27 (2004) 313–323

D. Young et al. / Journal of Substance Abuse Treatment 27 (2004) 313–323314

management and carefully calibrated sanctions and incen-

tives, drug court participants must complete a regimen of

community-based treatment before charges are dropped or

reduced (Belenko, 1998).

Although questions have been raised about whether these

programs represent true alternatives to incarceration—drug

courts in particular may target offenders who would not be

going to jail or prison (Belenko, 2000)—they remain attrac-

tive to policy makers for other reasons. They provide an

efficient means of ensuring access to treatment for many

high-risk, high-need individuals who would not otherwise

enter treatment (Hammett, Gaiter, & Crawford, 1998;

Wenzel, Longshore, Turner, & Ridgely, 2001). Further, there

is a widespread, research-based consensus that programs that

use the coercive powers of the justice system retain clients

for the same or longer periods than clients who are not

legally mandated, leading in turn to improved employment

and criminal recidivism outcomes (Anglin, 1988; Brecht,

Anglin & Wang, 1993; Collins & Allison, 1983; Hiller,

Knight, Broome, & Simpson, 1998; Marlowe, 2001). While

not directly disputed, this conclusion has been faulted in

recent years as oversimplified, with reviewers pointing to

the imprecise terminology, poor methodology, and uneven

findings in much of the earlier research on coerced treatment

(Farabee, Prendergast, & Anglin, 1998; Marlowe, Merikle,

Kirby, Festinger, & McLellan, 2001; Wild, 1999; Young,

2002). Some of the same criticism is echoed in reviews of

the many drug court evaluations that have been spawned

by federal requirements for program funding (Gottfredson,

Najaka, & Kearley, 2003; Listwan, Sundt, Holsinger, &

Latessa, 2003). In practice, the structural and operational

characteristics of compulsory treatment models vary greatly

from one program to another (Anglin et al., 1999; Taxman &

Bouffard, 2002; Young & Belenko, 2002). Client targeting

and screening, treatment dosage and approach, case manage-

ment, monitoring, and sanctioning practices are just some

of the elements that differ among programs and are likely to

affect outcomes.

Policy makers looking for effective treatment alternatives

to incarceration need better information about the impacts of

different program mechanisms and models. The research re-

ported here is part of a small trend of recent studies that have

sought to assess the effects of specific coercive practices

and policies. It specifically builds on prior research assessing

mandated clientsT perceptions of legal pressure (PLP) in threedifferent compulsory treatment programs and the impacts of

PLP and other client factors on retention in residential treat-

ment (Young, 2002; Young & Belenko, 2002). The present

study extends the comparative analysis of the three programs

from retention outcomes to the bbottom lineQ gauge used by

policymakers—criminal recidivism.

1.1. Review of the literature

Research on compulsory treatment has evolved sub-

stantially from early studies that simply compared outcomes

of legally-involved clients and those entering treatment

voluntarily (Salmon & Salmon, 1983; Pompi & Resnick,

1987; Steer, 1983). This initial research often blurred

important distinctions—legal status, referral source, and

treatment mandate—and ignored the fact that bvoluntaryQclients are rarely self-referred, but enter treatment under other

pressures from family, peers, and employers (Marlowe et al.,

2001). Building on an ordinal index created by Anglin and

colleagues (Anglin, Brecht, & Maddahian, 1989; Brecht

et al., 1993), subsequent studies have assessed outcomes of

clients under low, medium, and high coercion, as determined

by legal status, monitoring through drug testing, and the

client reporting a legal reason for entering treatment (Hiller

et al., 1998; Hser, Maglione, Polinsky, & Anglin, 1998).

Exemplifying recent trends that extend the field, a study

by Knight , Hiller, Broome, and Simpson (2000) employs

this continuous index of legal coercion within a larger con-

text that includes assessments of engagement and motiva-

tion for treatment.

Even more detailed studies of the bblack boxQ of coer-cive program practices are evident in recent research on

drug courts, TASC programs, and other treatment diver-

sion models. These studies represent empirical tests of

themes found in theoretical and review papers supporting

the use of client contracts, swift and timely responses to

violations, and structured sanction menus (Marlowe et al.,

1996; Taxman, Soule, & Gelb, 1999; Taxman, 2000), and

the application of principles of behavioral psychology

(Marlowe & Kirby, 1999) and contingency management

(Higgins & Petry, 1999). A controlled study of a pretrial

diversion program in Washington, DC, found that grad-

uated sanctions, with or without ancillary drug treatment,

had favorable impacts on offendersT drug use (Harrell &

Cavanaugh, 1995; Harrell, 1998). The case management

model utilized by TASC—assessment, close monitoring of

treatment progress, drug testing, and reporting compliance

to legal agents—has generally been supported in evalua-

tions (Rhodes & Gross, 1997; Van Stelle, Mauser, &

Moberg, 1994), however implementation fidelity can vary

greatly across sites, moderating impacts (Anglin et al.,

1999). Applied in a broader scope in the federal Breaking

the Cycle initiatives, these same practices have received

support in an evaluation of BTC demonstrations (Harrell

et al., 2000).

Recent studies have similarly begun to test some of

the assumptions about effective coercive practices inher-

ent in the many prescriptive documents on drug courts

(e.g., NADCP, 1997). In a rare controlled evaluation of a

drug court serving offenders with serious drug histories,

Gottfredson and colleagues (2003) found that drug court

participants had lower rearrest rates than the control group

at the 2-year follow up. Results suggested this effect was

at least partially due to the courtTs success in imposing a

threat of future sanctions, which worked regardless of the

participantsT drug history (contrary to hypotheses that sanc-

tion threats would be ineffective with heavy users). The

D. Young et al. / Journal of Substance Abuse Treatment 27 (2004) 313–323 315

study findings also underscored the importance of treatment

in achieving recidivism reduction effects.

In a less rigorous design, researchers found reduced

recidivism outcomes for participants of the Douglas County

Drug Court (Omaha, NE) relative to non-equivalent com-

parison groups, and attributed at least some of this success

to the intensive judicial supervision and monitoring em-

ployed by court staff (Spohn, Piper, Martin, & Frenzel,

2001). Marlowe and colleagues (2003) have assessed the

impacts of bthe single-most defining component of a drug

court, namely, ongoing judicial status hearings with of-

fender Q (p. 145) using a controlled design. Against expec-

tations, court participants randomly assigned to attend

bi-weekly status hearings did no better than those attending

status hearings on an bas neededQ basis on several measures,

including counseling attendance, drug testing results, and

self-reported drug use or criminal activity. Clients in the

bi-weekly condition did receive more sanctions, such as

increased case management or testing, but this difference

appeared to have no impact on recidivism outcomes. A

recent study of the drug court in Cincinnati similarly found

no effects for status review hearings on re-arrests or incar-

ceration for new offenses, although attendance in hearings

was associated with a reduction in arrests for drug-related

crimes (Listwan et al., 2003).

These studies represent the latest evolution of designs

examining the effects of objective coercive program ele-

ments. Another line of recent research has emphasized the

importance of the clientTs subjective experience of coercion.Wild, Newton-Taylor, and Alletto (1998) have used a variant

of the MacArthur Perceived Coercion Scale to test hypothe-

ses generated from self-determination theory, which asserts

that personal autonomy is undermined by structural and

psychological factors (legal or employer mandates, beliefs

about substance abuse severity and interpersonal pressures to

enter treatment) that promote perceived coercion. Marlowe

et al. (1996, 2001) developed the Survey of Treatment Entry

Pressures to assess clientsT reasons for entering treatment

and motivations for quitting drug use. Consistent with the

conclusions of recent literature reviews on compulsory treat-

ment (Farabee et al., 1998; Wild, Roberts, & Cooper, 2002),

findings from both of these lines of inquiry have underscored

the multi-dimensional nature of both legal and non-legal

pressures on treatment entry, and the relatively modest role

of formal legal circumstances (legal status, referrals, and

mandates) compared to client perceptions of coercion and

other motivational factors.

In two previous studies, we explored the impacts of

coercive program elements, and clientsT perceptions of legalpressure on retention in long-term residential therapeutic

communities (TC). As in the current research, both prior

studies centered around a highly structured and coercive

program developed and operated by the Kings County

District Attorney (Brooklyn, NY), the Drug Treatment

Alternative to Prison (DTAP) program. DTAP offers repeat,

non-violent felony defendants the option of treatment in a

TC in lieu of prosecution leading, in all probability, to a

prison term (Dynia & Sung, 2000; Hynes, 1999). In the

first study, DTAP participants were compared with clients

mandated to TC treatment by other, more conventional

criminal justice sources, including probation, parole and

the courts (Young, 2002). The second study was expanded

to include another experimental group composed of par-

ticipants of the local TASC program, as well as larger

DTAP and comparison group samples (Young & Belenko,

2002). In both studies, all participants were recruited upon

admission to the same TCs used by DTAP, so treatment

was held constant in the study designs. In the second larger

study, DTAP and TASC participants had higher rates of

retention than the comparison group at the two follow-up

points, 6 and 12 months post-admission; the DTAP differ-

ence held up in multivariate analyses that controlled for an

extensive set of background factors between the groups.

Both studies also used an exploratory measure, the Per-

ception of Legal Pressure questionnaire, which assessed in-

formation provided to clients about the treatment mandate

and consequences for failure, and their perceptions of moni-

toring by DTAP, TASC, or the supervision agent, and views

on enforcement and severity of the consequence for fail-

ing. In both studies, scores on the PLP were found to be

powerful, independent predictors of retention. With a few

notable exceptions (discussed in the next section), client

perceptions as measured by PLP items were consistent

with the practices and policies of the three programs, as

indicated in a survey of program documents and observa-

tions and in-depth interviews with treatment staff, super-

vision agents, and clients. Taken together, the findings

suggested that the high retention rates in the DTAP group

was partly attributable to the priority placed on enforcement

in this program, and particularly DTAPTs use of a specializedwarrant squad and other policies that increase the certainty

of incarceration upon failure in treatment. Another program

element evident in PLP results that helped contribute to

high retention in DTAP and TASC was the practice of pro-

viding frequent and consistent messages to clients about

the contingencies of treatment participation, and informa-

tion about how participation will be regularly monitored by

legal agents.

Criminal recidivism data were not available for either of

these studies. While we would anticipate favorable recidi-

vism outcomes for the DTAP and TASC groups based on

their retention performance, this remains a hypothesis until

tested with the kind of bhard dataQ demanded by policy-

makers. Further, the scope and quality of recidivism

measures are critical methodological factors in offender

treatment research. One significant improvement in recent

years is the use of multiple measures of recidivism, in

response to problems inherent in any single indicator (e.g.,

use of re-arrest is contrary to the notion of presumptive

innocence and may be influenced by police enforcement

practices, while reconviction and reincarceration are

affected by case processing policies and practices).


Some studies, however, still do not employ survival

methods or other means of assessing the time to a recidivism

event, or to account for censoring caused by follow-up

periods that are often limited to 1 year and rarely extend

beyond 2 years (e.g., Gottfredson, Najaka, & Kearley, 2003;

Marlowe et al., 2003; Spohn et al., 2001; Van Stelle et al.,

1994; Zanis et al., 2003). Researchers also have generally

failed to employ controls for time at risk in the community,

thus limiting analyses to the single first event during the

follow-up period, despite the fact that arrest chronicity—

frequent low level arrests—is comparatively common

among substance abusing offenders. Rearrest rates (number

of arrests/follow-up period) is one of the most succinct

recidivism measures for this population, but can be biased

if time-in-custody is not subtracted from the follow-up

duration. Without this adjustment for time-in-custody, re-

arrest rates are artificially deflated, making repeat offenders

look better on this outcome (Belenko, Schiff, Phillips, &

Winterfield, 1994). Each of these improvements—multiple

recidivism measures, statistical survival techniques, and

arrest rates controlling for time-in-custody—were employed

in the present recidivism research.

1.2. Description of the mandatory treatment models

To help interpret the recidivism findings we here describe

the three mandatory models studied in the current research,

incorporating some of the description from the previous

retention paper, as well as PLP findings from that research

(Young & Belenko, 2002). Typical of mandatory treatment

programs generally, the three included here show consid-

erable variation in their coercive program elements. The

coercive policies and practices of DTAP, TASC, and the

bmandated as usualQ programs were initially assessed

through document review and interviews, observations,

and informal discussions with clients, treatment staff, and

criminal justice agents supervising study participants.

Structured interviews aimed at gathering qualitative data

on clientsT experience of coercive practices were held with

45 study participants and 36 qualitative interviews were

held with criminal justice agents and treatment staff. The

formal policies and practices, as well as clientsT experiencesof them, are organized here around the information,

monitoring, enforcement; and severity areas addressed in

the PLP. Differences in the programsT client targeting and

screening policies are discussed, and a brief description of

the treatment sites is presented.

1.2.1. Client targeting and screening

Designed to address New YorkTs second-felony offender

law, the Brooklyn DTAP program targeted defendants

charged with drug sales who had a previous non-violent

felony conviction, and typically faced a prison term of

18 months to 3 years under the new charge. TASC worked

with a more diverse set of defendants which included many

repeat felony defendants but also some first-time felons and

defendants with violent charges or convictions. Typically,

TASC participants were on probation or parole from an

earlier offense and facing a new charge. TASC did not

exclusively target defendants charged with drug crimes, but

both TASC and DTAP participants had to show evidence of

a drug problem as indicated on the Addiction Severity

Index. The third study group included probationers and

parolees charged with new crimes or who were mandated in

lieu of a technical violation of the conditions of their release

(typically positive drug tests). This comparison group also

included a few offenders referred to treatment directly from

the courts (but not drug courts, which had not yet been

implemented in New York when data collection took place).

The criminal and drug histories of this group were more

varied, reflecting the discretion allowed judges and super-

vision agents in setting treatment mandates. Any group

differences in demographics, drug and criminal history, and

other client characteristics were assessed and controlled

statistically in analyses.

1.2.2. Information

DTAP and TASC had explicit, well-implemented pro-

tocols for informing the client and defense attorney about

the legal contingencies of participation, consequences of fail-

ure, and rules and expectations of the treatment program.

DTAP required participants to sign behavioral contracts that

were reviewed in open court. TASC had a similar policy to

require written agreements by participants; however, PLP

scores indicated that, unlike DTAP, TASC did not fully im-

plement or emphasize the policy. DTAP had formal agree-

ments with the TCs requiring that treatment staff reiterate

program rules and the consequences of failure to partici-

pants, and DTAP clients were significantly more likely than

TASC clients to report that staff provided information to

them about treatment mandates and legal contingencies. The

judges, probation, and parole officers who were involved in

the comparison group cases were more variable in providing

information to mandated clients, and the comparison group

had significantly lower scores than both the DTAP and TASC

groups on all seven of the information items on the PLP

measure. It was evident from staff interviews, observations,

and PLP scores that treatment staff were less likely to know

the contingencies or consequences faced by comparison

group clients.

1.2.3. Monitoring

The TCs closely followed formal agreements they had

with DTAP and TASC to provide monthly progress reports

and to inform the program when a client had left treatment

or was to be terminated. Although TASC put greater empha-

sis on monitoring, and compared to the other programs made

more frequent contact with participants, treatment staff, and

judges, this difference did not register on the clients as

indicated by PLP scores. DTAP clients were just as or more

likely than TASC clients to report that their treatment prog-

ress was being closely monitored and that infractions or


failure would be quickly detected. Significantly lower

scores on all five of the PLP monitoring items confirmed

that probation, parole, and court actors represented in the

third group were more variable and generally less active

in terms monitoring policies and capacities. Reports from

treatment staff about client progress or problems were re-

quested at the discretion of individual supervision agents or

judges, and treatment staff contrasted the ease of reaching

TASC and DTAP staff with that of trying to inform other

supervision agents about clients who were at risk of failing

or had left treatment.

1.2.4. Enforcement

As noted previously, DTAP emphasized enforcement

and the PLP results showed that program participants were

well aware of this. DTAP documents stressed the value of

the programTs specialized warrant enforcement squad—

former law enforcement officers who pursued clients

absconding from treatment—while TASC and the compari-

son group were left to rely on standard warrant squads

which routinely assigned violent absconders a greater pri-

ority than drug offenders. DTAP also differed from the

other mandatory models in enforcing a strict policy of

denying participants another chance if they failed once in

treatment. Although TASC case managers also delivered

stern threats to clients about the severe legal consequences

of failure, they would routinely refer clients to a second

(and sometimes a third) TC if they failed in the first pro-

gram but had made some progress and did not abscond.

Second chance referrals were also common in the com-

parison group, where judges, parole, and probation agents

would tolerate relapses and make multiple treatment re-

ferrals before enforcing any legal consequences for failure.

DTAP participants appeared to be aware of the programTsmore stringent referral policy based on responses to PLP

items that addressed this issue.

1.2.5. Severity

DTAP and TASC clients faced more severe sentences

than members of the comparison group, which included

more first-time felons and offenders facing violations of

parole and probation. PLP responses conformed to this

difference, with TASC and DTAP clients scoring higher

than the comparison group on most perceived severity

items. TASC clients scored higher than either group on one

item about the severity of the threatened consequence. Two

PLP items which assessed the respondentTs aversion to

serving time in prison showed no differences between the

three groups.

1.2.6. Therapeutic community treatment

The four TC treatment sites were all long-standing,

traditional therapeutic communities operated by large,

well-established non-profit agencies. TCs are highly struc-

tured residential treatment programs for substance abusers

that are designed to promote prosocial behavior and drug

abstinence. Communal living provides the context for con-

tinuous learning where individual change in conduct, atti-

tudes, and emotions is monitored and mutually reinforced in

the day-to-day routine. Clients must earn their way through

a series of treatment stages that bring additional status,

responsibility, and independence. In the four TC sites used

by DTAP and the other study models, clients typically spend

a year in residence at a relatively remote program campus

in upper New York State and then return to New York City

to complete a 4- to 12-month reentry phase. There, clients

participate in counseling and reside in a treatment facility,

while encouraged to obtain jobs, establish community con-

tacts, and save money for independent living upon departing

the residence.

2. Materials and methods

2.1. Sample

All DTAP and TASC clients entering the treatment pro-

grams during the data collection period were eligible to take

part in the study. Other legally-referred clients admitted

to the TCs took part in a brief screening interview. These

clients were eligible for the study if they confirmed that they

had been referred to treatment by a legal supervision agent

or the court, that someone in the justice system would be

informed if they failed in treatment, and that they had been

told or believed that there would be a legal consequence for

failure. Once confirmed as eligible, clients were recruited

using a standard informed consent protocol. Four of

154 DTAP clients and three of 203 comparison clients

recruited to take part in the study refused to participate.

Study participants were administered an intake interview as

soon as possible, typically within the first 2 weeks of their

admission to the TC (all were completed within a month

of admission). About 8% of the clients referred to the TCs

by DTAP, TASC, or other legal sources dropped out of

treatment within a few days of admission, before they could

be recruited for the study. Study participants thus included

150 DTAP clients, 124 TASC clients, and 76 clients in the

bmandated as usualQ comparison group.

As shown in Table 1, study participants were predom-

inantly male, African-American or Hispanic, and averaged

33 years old. They had extensive drug and criminal

histories, poor employment and educational histories, and

a relatively high incidence of medical and psychological

problems. On most background items the three groups were

similar. DTAP had proportionately more Hispanic clients

(62%) than TASC (50.8%) and the comparison group

(42.1%). While the groups were similar in regard to past

heroin use, TASC and comparison group clients reported

more extensive use of crack cocaine and, especially, pow-

dered cocaine. Predictably, DTAP clients averaged more

drug convictions and fewer arrests for violent offenses,

reflecting the programsT different admissions policies. These

Table 1

Sample description

Variable description

DTAP

(N = 130)

TASC

(N = 124)

Other

CJ referrals

(N = 76)

Demographics, SES

Age 33.1 32.7 33.5

% Male 88.7 88.0 90.1

Race/Ethnicity**

% Hispanic 62 50.8 42.1

% African-American 32.7 47.6 56.6

% White 5.3 1.6 1.3

% High school diploma

or GED

26 19.4 27.6

Weeks worked in past year 14.9 13.5 11.3

Medical, psychiatric problems

% Reports chronic medical

problem(s)

16.7 21 11.9

% Significant need for

medical treatment*

15.3 32.2 27.6

% Psychiatric

hospitalization, lifetime

6 6.5 7.9

% Serious depression,

lifetime

48.7 43.6 27.6

Substance abuse, criminal history

% N 1 prior admissions to

drug treatment*

37.4 45.1 59.2

Years regular use of heroin 6.9 7.1 6

Years regular use of crack

cocaine**

3.4 5.4 4.6

Years regular use

of cocaine**

4.1 7.6 8.4

% Significant need for drug

treatment

87.3 84.5 93.3

% Ever charged with

robbery**

12.7 21.8 31.6

Felony drug convictions** 3.9 3.1 2.3

* p b .05.

** p b .01.

Table 2

Recidivism results by group

Variable description

DTAP

(N = 150)

TASC

(N = 124)

Other CJ

referrals

(N = 76)

Follow-up periods

Tx. admission to

end date (months)**

44.5 41.1 42.9

Tx. termination/

completion to end date

28.1 26.8 29.9

Time-at-risk (TAR)

since admission

37.2 37.9 39

Unadjusted recidivism measures

Percent arrested** 30 28.1 55.6

Percent arrested for

felony*

16.7 17.7 22.9


misdemeanor*

18 16.1 35.5

Percent convicted of

felony

10 6.6 17.1

Percent convicted of

misdemeanor*

12 12.1 30.3


felony drug crime

10.7 13.7 18.4

Percent arrested for misd.

drug crime*

12.7 8.3 21.4

Months to first arrest 26.4 21.8 21.1

Recidivism measures, adjusted for TAR

Arrest rate (annualized)** .19 .21 .46

Arrest rate, felonies only .08 .13 .19

Arrest rate, misdemeanors

only**

.11 .08 .27

Conviction rate, felonies .04 .07 .10

Conviction rate,

misdemeanors**

.08 .07 .24

Arrest rate, drug felonies .05 .10 .12

Arrest rate, drug

misdemeanors**

.05 .03 .10

* p b .05.

** p b .01.


differences were controlled statistically in testing for group

differences in multivariate analyses.

2.2. Baseline measures

Client history and status information was gathered on

the Addiction Severity Index (ASI; McLellan, Luborsky,

Cacciola, & Griffith, 1985; McLellan et al., 1992). The ASI

questions were supplemented with several more detailed

items we created covering employment history and self-

reported criminal behavior. Official criminal history data

were obtained from the New York State Division of Criminal

Justice Services (DCJS). The research intake interview also

included the Perception of Legal Pressure questionnaire,

developed by the researchers. The 39-item measure had

respectable reliability, with a standardized internal consis-

tency coefficient (CronbachTs a) of .80. Scores on the over-

all PLP measure ranged from 32 to 73 with a mean of

52.4 (SD = 8.9); higher scores indicated greater perceived

legal pressure.

2.3. Recidivism

Recidivism was determined from official records obtained

from DCJS and the Department of Correctional Services.

The follow-up period covered by the data averaged 3.59

(SD = .43) years from the study participants’ date of ad-

mission to treatment and ranged from 2.75 to 4.47 years.

Each subjectTs time at risk was calculated by subtracting

time in custody (jail or prison) during follow-up from the

total follow-up duration. Time at risk averaged 3.16 years

(SD = .88). Several recidivism measures were assessed,

including number of re-arrests, charge types (misdemeanor,

felony, drug), time to arrest, and conviction. To control for

the variable follow-up period used in the research, we used

an arrest rate measure, calculated by dividing the total

number of arrests by time at risk, in the principal analysis.

To illustrate, the arrest rate for a client who was arrested

twice between her DTAP admission and the data cut-off

date 3 years later, and who spent 6 months in jail as a result


of those arrests, would be calculated as follows: 2 arrests /

(1096 days�181 days) = .0021587. When annualized for

descriptive purposes, this amounts to a rate of .79 arrests

per year.

2.4. Analysis plan

Analyses progressed in three phases. Initial analyses

focused on differences among the study groups and bi-

variate tests to select variables for inclusion in subsequent

multivariate analyses of retention. One-way ANOVAs and

chi-square tests were conducted to test the equivalence of the

three groups and to identify variables which needed to be

controlled in multivariate tests involving the grouping factor.

Bi-variate analyses (t-tests and chi-square statistics) were

done to identify variables from the ASI and the official cri-

minal record that were minimally related to retention ( p b .2)

and to assess multicollinearity of the predictor variables.

Bi-variate analyses also explored group differences on the

recidivism measures.

Variables emerging from the data reduction process

were used to build multivariate models. Ordinary least

squares multiple regressions were conducted involving the

arrest rate variable. Logistic regression was used to model

arrest as a dichotomous outcome and survival analysis

and Cox hazard models examined recidivism taking into

account time to arrest and censoring. Finally, conviction as a

dichotomous outcome was assessed in a logistic regression.

Predictors were entered in the models using the forward

selection method (tests using backward likelihood ratio

elimination yielded virtually the same results). The grouping

variable, dummy coded with the comparison group serving

as the reference category, was forced into the model in

0.40

0.50

0.60

0.70

0.80

0.90

1.00

0 100 200 300 400 500 6

Days from Admiss

Cu

mu

lati

ve S

urv

ival

Fig 1. Survival function of ar

the final step, to assess its independent effects on the recidi-

vism outcomes.

3. Results

3.1. Bi-variate recidivism outcomes

Table 2 shows recidivism results for the three study

groups. Bi-variate tests indicate that, consistent with the

retention findings reported previously (Young & Belenko,

2002), recidivism was significantly higher among compari-

son clients than those in the other two groups on several

measures, including percent arrested, rates of arrest control-

ling for time at risk, and time to arrest. The comparison

group had higher rates of felony and misdemeanor arrests

and convictions; however, this difference was not significant

in the case of the felony arrest and conviction rates. No

differences were observed between the DTAP and TASC

samples in any of these analyses.

Differences among the groups on time to arrest are

evident in the survival curves shown in Fig. 1. Compared to

DTAP, arrests clearly occur sooner in both the comparison

and TASC groups; the first arrests in the DTAP group were

observed about 6 months after admission to the program.

After a first group of TASC clients were arrested in the

initial months after admission, very few TASC participants

were re-arrested between 3 months and 1 year post-

admission. Throughout the tracking period, the proportion

of clients bsurvivingQ (not arrested) in TASC and DTAP was

very similar—within about five percentage points. By

contrast, the proportion arrested in the comparison group

steadily diverges from the arrest rate for the other groups

00 700 800 900 1000

ion

ComparisonTASCDTAP

Study Group

rest outcome by group.

Table 3

Multiple regression with arrest rate as criterion

Predictor Variable Coefficient

Standardized

coefficient (h)t

statistic

p

value

Gender (0 = male,

1 = female)

�.153 �.09 �1.77 .077

Education level �.099 �.11 �2.16 .031

Bothered by

employment problems

�.030 �.09 �1.65 .100

Held fulltime job

at admission

�.087 �.71 �1.37 .171

Total prior theft arrests .044 .12 2.26 .024

Total prior days

incarcerated

.028 .20 3.82 .000

Total prior felony drug

convictions

�.023 �.04 �.61 .547

Last charge was probation

or paroleviolation

.218 .13 2.55 .011

Sold drugs frequently in

prior year

�.246 �.13 �2.53 .012

Total years cocaine use �.007 �.08 �1.55 .122

Prior drug treatment

admissions

.009 .04 .91 .366

Prescribed

psychiatric meds

.226 .08 1.59 .113

Chronic medical problems .138 .09 1.75 .082

Study group

DTAP= 1; comparison

group = 0

�.216 �.19 �2.43 .015

TASC = 1; comparison

group = 0

�.229 �.19 �2.85 .005

Model Statistics R2 = .21

F = 5.64 (df = 15, 325)

p b .0001

Table 4

Cox regression results on re-arrest

Predictor variable Wald m2 h (p)

odds

ratio

Gender (0 =male, 1 = female) 9.55 �1.08 (.002) .334

Education level 6.13 �.367 (.01) .692

Bothered by employment

problems

8.25 �.165 (.004) .848

Employed full time past

3 years

8.61 �.673 (.003) .510

Total prior felony drug

convictions

.130 �.020 (.88) .980

Last charge was

probation/parole violation

12.83 .881 (.000) 2.41

Sold drugs frequently in

prior year

8.52 �.822 (.004) .440

Total years cocaine use 5.37 �.034 (.021) .967

Prior drug treatment

admissions

3.02 .057 (.08) 1.06

Chronic medical

problems

7.14 .670 (.007) 1.95

Study group 20.33 (.000)

DTAP= 1; comparison

group = 0

6.04 �.383 (.014) .682

TASC=1; comparison

group = 0

3.38 �.264 (.066) .768

Model Statistics m2 = 71.35 ( p b .001)

df / N = 12 / 342

�2 Log L= 1311.73


beginning about 8 months after admission. By 3 years post-

admission, the proportion of comparison group clients who

were re-arrested is about 25% greater than that rate for

TASC and DTAP groups.

3.2. Multivariate models

A number of multivariate analyses tested whether the

differences among the study groups on the recidivism

outcomes would hold up controlling for other factors.

Table 3 presents the OLS multiple regression results on

the arrest rate variable. The R2 for this overall model was

.21 (F = 5.64; df = 15, 325; p b .001). This analysis showed

that DTAP and TASC clients had significantly lower arrest

rates than the comparison group while holding constant pre-

admission group differences on prior drug convictions,

cocaine use, treatment admissions, and medical problems, as

well as other factors which met the criteria for entry in the

stepwise model.

Although the history variables on which the groups

differed were unrelated to subsequent arrests, other criminal

history variables were selected for the model, including total

time incarcerated, prior thefts, and prior probation or parole

violation. All three of these are traditionally associated with

arrest chronicity, particularly low level property crime and

violations while on supervision. Surprisingly, clients who

self-reported that they had sold drugs frequently in the prior

year had lower arrest rates. Education level was inversely

related to recidivism in the regression model, as were two

marginally related employment measures. Experiencing

chronic medical problems was also marginally positively

related to arrest rate.

Logistic regression and Cox hazard models of arrest

showed generally similar results. In the logistic analysis the

overall model had a pseudo R2 of .24 (model v 2 = 65.19;

p b .001) and the differences between the comparison group

and DTAP (h=�1.15, p b .001) and the comparison group

and TASC (h=�1.31, p b .001) on the dichotomous arrest

outcome were upheld as significant, yielding odds ratios of

.317 and .269 respectively. The Cox results showed the

same significant effect for the DTAP group, while the effect

for TASC group membership was marginal ( p = .069, see

Table 4). As in the OLS analysis, a prior parole or probation

violation was associated with arrest and time to arrest;

however, the prior theft and time incarcerated variables did

not contribute to the Cox model. Being female, having a

higher education level, steadily holding a full time job in

recent years, and reporting concern about employment

problems were inversely related to arrest and time to arrest

in the model. Mirroring findings in the multiple regression

analyses, frequent prior drug sales, as well as years of

regular cocaine use were negatively associated with the


arrest outcome, while having chronic medical problems was

a positive predictor.

To further test the robustness of the group differences, an

additional analysis examined conviction as a variant of

recidivism. We also considered performing an analysis

involving time incarcerated during follow-up, but rejected

this as an outcome of interest because it is as much a re-

flection of the varying sanctioning policies of the mandatory

treatment models as it is the behavior of the client. In the

conviction analysis, logistic regression was chosen over a

hazard model, since time to conviction is often influenced by

case processing practices and legal maneuvering. The

conviction results generally replicated those found for

arrest, with a pseudo R2 of .21 (model v2 = 51.90;

p b .003) and significant effects for DTAP (h =�1.20,

p b .002) and TASC (h =�1.28, p b .001), with odds ratios

of .303 and .278 respectively.

4. Discussion

State and local policymakers, faced with the worst

budget crises in a generation, are searching for safe and

effective ways to reduce criminal justice system costs

(Campbell, 2003). Treatment diversion programs are

attractive because of their potential cost efficiencies (Lang

& Belenko, 2000), but much more must be known about the

impacts of different compulsory treatment models and the

constituent policies and practices that make them work.

Extending a line of research on two such programs that had

been shown to have high retention rates (Young, 2002;

Young & Belenko, 2002), the present study showed that

criminal recidivism of participants in the Brooklyn DTAP

and TASC programs were substantially below those of a

matched comparison group of offenders who were man-

dated to treatment from conventional criminal justice

sources—sources that had similar clients but lacked the

more formal monitoring and sanctioning procedures of

DTAP and TASC. The value of these findings are enhanced

by the comparatively long follow-up period used in the

research, which averaged 3.6 years from the study partici-

pantsT date of admission to the program and 2.3 years from

the point these clients either completed or were terminated

from treatment. The capacity to assess recidivism through

arrest rates by calculating participantsT time at risk during

the follow-up period was another strength of the study

design. Taking time in custody into account helped level the

playing field between the groups, and arrest rate provided a

more accurate index of recidivism than more typical arrest

outcomes (e.g., probability of arrest, number of arrests).

The proportion of comparison group participants that

were rearrested (55.6%) was similar to that reported for

prison releasees nationally (Langan & Levin, 2002) but

almost twice the proportion rearrested in DTAP and TASC

(30% and 28.1% respectively). This pattern of group

differences was robust across multiple measures of recidi-

vism. Significantly more comparison group clients were re-

arrested for both misdemeanors and felonies during the

tracking period, and the reconviction rates in this group

were 1.7 to 2.5 greater than those for DTAP and TASC. The

fact that the felony reconviction differences were not

significant may have been due to the restricted range in

their distributions. The overall annual arrest rate for the

comparison group (.46) was over twice the rate for DTAP

(.19) or TASC (.21).

These recidivism results were tested in four different

multivariate analyses that controlled for the small number of

variables on which the groups differed pre-treatment, and

other factors found to be associated with the recidivism

outcomes. With these factors held constant, three of the

analyses assessed a variation of the overall re-arrest rate

outcome measure (OLS regression), any arrest (logistic

regression), and time to re-arrest accounting for censoring

(survival analysis and Cox hazard regression)—and a fourth

assessed any conviction (logistic regression). With the

exception of a marginal finding for the TASC group in

one analysis, results consistently showed that DTAP and

TASC clients had significantly more favorable outcomes on

these measures than the comparison group. As expected,

criminal history measures were also significant predictors

across the multiple models. An offense that included a

parole or probation violation was the history item most

predictive in all of the models assessing re-arrest. Other

significant criminal record items in the OLS model included

total prior thefts and days incarcerated—both indicators of

the kind of chronic pattern of frequent, low level arrests that

typically comprise criminal records with high arrest rates.

Most of the other factors that were significant in these

models had also been found in past research. Higher levels

of education, fulltime employment, and expressing concern

about employment problems were consistently associated

with less recidivism. Having chronic medical problems

was shown to be a risk factor for re-arrest. It was some-

what unexpected to find that female participants in the

TCs were less likely to recidivate, given concerns raised

by some reviewers about the effectiveness of confronta-

tional, group-oriented approaches with women substance

abusers (Lockwood, McCorkel, & Inciardi, 1998; Peugh &

Belenko, 1999). Additional research exploring the ability

of these TCs to address the unique needs of women

clients—their sensitivity to clientsT traumatic experiences

and psychological distress, and social support, child care,

and transitional issues (Bouffard & Taxman, 2000)—are

suggested by these results.

The key findings of reduced recidivism for the DTAP

and TASC groups provide potentially valuable support for

compulsory treatment and these models in particular. For all

the drawbacks of individual measures, recidivism is the

benchmark sought by policymakers and the public for

assessing correctional interventions. The need for studies

involving recidivism was further evidenced in a recent,

extensive review of research on compulsory treatment (Wild


et al., 2002). Of 161 articles that met their initial review

criteria, the authors identified only 18 studies that were

adequate methodologically to assess the effectiveness of a

compulsory treatment program, and only six of these

assessed recidivism as an outcome. Moreover, while more

than half of the studies that tracked other outcomes (entry

and retention in treatment) showed favorable effects for

clients in the compulsory treatment group, only two of the

six recidivism studies demonstrated lower recidivism rates

for this group. This review did not include the most recent

studies discussed in the background section of the present

paper, but it is notable that even the most rigorous of these

studies—controlled evaluations of drug court programs that

track recidivism outcomes (Gottfredson & Exum, 2002;

Listwan et al., 2003)—continue to show mixed results.

In this regard, it is instructive to review findings from the

Perception of Legal Pressure measure and from our obser-

vations and qualitative interviews with staff and clients,

which point to the specific coercive program policies and

practices that likely account for the success of DTAP and

TASC. Providing information to mandated clients about

the conditions of treatment participation and consequences

for failure—and convincing them those conditions will be

enforced—stood out as effective coercive strategies in this

research. DTAPTs use of a warrant enforcement squad, and

TASCTs strategy of mixing support for clients with frequent

cajoling and threats appears to create the perception of en-

forcement. Monthly progress reports to the legal agent, case

managersT phone calls, program visits, and the use of court

appearances and graduated responses to early signs of failure

likely reinforce this perception (Young, 2002; Young &

Belenko, 2002).

A major caveat to this research is that the findings may

be specific to compulsory models employing long-term

residential treatment, and/or to offenders with compara-

tively serious criminal records. The PLP was developed for

use in these community-based TCs, with these kinds of

clients, and studies must be done to assess whether these

findings can be replicated in the much more ubiquitous

outpatient settings and client profiles that predominate in

drug courts and most TASC programs. More generally, self-

reported perceptions of the presence and strength of

coercive program components is at best an indirect indicator

of their causal role in client retention and recidivism

outcomes. Future research should be aimed at expanded

use of both perceptual tools like the PLP as well as

objective indicators of program practices and policies in

study designs that can isolate and identify their impact on

client outcomes in the full range of compulsory models now

operating nationally.

Acknowledgments

This research was funded by a grant from the National

Institute of Drug Abuse (R01-DA09075) to Steven Belenko.

We much appreciate the support of our colleagues at the

Vera Institute of Justice, where much of this research was

conducted; Susan Powers and Paul Dynia, formerly of the

Office of the Kings County District Attorney; Kenneth Linn

of EAC-TASC; and the clients, administrators, and staff of

the treatment programs involved in the study.

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