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Who Cares for Involuntary Clients?Soheil Soliman MPH, MAE a , Harold A. Pollack PhD b & Jeffrey A. Alexander PhD aa Department of Health Management and Policy , University of Michigan School of PublicHealth , Ann Arbor, Michigan, USAb School of Social Service Administration , University of Chicago , Chicago, Illinois, USAPublished online: 28 Jan 2009.

To cite this article: Soheil Soliman MPH, MAE , Harold A. Pollack PhD & Jeffrey A. Alexander PhD (2009) Who Cares forInvoluntary Clients?, Substance Abuse, 30:1, 1-13, DOI: 10.1080/08897070802606279

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Substance Abuse, 30:1–13, 2009Copyright c© Taylor & Francis Group, LLCISSN: 0889-7077 print / 1547-0164 onlineDOI: 10.1080/08897070802606279

Who Cares for Involuntary Clients?

Soheil Soliman, MPH, MAEHarold A. Pollack, PhD

Jeffrey A. Alexander, PhD

ABSTRACT. The objectives of this study were to compare characteristics of outpatient substance abusetreatment (OSAT) units that serve high proportions of involuntary clients (ICs) with those that serve alow percentage of such clients. The authors analyze unit-level 1995–2005 data from the National DrugAbuse Treatment System Survey (NDATSS). Approximately 1/6 of OSAT units draw the dominantmajority of their clients from involuntary referrals. OSAT units that treat a high proportion of ICs areless likely to be accredited by professional organizations, have fewer treatment staff with advanceddegrees, and have shorter average treatment duration than do OSAT units that serve few ICs. OSAT unitsthat serve ICs are more likely to offer legal and domestic violence services but are less likely to offermental health services or aftercare. OSAT units that serve ICs are less likely to be hospital-affiliatedthan are other units. Clients at such facilities are more likely to be convicted of driving while intoxicated(DWI), are younger, are less likely to have received prior treatment, are more likely to remain abstinentafter treatment, but are more likely to be remanded back to courts. The authors conclude that ICs are animportant market niche in OSAT care. DWI is by far the most common offense reported in units thatspecialize in ICs. Aside from legal and domestic violence services, units with a high proportion of ICsappear to offer somewhat less intensive and professionalized services than do other facilities; however,clients at these units are more likely to be abstinent at the end of treatment and but more likely to beremanded back to the courts.

KEYWORDS. Court referral, involuntary clients, outpatient substance abuse treatment, trends

INTRODUCTION

The use of drug courts and diversion fromprisons to drug treatment has received muchattention from citizens and policymakers (1).

Soheil Soliman and Jeffrey A. Alexander are affiliated with the Department of Health Management andPolicy, University of Michigan School of Public Health, Ann Arbor, Michigan, USA.

Harold A. Pollack is affiliated with the School of Social Service Administration, University of Chicago,Chicago, Illinois, USA.

Address correspondence to: Soheil Soliman, MPH, MAE, Department of Health Management and Policy,University of Michigan School of Public Health, 109 S. Observatory, Ann Arbor, MI 48109 USA (E-mail:solimans@umich.edu).

Grant R01-DA32727 from the National Institute on Drug Abuse (NIDA) and a seed grant from the ChicagoCenter of Excellence in Health Promotion Economics supported this research. The views expressed here arethe authors’ and not necessarily those of NIDA. The Institutional Review Board of the University of Michiganapproved this research.

Initiatives such as California’s Proposition 36seek to reduce social costs of incarceration byshifting nonviolent drug offenders into treatmentinterventions. Criminal justice referrals to sub-stance abuse treatment have steadily increased

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over time, accounting by 2002 for 36% of all ad-missions into substance abuse treatment (2). De-spite many evaluations of court-mandated drugtreatment, the role and proper design of such in-terventions in reducing drug abuse and criminalrecidivism remains contested (3,4).

These and similar initiatives have engendereda long line of studies that find that involuntaryclients experience no worse treatment outcomesthan those experienced among other treatmentparticipants. This general finding has been sup-ported by the National Institutes of Health (NIH)consensus panels and by expert committees ofthe Institute of Medicine (e.g., 5,6). Most re-cently, Kelly, Finney, and Moos (7) report 1-year and 5-year outcomes from a prospectivestudy of 2095 patients with substance use disor-ders. These authors find that patients requiredto undergo treatment by the criminal justicesystem reported similar or better outcomes aswere found in two comparison groups: criminaljustice–involved clients who were not requiredto seek treatment, and clients who were not in-volved in the criminal justice system.

Several data sources provide nationaloverviews of treatment effects for involun-tary clients. Meta-analyses have been reported,though few studies are designed to address dif-ferences across treatment programs (3,8,9). An-glin and colleagues (3) note that program het-erogeneity and differences in implementationpose a key challenge to inferring the impact ofinvoluntary treatment for client outcomes. Evi-dence that involuntary clients (ICs) enter treat-ment with different, often greater needs than vol-untary clients (4,10), provides a second obstacleto gauging program effectiveness.

The quality and content of services offeredto court-mandated treatment clients has also re-ceived limited attention, though useful studieshave been reported in particular areas, such as inmandated treatment for convicted drunk drivers(11). Other studies suggest that the content andquality of OSAT services influence client out-comes. Differences in staffing, treatment dura-tion, and intensity of treatment, for example,help to account for general differences in clientoutcomes, and for outcomes within the specificpopulation of involuntary clients (4,9,12). Thereis also evidence that counselor competency (13),

group therapy (14), and the number of therapysessions (15) are associated with better outcomesfor involuntary clients. Howard and McCaugh-rin (9) found that for-profit facilities, facilitiesaffiliated with a hospital, and facilities that of-fered more group therapy sessions had betteroutcomes as measured by the percent of invol-untary clients completing treatment (9).

The existing literature has mostly focused onthe link between involuntary referral and sub-sequent substance use. Although substance useis a key outcome, ICs have other distinctiveneeds. Many ICs require legal services (16).Other needs include housing and treatment forcomorbid mental illnesses. Provision of ancil-lary services tailored to clients’ specific needsis linked to better outcomes and social perfor-mance, and has been identified as central to ef-fective care (14).

Many studies on court-mandated clients fo-cus on a particular drug court and the treatmentcenters to which the court refers offenders. Eval-uations of one drug court or one set of treatmentinterventions rarely allow researchers to controlfor differences across drug treatment programsthat clients are mandated to attend (8). Differ-ences in ancillary services and quality of caremay be important. Individuals receiving man-dated treatment could attend higher- (or lower-)quality treatment facilities than are receivedby otherwise similar peers. Facilities that servelarge numbers of mandated clients may system-atically differ from others in available resources,treatment practices, and other factors that influ-ence client outcomes. Such systematic differ-ences in unit quality and practice could thus biasevaluations of mandated treatment interventions.If unit quality is associated with higher percent-ages of involuntary clients, studies that do notcontrol for unit quality may find differences inmandated clients’ outcomes that are attributableto unit quality instead of the compulsory treat-ment.

This paper considers how variations in keyoutpatient substance abuse treatment (OSAT)unit characteristics are associated with the pro-portion of involuntary clients being served atsuch facilities. It examines whether and howOSAT units that serve mostly involuntary clientsdiffer from otherwise similar OSAT facilities

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that serve mostly voluntary clients. This paperalso documents the trends in these relationshipsand how services and unit characteristics havechanged from 1995 to 2005.

It is the first study of its kind to use nation-ally representative OSAT panel data to exam-ine trends and correlates of services provided inrepresentative units that serve court-mandatedclients. Given increasing numbers of criminalreferrals to drug treatment, such data are impor-tant for policy makers to consider the populationof OSAT units that serve involuntary clients, andthe resulting quality and scope of services invol-untary clients are likely to receive.

DATA

The data for this study come from the Na-tional Drug Abuse Treatment System Survey(NDATSS). The survey covers a national sampleof OSAT facilities. OSAT centers are defined asphysical facilities that use at least half of theirresources treat individuals with substance abuseproblems on an outpatient basis. NDATSS is amixed panel survey administered by the Institutefor Social Research at the University of Michi-gan. Units previously surveyed are reinterviewedin subsequent waves. To maintain a representa-tive sample and to replace panel units that dieor exit, a new random sample of OSAT units isadded at each wave. The sample is derived froma census of outpatient substance abuse treatmentprograms, excluding treatment programs run bycorrectional facilities and the Veterans Adminis-tration. NDATSS includes a representative sam-ple of OSAT units using methadone mainte-nance and outpatient drug-free (nonmethadone)modalities. The sampling frame and methodol-ogy have been described in greater detail in andAdams and Heering (17) and Heering (18). Fur-ther details on NDATSS may be found in Pol-lack, D’Aunno, and Lamar (19).

Established survey methodology was fol-lowed to produce reliable and valid data. Datawere collected in two phone interviews, one withthe unit director and one with the clinical su-pervisor. The unit director and clinical super-visor are each asked to participate. The direc-tor answers questions pertaining to ownership,

affiliations, funding, accreditation, and man-aged care arrangements. Clinical Supervisorswere asked about staffing, treatment prac-tices, client characteristics, and services. A to-tal of 1454 nonmethadone observation pointswere surveyed for this analysis. We excludedmethadone programs from the sample becausemost methadone programs had no or very few in-voluntary clients. There were 486 nonmethadoneunits surveyed in 1995 (88% response rate), 563nonmethadone units surveyed in 2000 (89% re-sponse rate), and 405 nonmethadone units sur-veyed in 2005 (88% response rate). Involuntaryclients made up less than 25% of clients in 955units, and more than 75% of the clients in 320units.

Measures

Some data in the survey are available regard-ing the specific sample of involuntary clients.Other data are only available as an average forall clients served by the OSAT unit. Clinical su-pervisors were asked: “In the most recent com-plete fiscal year, how many of your unit’s out-patient substance abuse clients were involuntaryclients who were compelled to come for treat-ment because of a court order?” They were alsoasked the percents of involuntary clients whowere African American, Hispanic, and female.Data were also collected regarded the percentageof ICs charged with different specific crimes, in-cluding driving while intoxicated (DWI), theft,domestic violence, drug possession, and drunkand disorderly conduct.

NDATSS data contain three measures of out-comes specific to court-mandated clients: thepercent abstinent at the end of treatment, thepercent who meet treatment goals, and the per-cent who are remanded back to the courts. Al-though some programs may not expect or requireabstinence at the end of treatment, this is a cen-tral treatment goal. Meeting treatment goals is asecond, broader measure of overall compliance.Remand back to the referring courts representsnoncompliance by the client serious enough tosuggest a violation of the terms of diversioninto treatment. Remand can represent differentlevels of noncompliance depending on the re-quirements of the referring court, the treatment

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facility, and the amount of involvement of thecourts in the treatment program.

Supervisors also responded to questions aboutthe sociodemographic and substance-use char-acteristics of all clients they serve. In addition,NDATSS explored key unit characteristics suchas the number of clients treated per year; thepercent of treatment staff with a masters degree,MD, or PhD; accreditation status from the JointCouncil on Accreditation of Healthcare Orga-nizations (JCAHO); for-profit, not-for-profit, orpublic ownership status; free-standing or affilia-tion with a hospital or mental health center; andthe age of the unit.

Provision of various services was operational-ized as the percent of clients who received thatservice. Services of interest included in the studyare after-care, domestic violence counseling,mental health services, physical exams, employ-ment counseling, and criminal legal counseling.We also included unit-level measures of meantreatment duration and a combined measure ofaverage weekly number of hours of individualand group therapy. We controlled for both geo-graphic and year effects.

METHODS

We seek to examine the extent to which in-voluntary clients are referred to certain OSATunits and how treatment services compare acrossOSAT units that serve varying percentages ofICs. NDATSS includes repeated observations ofthe same units. Because unobserved (but stable)characteristics of specific units may be impor-tant, we use generalized estimating equations(GEEs) to account for repeated observations ofthe same OSAT unit.

Many OSAT units reported item nonresponsefor at least one variable included in our regres-sion specifications. To address potential biasesassociated with item nonresponse, we use mul-tiple imputation in our baseline specifications(20–22). We use the STATA command mvis forthe imputation and micombine for the analysis.Ten imputations were used for this analysis. Asshown by Schafer (23), this is sufficient for suf-ficient estimation in large samples.

In our baseline regressions, the dependentvariable is percent of clients who are court

mandated. Our baseline regression includesclient and organizational characteristics, both ofwhich may be correlated with services providedby the unit and with the proportion of ICs. Wealso account for organization characteristics (ac-creditation, ownership and affiliation) and treat-ment practices (duration of treatment, treatmentstaff, number of therapy sessions per week).

We examined several different correlationsbetween the percent of ICs and the indepen-dent variables. The first multivariate analysis in-cluded unit and client characteristics and crimesassociated with involuntary clients. Because ofthe large number of covariates in the main re-gression, we also ran separate regressions look-ing only at unit characteristics, clients charac-teristics, and crimes. Each regression was runon all three waves combined and for each waveindividually.

To sharpen distinctions across units, we alsoperformed logit analyses using only units thathad either less than 25% or more than 75% in-voluntary clients. We only report the bivariateresults of this analysis because the results fromlogit regressions did not differ from regressionswhere the dependent variable was percent of in-voluntary clients. For convenience, we refer tothe under-25% group as “non-IC” OSAT units.We refer to the over-75% group as the “IC”OSAT units.

We also performed the same regressions asabove using outcome measures for involuntaryclients as the dependent variable. We ran sepa-rate regressions on each of the outcomes at theend of treatment (% abstinent, % met goals, and% remanded). To examine various correlations,we ran these models on all independent vari-ables, on client characteristics only, unit charac-teristics only, and criminal characteristics.

RESULTS

As shown in Table 1, bivariate relationshipbetween the extremes of involuntary clients andother unit characteristics reveal some importantdifferences. DWI is by far the most commonlegal infraction committed by ICs. More than50% of clients in IC units are convicted of DWI,compared with 30% in non-IC units (P < .001).

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TABLE 1. Bivariate Means of Various Client and Unit Characteristics in Units with >75%and <25% Involuntary Clients

All units n <25% n >75% n t score

Northeast 22.56 1454 23.48 575 16.24 314 2.54Midwest 28.82 1454 27.65 575 28.34 314 −0.22South 25.65 1454 28.17 575 22.61 314 1.8West 22.97 1454 20.7 575 32.8 314 −4.021995 33.43 491 29.91 174 32.48 102 −0.792000 38.72 583 40.7 238 36.31 114 1.282005 27.85 415 29.39 176 31.21 98 −0.56Private for-profit 18.69 1450 19.34 574 21.09 313 −0.62Private not-for-profit 61.93 1450 62.2 574 60.06 313 0.62JCAHO 22.37 1435 27.1 572 16.34 306 3.61% nnits affiliated with hospital 13.27 1454 17.39 575 7.01 314 4.34% units affiliated with MHC 17.95 1454 16 575 16.88 314 −0.34% of staff >BA 45.76 1454 50.37 575 37.92 314 4.97Average no. of treatment sessions/week 2.45 1284 2.73 514 2.46 281 1.16% clients in an HMO 13.68 1219 17.16 490 8.89 265 4.83% of clients Hispanic 12.19 1399 11.5 568 14.99 309 −2.54% clients Black 22.29 1399 23.98 566 20.27 310 1.97% women 33.68 1377 35.59 567 32.37 310 2.18% unemployed 37.83 1400 39.71 568 35.5 313 2.12% uninsured 26.02 1348 25.21 542 27.16 290 −0.81% polydrug users 69.3 1375 69.49 556 67.92 306 0.8% received prior treatment 59.39 1391 61.21 564 55.11 311 3.24% receive aftercare 85.9 1397 88.53 571 82.01 311 3.23% require prior authorization 23.06 1362 27.27 546 16.53 297 4.39Average age 34.41 1394 34.89 566 33.94 311 2.31No. of years OSAT unit been in operation 17.28 1438 18.04 571 15.77 310 3.34No. clients/year 685.65 1397 845.6 574 482.97 314 4.92Average treatment duration (in months) 5.81 1388 5.94 564 6.06 309 −0.33% of clients convicted of:

Drunk and disorderly 8.47 1240 6.74 496 9.79 299 −3.04Domestic violence 9.84 1246 8.44 499 11.38 301 −3.04DWI 41.19 1254 30.16 501 51.22 303 −8.72Theft 11.67 1233 9.53 494 12.87 296 −2.87

% of clients receiving counseling for:Mental health 25.98 1279 30.19 491 20.5 306 5.14Domestic violence 16.5 1272 16.02 488 19.66 304 −1.89Employment 23.56 1270 25.1 490 23.69 301 0.62Legal 14.17 1272 12.36 491 16.3 302 −2.13Physical health 30.64 1268 35.78 490 25.04 301 3.94

% of clients:Abstinent at the end of treatment 49.22 1260 29.43 849 58.8 305 13.71Met treatment goals 50.66 1271 30.09 857 61.84 308 15.28Remanded back to courts 19.25 1268 11.83 858 22.18 305 −8.9

Drunk and disorderly conduct and domestic vio-lence were also more common in IC units, but thebase differences were much smaller in reportedoffending.

IC units appear to have less professionalizedtreatment staff. Only one third of IC-unit staffhave advanced degrees, compared with 50% innon-IC units. In similar fashion, only 16% of

IC units are JCAHO accredited, compared with27% of non-IC units. IC units are less likely tobe affiliated with a hospital and are more likelyto provide legal services. More clients receivecriminal legal counseling at IC units. We foundno differences between the two groups on theaverage number of therapy sessions per weekand in average treatment duration.

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There is also a decline in the average numberof involuntary clients at the units over time. Inthe average OSAT unit in our sample, 33% ofclients were involuntary in 1995. This climbedto 38% in 2000 and fell to 28% in 2005. Thesechanges were not accompanied by changes inthe units who had less than 25% or greater than75% of the clients involuntarily participating intreatment.

We also examined the average number ofclients who were reported to complete treat-ment, who were abstinent, and who met treat-ment goals. Fifty-eight percent of involuntaryclients at IC units were reported abstinent at theend of treatment compared with 30% at non-IC units. Approximately 60% of IC clients mettreatment goals within IC units. Only 30% of ICsmet treatment goals when they received servicesat non-IC units. IC units reported more clientsremanded back to the court (22%) than did non-IC units (12%). These results were significantand stable across all three waves.

Regression Results

GEE analyses confirmed many observed bi-variate relationships. There were 831 completeobservations available for the full regression. Af-ter multiple imputation (MI), the analysis wasperformed on 1342 nonmethadone units. Thepoint estimates for the regression results did notchange, but the MI did create tighter confidenceintervals. This increased the significance levelof some variables and making a few variablessignificant that previously were close, but notsignificant. The use of MI did not appreciablyalter our point estimates.

In the main model (Table 2) with both clientand unit characteristics (n = 1327), involuntaryclients were more likely to go to smaller unitsand newer units. A high proportion of ICs isassociated with a decreased proportion of unem-ployed clients. It is associated with a decreasedproportion of clients receiving after-care ser-vices, and a decreased proportion of clients whobelong to health maintenance organizations orpreferred provider organizations. Clients at ICunits are more likely to receive counseling fordomestic violence and for criminal legal diffi-culties. There were no differences in treatment

duration or the average number of individual andgroup therapy sessions that clients received perweek.

In the main model with criminal offenses in-cluded (Table 2), the criminal legal counselingwas no longer significantly associated with thepercent of involuntary clients, but average ageand the education level of the treatment staffwere both negatively associated with the percentof involuntary clients. DWI and possession werethe only two offenses that were associated withincreasing involuntary clients.

Examining the relationship between clientcharacteristics and the percent of ICs (resultsnot shown) highlights other patterns in the data.A higher proportion of IC clients is associatedwith a smaller proportion of Hispanic clients.It is also associated with reduced prevalence ofprior treatment for substance use disorders, andwith a smaller proportion of female clients. Noadditional results are significant.

Other patterns emerge in year-specific regres-sions (not shown). Again, units with larger pro-portions of ICs have lower mean client age, anda higher proportion of clients experiencing al-cohol disorders. In 1995 more units in the Westhad higher numbers of involuntary clients, butthis relationship disappears by 2005.

In regressions of the percent of ICs on unitcharacteristics (not shown), several additionalvariables were significantly associated with anincreasing percent of involuntary clients. Unitswith larger proportions of ICs were staffedwith fewer people with advanced degrees andhad fewer clients receiving mental and physicalhealth services.

Treatment duration does not appear to dif-fer between IC and non-IC units in multivari-ate analysis. The 2005 data contained questionsabout treatment duration for involuntary clientsas well as the overall treatment duration. The av-erage treatment duration for involuntary clients(6.5 months) is shorter than the average treat-ment duration on the whole (10.5 months).

Multivariate analyses (not shown) of criminalconvictions indicate that “driving while intoxi-cated” was the only crime that showed a consis-tent, significant association with more involun-tary clients. There was an association with drugpossession and more involuntary clients. This

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TABLE 2. Regression of Unit and Client Characteristics on Percent of Involuntary Clients

% Involuntary clients No. of values imputed

1995 −0.940 (2.904) −2.836 (2.806)2000 −2.636 (2.625) −3.016 (2.519)2005 Referent ReferentNortheast Referent ReferentMidwest 2.228 (2.889) 2.384 (2.787)South −3.913 (2.971) −4.798 (2.831)West 6.151 (3.057)∗ 5.166 (2.938)OwnershipPublic Referent Referent

Private for-profit −2.712 (3.616) −3.549 (3.512) 37Private not-for-profit −0.322 (2.605) −1.244 (2.499) 37

AffiliationFree standing Referent ReferentHospital −5.251 (3.743) −4.501 (3.617) 8Mental health center 4.606 (2.673) 3.910 (2.569)JCAHO −2.924 (3.005) −1.988 (2.879) 50Unit size −0.005 (0.001)∗∗ −0.005 (0.001)∗∗ 69% staff > BA −0.048 (0.028) −0.055 (0.027)∗Treatment duration −0.331 (0.199) −0.237 (0.191) 83

Average therapy sessions/week −0.354 (0.379) −0.320 (0.355) 170% Black 0.022 (0.042) 0.032 (0.042) 67% Hispanic −0.012 (0.054) 0.005 (0.052) 68% Women −0.067 (0.050) −0.007 (0.048) 90% Unemployed −0.093 (0.041)∗ −0.058 (0.041) 69% HMO −0.141 (0.055)∗ −0.107 (0.051)∗ 264

% Require prior authorization −0.006 (0.032) −0.010 (0.030) 122% received after care −0.089 (0.031)∗∗ −0.088 (0.030)∗∗ 73Unit age −0.363 (0.107)∗∗ −0.349 (0.103)∗∗ 22Average client age −0.281 (0.175) −0.335 (0.171)∗ 72

% Received prior treatment −0.042 (0.036) −0.009 (0.035) 78% poly drug users −0.021 (0.035) −0.014 (0.033)% uninsured 0.024 (0.032) 0.024 (0.032) 136% paid reduced fee 0.014 (0.027) 0.013 (0.026) 111% abuse alcohol 0.078 (0.038)∗ 0.040 (0.038)

% clients receive:Financial counseling −0.013 (0.039) −0.019 (0.037) 211Criminal legal counseling 0.087 (0.039)∗ 0.041 (0.039) 201Employment counseling −0.035 (0.042) −0.018 (0.040) 203Domestic violence counseling 0.102 (0.039)∗∗ 0.093 (0.038)∗ 201Physical exams −0.046 (0.028) −0.024 (0.028) 205Mental health services −0.092 (0.041)∗ −0.106 (0.039)∗∗ 194

% clients charged with:Drunk and Disorderly Conduct 0.029 (0.078) 233

Domestic violence −0.016 (0.083) 227DWI 0.268 (0.032)∗∗ 219Theft 0.094 (0.073) 240Possession 0.176 (0.046)∗∗ 227Constant 81.414 (9.472)∗∗ 64.219 (9.342)∗∗

Observations 1342 1342Number of OSAT units 710 710

Note. Standard errors in parentheses.∗Significant at .05.∗∗Significant at .01.

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association was significant in both pooled andyear-specific regression specifications.

Treatment Outcomes

Table 3 displays regression analyses of unitcharacteristics on treatment outcomes. We reportthe models with and without criminal offendinghistories. We found several significant resultsfor clients at IC units. A lower proportion ofstaff with advanced degrees was associated withfewer remanded clients. Criminal legal counsel-ing and domestic violence counseling were alsoassociated with more clients meeting their treat-ment goals. Treatment duration was inverselyassociated with clients meeting their treatmentgoals.

In the full model (results not shown), onlybeing charged with a DWI was significantlyassociated with all three outcomes (% absti-nent, % met goals, and % remanded). The ef-fect was larger for being abstinence and meetingtreatment goals. Being charged with possessionwas significantly associated with the percent ofclients who were abstinent and who met the treat-ment goals at the end of treatment. Fewer clientswere remanded back to the courts at units with ahigh proportion of treatment staff with advancedacademic degrees. There is also an associationbetween the percent of clients who receive crim-inal legal counseling and the percent of clientswho met their treatment goals.

In the models that included criminal offendinghistory, the results changed slightly. Treatmentduration, criminal legal counseling, and em-ployment counseling were no longer associatedwith clients meeting treatment goals. Among thecriminal offenses, drunk and disorderly conductwas negatively associated with abstinence andtreatment goals, and domestic violence was as-sociated with more clients remanded back tocourts. DWI and possession were associatedwith all three outcomes.

Examining the relationship between clientcharacteristics and the three outcomes (notshown), units with more Hispanic clients hadmore clients remanded back to the courts. Fewerclients were remanded back to the courts in unitsthat served a greater proportion of women. Poly-drug users were less likely to be abstinent at

the end of treatment. We also found strong timetrends. Clients were more likely to be remandedback to the courts in 1995 and less likely to beabstinent in 2000 than in 2005.

The strongest and most consistent associa-tions with outcomes were being charged withpossession and driving while intoxicated (Table4). A greater proportion of clients charged withdrunk and disorderly conduct was also associ-ated with more clients meeting treatment goalsand remaining abstinent at the end of treatment.There are large and strong differences over time.More clients were abstinent at the end of treat-ment in 2005 than in 2000 or 1995. Althoughunits with more clients charged with possessionand DWI were associated with all three out-comes, the effects were larger for abstinence andtreatment goals.

DISCUSSION

Study Limitations

Our analysis has several limitations that mustbe considered in evaluating the findings.

First, NDATSS only examines OSAT care.We do not analyze care for involuntary clientsin residential facilities. Existing data indicatethat OSATs care for more than three quartersof involuntary clients receiving substance abusetreatment (24). Estimates from the TreatmentEpisode Data Set (TEDS) find that, of clientsreferred from the criminal justice system, 77.6%entered OSAT units in 1995 and 80.2% of themwent to OSAT units in 2004 (25). Our analy-sis is therefore pertinent to the average involun-tary client, but likely does not apply to the mostintensively served and monitored subset of in-voluntary clients. We presume that our analysisdoes not apply to offenders charged with seri-ous felonies, who may be referred to residential,governmental, or prison programs for treatment.

Second, NDATSS data capture unit-level as-sociations. We cannot determine the extent towhich involuntary clients receive different ser-vices from those provided to voluntary clients inthe same units.

Third, our data contains no information ondifferences in the underlying treatment need. As

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TAB

LE3.

Uni

tCha

ract

eris

tics

Ass

ocia

ted

with

Trea

tmen

tOut

com

esof

Invo

lunt

ary

Clie

nts

No.

ofM

etM

etva

lues

Rem

ande

dA

bstin

ent

goal

sR

eman

ded

Abs

tinen

tgo

als

impu

ted

1995

3.71

4(1

.459

)∗−6

.141

(2.5

77)∗

0.97

3(2

.487

)3.

550

(1.3

92)∗

−8.3

49(2

.356

)∗∗

−2.7

01(2

.197

)20

002.

250

(1.4

13)

−7.3

03(2

.500

)∗∗

−3.1

27(2

.409

)1.

767

(1.3

38)

−7.8

83(2

.323

)∗∗

−3.9

58(2

.181

)20

05R

efer

ent

Ow

ners

hip

Pub

licR

efer

ent

Priv

ate

for-

profi

t−5

.163

(1.8

60)∗

∗4.

910

(3.2

31)

11.6

63(3

.112

)∗∗

−4.2

09(1

.804

)∗1.

834

(2.8

97)

5.54

7(2

.631

)∗37

Priv

ate

not-

for-

profi

t−0

.241

(1.4

13)

5.37

9(2

.433

)∗6.

181

(2.3

44)∗

∗−0

.550

(1.3

43)

4.33

9(2

.142

)∗4.

942

(1.9

65)∗

37A

ffilia

tion

Free

stan

ding

Ref

eren

tH

ospi

tal

−1.4

49(2

.082

)1.

643

(3.5

71)

−0.8

74(3

.470

)−0

.412

(1.9

79)

2.10

6(3

.182

)−1

.227

(2.9

34)

8M

enta

lhea

lthce

nter

1.28

7(1

.495

)1.

073

(2.5

49)

0.65

3(2

.459

)0.

555

(1.4

24)

0.74

9(2

.268

)0.

587

(2.0

83)

JCA

HO

−4.5

83(1

.662

)∗∗

−3.5

07(2

.868

)−0

.541

(2.7

68)

−3.8

22(1

.597

)∗−1

.919

(2.5

81)

0.38

9(2

.370

)50

Uni

tage

0.03

9(0

.060

)−0

.201

(0.1

02)∗

−0.1

44(0

.098

)0.

046

(0.0

56)

−0.2

10(0

.092

)∗−0

.175

(0.0

84)∗

22Tr

eatm

entd

urat

ion

−0.1

38(0

.107

)−0

.053

(0.1

85)

−0.3

76(0

.178

)∗−0

.060

(0.1

02)

0.06

9(0

.165

)−0

.283

(0.1

52)

83A

vera

geth

erap

yse

ssio

ns/w

eek

0.09

0(0

.192

)−0

.118

(0.3

36)

−0.1

48(0

.328

)0.

085

(0.1

74)

−0.0

06(0

.307

)0.

001

(0.2

91)

194

Uni

tsiz

e0.

001

(0.0

01)∗

0.00

0(0

.001

)−0

.000

(0.0

01)

0.00

1(0

.001

)0.

000

(0.0

01)

−0.0

00(0

.001

)69

%st

aff>

BA

−0.0

37(0

.015

)∗0.

009

(0.0

26)

0.03

2(0

.025

)−0

.033

(0.0

14)∗

0.00

3(0

.023

)0.

015

(0.0

21)

%cl

ient

sre

ceiv

e:A

fterc

are

0.00

2(0

.017

)0.

069

(0.0

29)∗

0.02

0(0

.028

)0.

002

(0.0

16)

0.07

7(0

.027

)∗∗

0.02

8(0

.024

)73

Fin

anci

alco

unse

ling

0.00

8(0

.021

)0.

049

(0.0

37)

0.04

5(0

.036

)0.

002

(0.0

20)

0.04

0(0

.034

)0.

040

(0.0

31)

211

Crim

inal

lega

lco

unse

ling

0.01

4(0

.021

)0.

058

(0.0

36)

0.09

8(0

.035

)∗∗

−0.0

21(0

.020

)−0

.014

(0.0

33)

0.03

7(0

.030

)20

1

Em

ploy

men

tcou

nsel

ing

−0.0

01(0

.021

)−0

.061

(0.0

38)

−0.0

97(0

.036

)∗∗

0.00

4(0

.021

)−0

.013

(0.0

34)

−0.0

30(0

.031

)20

3D

omes

ticvi

olen

ceco

unse

ling

−0.0

29(0

.021

)0.

067

(0.0

37)

0.07

0(0

.035

)∗−0

.047

(0.0

20)∗

0.06

4(0

.034

)0.

071

(0.0

31)∗

201

Num

ber

ofO

SAT

Uni

ts71

671

371

771

671

371

7

9

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TAB

LE3.

(con

tinue

d)

No.

ofM

etM

etva

lues

Rem

ande

dA

bstin

ent

goal

sR

eman

ded

Abs

tinen

tgo

als

impu

ted

Phy

sica

lexa

ms

−0.0

17(0

.015

)0.

012

(0.0

27)

−0.0

42(0

.026

)−0

.008

(0.0

15)

0.05

3(0

.024

)∗0.

005

(0.0

22)

205

Men

talh

ealth

serv

ices

0.01

4(0

.022

)−0

.103

(0.0

39)∗

∗−0

.062

(0.0

37)

0.00

4(0

.021

)−0

.091

(0.0

34)∗

∗−0

.045

(0.0

31)

194

%cl

ient

sch

arge

dw

ith:

Dru

nkan

dD

isor

derly

Con

duct

0.05

3(0

.041

)−0

.138

(0.0

68)∗

−0.1

78(0

.063

)∗∗

233

Dom

estic

viol

ence

0.14

3(0

.044

)∗∗

0.05

7(0

.072

)0.

073

(0.0

66)

227

DW

I0.

061

(0.0

16)∗

∗0.

385

(0.0

27)∗

∗0.

473

(0.0

25)∗

∗21

9T

heft

−0.0

00(0

.037

)0.

076

(0.0

61)

0.06

7(0

.056

)24

0P

osse

ssio

n0.

158

(0.0

24)∗

∗0.

299

(0.0

39)∗

∗0.

201

(0.0

36)∗

∗22

7C

onst

ant

20.0

38(2

.919

)∗∗

48.3

60(5

.112

)∗∗

49.1

64(4

.910

)∗∗

11.8

20(2

.938

)∗∗

23.8

92(4

.848

)∗∗

25.2

17(4

.499

)∗∗

Obs

erva

tions

1284

1275

1287

1284

1275

1287

Num

ber

ofO

SAT

Uni

ts71

671

371

771

671

371

7

Not

e.S

tand

ard

erro

rsin

pare

nthe

ses.

∗ Sig

nific

anta

t.05

.∗∗

Sig

nific

anta

t.01

.

10

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Soliman, Pollack, and Alexander 11

TABLE 4. Crimes Associated with Treatment Outcomes

Met goals Abstinent Remanded No. of values imputed

1995 −2.358 (1.750) −6.108 (1.902)∗∗ 3.225 (1.136)∗∗2000 −2.273 (1.760) −5.558 (1.915)∗∗ 1.247 (1.128)Drunks and Disorderly −0.204 (0.063)∗∗ −0.161 (0.068)∗ 0.068 (0.042) 233Domestic Violence 0.128 (0.067) 0.101 (0.072) 0.107 (0.045)∗ 227DWI 0.462 (0.024)∗∗ 0.366 (0.026)∗∗ 0.057 (0.017)∗∗ 219Theft 0.071 (0.055) 0.082 (0.060) −0.002 (0.037) 240Possession 0.199 (0.038)∗∗ 0.285 (0.041)∗∗ 0.161 (0.025)∗∗ 227Constant 29.598 (2.065)∗∗ 31.884 (2.258)∗∗ 8.391 (1.401)∗∗Observations 1231 1223 1227Number of OSAT Units 707 705 706

Note. Standard errors in parentheses.∗Significant at .05.∗∗Significant at .01.

noted above, ICs may have greater needs at base-line than voluntary clients in the same facilities(4).

Fourth, we have little information regardingthe content of OSAT services of special importto ICs. We capture, for example, whether legalassistance is provided to clients. We know lit-tle about how such services are provided or theproportion of clients who require these services.More clients receive criminal legal counseling atIC units than at non-IC units. Still, less than 20%of clients at units with high proportions of ICs re-ceive legal counseling. Our data do not indicatehow many need further legal assistance. IC unitsare also more likely than others to offer domesticviolence counseling. This pattern is consistentwith the higher prevalence of criminal domesticviolence charges among involuntary clients.

Other findings suggest that ICs receive asomewhat less intensive mix of services, pro-vided by somewhat a less professionalized (asmeasured by academic degrees) distribution ofOSAT staff. For some services, such as mentalhealth services and physical exams, the propor-tion of ICs is inversely related to the proportionof clients receiving these specific services.

Finally, we have no measure of court involve-ment and communication between courts andtreatment facilities, a factor that some studieshave associated with favorable outcomes (3).

Despite these limitations, we find evidencethat IC units offer services that (imperfectly)match the distinctive needs of involuntary

clients. Our data do not allow us to draw stronginferences about the effect of cross-unit differ-ences on client outcomes. More clients on av-erage are remanded to the courts at IC units. Atthe same time, a higher proportion of clients suc-cessfully complete treatment and are abstinent atthe end of treatment in the same units. These ap-parently contradictory results are consistent withthe view that coercive treatment strategies can in-crease clients’ likelihood of attaining abstinenceand other treatment goals, even as such strate-gies increase the likelihood that some clientswill receive more explicit punishment and pres-sure from legal authorities. One caveat about thisfinding is that we cannot be certain that higher re-ported abstinence is unbiased. There is a strongincentive for IC clients to report abstinence toavoid punishment. Depending on the require-ments of the referring court and the treatmentcenter, deception may or may not be possible.Drug and alcohol testing, for example, may elicitmore candid responses regarding substance use.

Many OSAT clients receive services throughinvoluntary referrals from legal authorities. In-voluntary referral is especially common withinparticular client subgroups: Younger individu-als, first-time offenders, men, and individualswithout previous substance abuse treatment (10).

It may surprise some readers that the pop-ulation of ICs captured in our data is a rela-tively criminally inactive, majority-white pop-ulation. The majority of ICs receiving OSATservices are charged with relatively minor, often

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12 SUBSTANCE ABUSE

alcohol-related offenses. IC units included twicethe prevalence of previous DWI offenses as non-IC units. ICs charged with DWI do not appearto have high rates of other criminal convictionsrelated to their OSAT care. Individuals chargedwith DWI, typically alcohol users, appear to bethe largest population of clients served by suchinterventions. The association with more clientsbeing remanded back to the units suggests thatthere is heterogeneity among these clients andcoercion is effective for many, but not all clients.

Our results suggest that treatment units wheremost clients are court mandated are a specificmarket segment served by a subset of OSATs thatspecialize in such care. This market segment foralcohol abusers charged mainly with domesticviolence and DWI may also explain why thoseunits offer less intensive services and still havegood compliance (higher percentages of clientsabstinent at the end of treatment and more clientsmeeting their treatment goals). Such offensesprovide an important pathway for (often non-dependent) alcohol abusers to come to the atten-tion of legal authorities and the treatment system.This population of alcohol abusers may requireless intensive services than do clients with de-pendence disorders. The threat of coercion mayalso prove more effective for this population thanfor other clients. Another finding that points toa market niche is that many units with high con-centrations of court-mandated clients are smallerand newer, suggesting that these units arose tomeet a demand created by drug diversion courtsand similar interventions.

Individualized trial data would help disentan-gle how clients charged with different offenseswould likely respond to differing levels of treat-ment. Coercion and lower intensity services maywork well for the subset of involuntary clientscharged with alcohol-related misdemeanors andfor first-time offenders without prior treatment.More intensive services are likely required formore criminally active clients and for those withmore severe dependence disorders. Policy mak-ers and courts should implement diversion pro-grams that entail a more comprehensive assess-ment of needs and a broader range of services,tailored to meet the needs of each client and ef-fective in achieving good outcomes for a broaderrange of offenders. Many facilities that serve in-

voluntary clients offer a relatively narrow rangeof services that are not tailored to individualswith severe disorders. We hope to explore thesequestions in future work.

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