Matching substance abuse aftercare treatments to
Thomas G. Brown
*, Peter Seraganian
, Jacques Tremblay
Applied Alcohol and Drug Addiction Research Unit, Concordia University, Montreal, Canada
Pavillon Foster Substance Abuse Treatment Center, St. Philippe de LaPrairie, Canada
Addiction Research Program, Douglas Hospital Research Center, Verdun, Canada
Addiction Research Foundation, Toronto, Canada
This study investigated matching client attributes to different aftercare treatments. A naturalistic
sample of adults entering substance abuse treatment was randomized into either Structured Relapse
Prevention (RP, n= 61) or a 12-Step Facilitation (TSF, n= 72) aftercare program. Four patient
attributes were matched to treatment: age, gender, substance abuse profile, and psychological status.
Substance use outcomes were assessed 3 and 6 months posttreatment. At 6 months, four significant
matches were uncovered. Females and individuals with a multiple substance abuse profile reported
better alcohol outcomes with TSF aftercare than their cohorts exposed to RP aftercare. Individuals
with high psychological distress at treatment entry were able to maintain longer periods of
posttreatment abstinence with TSF aftercare compared to their cohorts exposed to RP. Inversely, RP
was found to maintain abstinence significantly longer for individuals reporting low distress
compared to those with high distress. Finally, better outcomes were achieved when random
assignment to aftercare was consistent with participant preference. Overall, an Alcoholics
Anonymous approach to aftercare appears to provide the most favorable substance use outcomes
for most groups of substance abusers. RP may be most suitable for clients whose psychological
distress is low, especially where maintenance of abstinence is targeted. Where choice in aftercare
0306-4603/02/$ – see front matter D2002 Elsevier Science Ltd. All rights reserved.
PII: S 0 3 0 6 - 4 6 0 3 ( 0 1 ) 0 0 195-2
Support for this study was provided by a grant from the National Health Research and Development
Program (NHRDP) of Health, Canada.
* Corresponding author. Addiction Research Program, Douglas Hospital Research Center, 6875 Boulevard
LaSalle, Verdun, Quebec, Canada H4H 1R3. Tel.: +1-514-761-6131; fax: +1-514-888-4064.
E-mail address: firstname.lastname@example.org (T.G. Brown).
Addictive Behaviors 27 (2002) 585 – 604
program is possible, matching client preference with type of aftercare program can improve outcome.
D2002 Elsevier Science Ltd. All rights reserved.
Keywords: Substance abuse; Treatment; Aftercare; Matching
Aftercare is recognized as an integral component of substance abuse treatment. In practice,
however, aftercare is often an appendage to the more structured, intensive phases of the
treatment program (Graham, Annis, Brett, & Venesoen, 1996). Treatment in aftercare
typically involves one or more sessions per week over several weeks or months following
a more intensive phase of either in- or outpatient care. That this facet of treatment would be
less well developed than the intense stage of treatment is a shortcoming. Although the
stabilization of clients’ substance abuse during the intensive phase of their program is reliably
achieved (Brown, Seraganian, & Tremblay, 1994), maintenance of such treatment gains in the
months after intensive treatment ends is less certain (Brown, Seraganian, & Tremblay, 1993).
Such slippage is particularly evident for individuals addicted to both alcohol and drugs, a
profile that is now the predominant complaint confronted in North American substance abuse
settings (Miller & Bennett, 1996). Posttreatment relapse arguably involves an aggregate of
factors, many unrelated to treatment (Connors, Maisto, & Zywiak, 1996). Nevertheless,
attempting to increase the overall effectiveness of treatment by devoting more clinical and
research effort to aftercare in the recovery process seems warranted.
The commonly held view that aftercare attendance improves the posttreatment prognosis
of alcoholic patients arose from early research by Costello (1980) and Vannicelli (1978). With
some exceptions (e.g., Gilbert & Maxwell, 1987; Ito, Donovan, & Hall, 1988; McLatchie &
Lomp, 1988), most studies since then have found that aftercare attendance is associated with
better outcomes in alcoholics (O’Farrell, Choquette, & Cutter, 1998; Simpson, 1979;
Tonigan, Toscova, & Miller, 1996; Walker, Donovan, Kivlahan, & O’Leary, 1983).
Considerably less in known about: (1) the relative efficacy of different approaches to
aftercare for multiple substance abusers; and (2) how aftercare treatment offered to substance
abusers might be tailored to enhance their outcome. With little data to guide refinements to
aftercare, it is not surprising that current clinical approaches to aftercare programming are less
developed than the initial phases of treatment.
A prevalent approach to aftercare delivery involves a non-specific or ‘broad-brush’
strategy (Graham et al., 1996; Hawkins & Catalano, 1985), with induction into Alcoholics
Anonymous (AA) representing an important objective. However, consistent with contem-
porary trends in psychotherapy research (Goldfried & Wolfe, 1998; Institute of Medicine,
1992), exploration has moved toward alternative intervention paradigms for the maintenance
of treatment gains. Relapse prevention (RP) programs seems conceptually and pragmatically
well suited to address the problem of posttreatment relapse. Typically, RP involves
cognitive–behavioral-based intervention approaches which target: (1) the assessment of the
environmental, interpersonal, and emotional situations linked to increased risk of relapse; and
T.G. Brown et al. / Addictive Behaviors 27 (2002) 585–604586
(2) increased self-efficacy through the utilization of improved and more varied coping skills.
The support for relapse-prevention-based aftercare programs in the treatment of alcohol
problems is generally positive. For example, when comparing RP to interpersonal process
aftercare, Ito et al. (1988) found no between-treatment differences on alcohol consumption,
but did uncover differential effects on other posttreatment measures including self-efficacy,
temptation, and behavioral coping. In individuals with alcohol dependency undergoing
behavioral marital therapy, those provided additional RP counseling used less alcohol, took
disulfiram (i.e., Antabuse) more reliably, and their wives experienced better marital
adjustment (O’Farrell et al., 1998). In a recent meta-analysis, RP was found to be generally
effective, with particular benefit for alcohol disorders (Irvin, Bowers, Dunn, & Wang, 1999).
Compared to cognitive–behavioral interventions, the effectiveness of AA attendance,
either as treatment or aftercare, remains poorly understood. The study of AA affiliation and
12-step programs has been criticized for lacking sound methodologies (Ouimette, Finney, &
Moos, 1997; Tonigan et al., 1996). However, one study of primary alcoholics and posttreat-
ment AA affiliation identified change elements that were predictive of outcome, including
self-efficacy, motivation, and active coping (Morgenstern, Labouvie, McCrady, Kahler, &
Frey, 1997). The investigators argued that these elements are not specific to AA, but are
generic to all effective interventions.
The literature on aftercare for drug abuse is more limited than for alcoholics. Nevertheless,
a number of recent studies have investigated the efficacy of RP and other aftercare treatments
for cocaine-dependent individuals as well as other groups of drug abusers. For example, in a
study in which cocaine-dependent participants were randomly assigned to different aftercare
treatments, McKay et al. (1997) compared RP to a standard group counseling procedure.
Counseling produced greater abstinence than individualized RP, while RP more effectively
reduced cocaine use in those who had difficulty in achieving abstinence during and shortly
after treatment. In a study of delivery modality (i.e., group vs. individual format), Graham et
al. (1996) found that how RP was provided had little impact on alcohol and drug outcomes. A
similar cognitive–behavioral aftercare approach was superior to AA-inspired 12-Step
Facilitation (TSF) in achieving abstinence in cocaine abusers (Maude-Griffin et al., 1998).
Finally, the meta-analysis cited above (Irvin et al., 1999) indicated that RP might have
particular benefits for polydrug abuse clients. With the exception of the study conducted by
Morgenstern et al. (1997), few well-designed studies have explored the efficacy of the 12-step
model in the treatment of naturalistic groups of multiple drug abusers.
During the past decade, the focus of substance abuse outcome research has shifted from
between-treatment comparisons to an attempt to identify advantageous patient–treatment
interactions (i.e., matching). Early matching studies were promising (Mattson, 1994).
However, Project MATCH (Project MATCH Research Group, 1997), the largest randomized,
multisite study of patient–treatment matching for alcoholism, failed to produce compelling
evidence in support of the 16 matching hypotheses explored. Since then, enthusiasm for
matching has waned somewhat. However, data from smaller-scale studies continue to support
the potential benefits of matching, especially in more naturalistic samples than the socially
stable alcoholics recruited for Project MATCH. For example, along with a main effect for the
superiority of RP with cocaine abusers compared to TSF, Maude-Griffin et al. (1998) found
T.G. Brown et al. / Addictive Behaviors 27 (2002) 585–604 587
that RP was differentially effective for cocaine abusers with a history of depression. Another
study explored potential interactions between counseling style and substance abuse severity
in a mixed group of substance abusers (Thorton, Gottheil, Weinstein, & Kerchsky, 1998). A
high-structure behaviorally oriented counseling style provided greater benefits to those
participants with the most severe substance abuse problems on a number of indices, including
counselors’ posttreatment ratings, the number of sessions attended, reduction in problem
severity, and clean urine specimens. Trends for reciprocal effects with low-structure
counseling and less severe abusers were also uncovered. In another naturalistic sample,
prospectively ‘matched’ patients stayed in treatment longer and had better consumption
outcomes at 6 months follow-up than mismatched clients (McLellan et al., 1997). Overall,
these findings, and the unabated clinical belief in the need to adapt treatment to patient
characteristics, support the continued investigation of patient– treatment matching in more
naturalistic populations of substance abusers.
The primary goal of this study was to explore the differential effectiveness of two aftercare
treatments based upon the individual characteristics of treated substance abusers. A guiding
philosophy was to assess patient–treatment matching under conditions comparable to those
in real-world substance abuse treatment. The importance we placed on external validity is
noteworthy as it is in contrast to the emphasis on internal validity adopted by the Project
MATCH Research Group (1993). Accordingly, instead of incorporating strict inclusion
criteria that permitted only stable alcoholics into the study, the minimal exclusion criteria
adopted here resulted in the recruitment of a more naturalistic sample of alcohol- and
multiple-drug-abusing patients. Despite the added methodological complexity this strategy
engenders, we hope it would increase the generalizability of our findings. In addition, as
group intervention remains the favored substance abuse treatment delivery modality (Graham
et al., 1996), all aftercare interventions were delivered in group format.
One aftercare treatment was based upon Structured Relapse Prevention developed at the
Clinical Institute of the Addiction Research Foundation (Annis & Davis, 1989). The selection
of Structured Relapse Prevention was predicated on its well-orchestrated manualized format,
extensive objective assessment of risky substance use situations, and support for its
effectiveness in previous studies. As well, it is increasingly promoted as a model for aftercare
and social reintegration programs in Canadian substance abuse treatment settings. The other
aftercare treatment was the manualized TSF program developed for Project MATCH (No-
winski, Baker, & Carroll, 1992) that promotes the principles of AA. The choice of an AA-
inspired aftercare program reflects the continuing reliance on AA and similar self-help
approaches as aftercare in North American substance abuse treatment. Moreover, over and
above anecdotal claims for the usefulness of AA-based interventions in the recovery process,
there is a growing interest in the empirical investigation of self-help processes of change.
Four patient characteristics were hypothesized to interact with the two experimental
aftercare treatments: (1) age, (2) gender, (3) drug abuse profile, and (4) psychiatric severity.
In previous work, age and gender have been seen to predict posttreatment functioning with
specific treatment approaches (Brown et al., 1993; Cronkite & Moos, 1984; Scott &
Anderson, 1990). Female alcoholics have higher prevalence rates of affective disorders and
engage in more frequent heavy drinking under situations involving negative emotional states
T.G. Brown et al. / Addictive Behaviors 27 (2002) 585–604588
(Annis, Sklar, & Moser, 1998). Accordingly, it was hypothesized that females would benefit
preferentially from a cognitive– behavioral approach such as RP since this intervention
would specifically address the psychosocial antecedents of substance use. In contrast, as AA
is considered a ‘made-for-men-by-men’ intervention (Coughey, Kelly, Cheney, & Klein,
1998; Galaif & Sussman, 1995), the AA-inspired TSF approach would benefit men more
Drug abuse profile has been associated with outcome from traditional AA-focussed
Minnesota model treatment, with a mixed alcohol and cocaine abuse profile predicting poorer
outcomes than ‘pure’ alcohol problems (Brown et al., 1993). Advantageous outcomes with RP
in the treatment of polydrug abuse as compared to single drug abuse (e.g., cocaine) have been
described, but not specifically with RP offered as an aftercare program (Irvin et al., 1999).
Given the added risk of multiple substance use, better results could be expected with treatment
that focuses on mastery of high-risk relapse situations compared to an approach that has
evolved primarily for alcoholism. Finally, psychiatric severity has been associated with poorer
treatment prognosis (McLellan, Woody, Luborsky, O’Brien, & Druley, 1983). Some strands of
evidence suggest that TSF may be most appropriate for individuals who are not grappling with
significant psychological disturbance (Project MATCH Research Group, 1997). Thus, we
hypothesized that this trend would extend to a naturalistic population of substance abusers.
Participant self-selection is of growing interest in terms of its potential impact on the
generalizability of outcome data and its role in treatment success (DeLeon, 1998; Maude-
Griffin, Hohenstein, Humfleet, Reilly, Tusel, & Hall; Rychtarik, McGillicuddy, Coonors, &
Whitney, 1998). When potential participants decide not to participate in randomized clinical
trials, a loss in the generalizability of the findings and bias in the randomization process may
result. In addition, randomization tends to neglect the potential contribution of client pre-
ference to treatment success. Additional data were gathered to address these issues. First,
baseline and outcome data were collected on patients who refused to participate in either of the
experimental aftercare programs but who agreed to undergo assessment identical to that of full
participators. Effectively, these participants had self-selected themselves to the ‘usual care’
aftercare program provided by the study’s treatment sites. Though neither a true control group
obtained through randomization nor a sample consisting of all those who self-selected out of
the experimental protocol, data from this ‘reference group’ could contribute to an appraisal of
the generalizability of the findings. Second, prior to randomization, participants were queried
as to which aftercare program they would prefer. While treatment preference did not influence
the randomization process, these data could clarify whether client preference might influence
either attrition from the experimental protocol or the effectiveness of the treatments.
Male and female adult patients 18 years and over entering treatment for alcohol and drug
abuse at three Montreal region residential treatment centers were approached to participate in
T.G. Brown et al. / Addictive Behaviors 27 (2002) 585–604 589
the study upon their entry into treatment. Patients who provided informed consent were
eligible for study participation if they met the following inclusion criteria: (1) met DSM III-R
diagnostic criteria for psychoactive substance abuse/dependence as classified by a structured
clinical interview (SCID; see below); (2) did not exhibit severe organic brain syndrome or
severe psychosis; (3) could read and write in either French or English at least at a grade 5
level; and (4) resided within a 50-km radius of Montreal.
Participants were recruited from among patients at three treatment centers in the
Montreal region: (1) Pavillon Foster, a publicly funded 20-bed inpatient and 12-place
outpatient facility, which serves English-speaking patients from across Quebec; (2)
Maison Jean Lapointe, a private, non-profit 42-bed inpatient facility, which serves
Francophone patients in central Montreal; and (3) Le Virage, a provincially funded
30-place in- and outpatient rehabilitation facility, which serves Francophone patients coming
from Montreal’s suburban and rural south shore region. The three treatment centers share
certain attributes: a multimodal treatment orientation which stresses heightened awareness
of the negative impact of substance abuse, personal autonomy from dependence on
psychoactive substances, improved social adjustment and coping, and ongoing involvement
2.3. Aftercare treatments
2.3.1. Structured Relapse Prevention
The RP aftercare program (Annis & Davis, 1989) involved 10 weekly sessions of a
manualized treatment process with three distinct counseling stages: (1) administration of
questionnaires to assess high-risk situations for substance usage; (2) initial counseling
procedures, which focus on change initiation; and (3) modified counseling procedures, which
focus upon maintenance of change. During the initial counseling phase, an individualized
treatment plan is developed for each patient, which draws upon the client’s report of specific
triggers for drinking/drug use coupled with use patterns and consequences. As well, the focus
is on a directive role by the counselor in helping clients identify, anticipate, and avoid drug/
alcohol use risk. Later, less reliance on the therapist and more use of a varied repertoire of
coping strategies are sought.
The comprehensive 164-page TSF manual developed by the Project MATCH Research
Group (Nowinski et al., 1992) formed the basis for AA-based aftercare counseling. This
aftercare approach is grounded in the conception of alcoholism as a disease of the spirit,
mind, and body. Although all 12 steps are explored in the facilitation program, emphasis is
placed on steps 1 through 3, namely, powerlessness over alcohol, belief in a higher power,
and carrying out a moral inventory. Counseling sessions were structured following a similar
format each week, which included symptom review, discussion of AA involvement, the
T.G. Brown et al. / Addictive Behaviors 27 (2002) 585–604590
introduction and explication of the week’s themes. Reading assignments from the AA
literature complemented material discussed during weekly sessions.
Two main features were common to both of the experimental aftercare programs. First,
both interventions were provided in a 10-week, 90-min closed-group format, with groups
comprised of four to eight participants. Second, highly trained and regularly supervised
counselors delivered both interventions. Recovering AA members delivered the TSF
condition while PhD-level graduate students enrolled in a clinical psychology program
provided RP. Counselors in both conditions were trained by the authors of the respective
treatments (H.A., S.B.) and subsequently met monthly with a highly skilled treatment
coordinator to minimize drift from the manualized treatment protocols.
2.4. Tests and measures
Sociodemographic and other pertinent information (i.e., age, education, marital status,
ethnic origin, employment status, religion, referral source, etc.) was gathered via specific
portions of the Addiction Severity Index (ASI) described below.
2.4.2. Alcohol and drug usage
Time Line Follow-Back (TLFB) (Sobell, Maisto, Sobell, & Cooper, 1979) presents
patients with a calendar (essentially an aid to recall) and asks them to recall instances of
drinking or substance use on a daily basis over the past 90 days. This technique has been
found to minimize the tendency to underreport substance use (Babor, Brown, & Del Boca,
1990). Days of substance use and days of abstinence prior to first use were dependent
variables drawn from this instrument.
2.4.3. Substance abuse and psychosocial functioning
The ASI is a semi-structured interview protocol that has been found valid and reliable in
assessing a spectrum of addiction-related behaviors and consequences in both evaluative
and matching investigations (McLellan, Luborsky, Woody, & O’Brien, 1980; McLellan
et al., 1983). In addition to the two composite scores specifically related to the severity of
alcohol and drug use over the past 30 days, the ASI provides objective indices of func-
tioning on five dimensions of psychosocial functioning, including social and familial,
employment, legal, physical, and psychiatric severity. It has been adopted as a standard
information-gathering device in addiction treatment contexts in many states and provinces
of the US and Canada.
2.4.4. Diagnostic classification
Diagnoses of substance use were made via the Structured Clinical Diagnostic Interview for
the DSM III-R (SCID-NP) (Spitzer, Williams, Gibbon, & First, 1990). This structured
interview protocol consists of items that are keyed to the major psychiatric diagnostic features
contained in the Diagnostic and Statistical Manual of Mental Disorders, Third Edition,
Revised (American Psychiatric Association, 1987). The structured interview protocol has
T.G. Brown et al. / Addictive Behaviors 27 (2002) 585–604 591
been well standardized (Spitzer et al., 1990), and yields data that are both valid and reliable if
subjects answer candidly. For this study, only those sections that provide diagnostic
classification of substance abuse or dependence disorders were administered.
2.4.5. Psychological status
Psychological status was assessed employing the Symptoms Checklist-90 (SCL-90)
(Derogatis, Lipman, & Covi, 1973). The SCL-90 has been frequently employed as a
simple, yet effective, screening device for detecting psychological disturbance in previous
treatment studies of alcohol and drug abusers (Brown et al., 1994; McLellan et al., 1983).
This self-administered paper-and-pencil instrument provides nine clinical scales as well as
three general indices of symptom severity. The Global Severity Index (GSI), an overall
measure of psychological adjustment, was used as an independent variable in the analysis. In
order to assess the degree of psychopathic tendencies, the Socialization Scale of California
Personality Inventory (CPI-So; Megargee, 1972) was employed. These scores were
employed in the urn randomization protocol to reduce the possibility of between-group
imbalance on this attribute.
Within 2 days following admission into intensive treatment, the patient was approached by
a designated member of the treatment staff, informed of the existence of the research project,
asked to read, and, if willing, to sign an informed consent attesting to his/her willingness to
accept randomization. However, those patients who were unwilling to undergo random-
ization, but were willing to participate to a reduced degree, were also recruited at this time.
Such patients consented to undergo the four assessment sessions, and were permitted, as were
all participants in the study, to attend the usual aftercare programs offered by their treatment
center. These participants were designated as Group Usual Care (UC).
Besides a brief description of the study, including the two levels of participation, the
informed consent contained several items: (a) a statement that reimbursement of CAN$10 and
CAN$20 was provided for completion of the postaftercare and 6-month follow-up assessment
sessions, respectively; (b) assertions that all data gathered were confidential and in the hands
of researchers who were independent of the treatment teams at the three centers; and (c) a
commitment to provide debriefing on their own individual data as well as a summary of
overall group findings. If the patient was in withdrawal or had used psychoactive substances
in the week before entering treatment, study participation was delayed for up to a week to
reduce data contamination from the effects of withdrawal.
Following completion of intensive treatment, patients who consented to full study
participation were randomly assigned to participate in one of the two aftercare treatments:
AA or RP. Randomization was done separately for each of the three sites. A computer-
assisted urn randomization procedure (Project MATCH Research Group, 1993) was utilized
in order to maximize the likelihood that the composition of the two groups was balanced with
respect to variables that could potentially influence outcome and that were of interest in
matching. These included: (1) age, (2) gender, (3) attendance in in- or outpatient treatment
T.G. Brown et al. / Addictive Behaviors 27 (2002) 585–604592
prior to their attendance in aftercare, (4) psychopathic tendencies, (5) cognitive functioning,
(6) psychological distress, and (7) whether primarily alcohol, drug, or multiply addicted.
Multidimensional assessment of participants occurred at four points in time: (1) intake into
intensive treatment; (2) following completion of intensive treatment; (3) following the 10-
session aftercare program; and (4) 6 months following completion of intensive treatment.
Each of these assessment sessions took about 2 h to complete. Finally,each participant was
asked on their Informed Consent Form to nominate two individuals who could be contacted
by the investigators to corroborate their substance use in follow-up assessments.
2.6. Analytic strategy
Three indices of substance use were the dependent variables in all matching analyses: (1)
number of days of alcohol and drug use in the prior 90 days as measured by the TLFB; (2)
days prior to first use of any alcohol and/or drugs after formal termination of the participant’s
aftercare program, also measured by the TLFB; and (3) alcohol and drug use severity as
measured by the Alcohol and Drug composite scores on the ASI. The following interactions
between aftercare treatment and patient attributes on treatment entry were tested: (1) age, (2)
gender, (3) psychological distress as measured by the GSI of the SCL-90, and (4) drug use
pattern (i.e., whether predominantly alcohol or multiple drugs) based upon consumption
patterns in the 90 days prior to the initial interview on treatment admission.
Patient–treatment matching was explored using hierarchical linear regression. For each
analysis, the pretreatment value of the outcome variable was entered, followed by a dummy
variable representing treatment type, and then the initial patient variable. Finally, an
interaction term (i.e., the initial patient characteristic treatment type) was entered to
determine whether the addition of this factor would add significantly to the predictability
of any of the dependent variables.
3.1. Characteristics of the sample
A total of 241 participants were randomized into the two experimental groups through the
urn procedure. Subsequently, 154 participants were successfully followed up with Group AA
consisting of 72 participants and Group RP of 61 participants. The 21 participants who
refused randomization, but agreed to be followed up, made up Group UC. Table 1 depicts
the means, standard deviations, and relevant proportions for the sample on sociodemo-
graphic, psychosocial functioning, and substance abuse measures. Of note is the distribution
of substance abuse diagnosis, with the majority of participants presenting with multiple
substance use diagnoses. In addition, this sample was mostly single, Caucasian, grappling
with long periods of unemployment and employment difficulties. Finally, the gender
distribution indicated the typical under-representation of women in substance abuse
T.G. Brown et al. / Addictive Behaviors 27 (2002) 585–604 593
3.1.1. Refusal to participate and attrition
Forty-seven individuals who were approached refused to participate. The main reasons
included lack of interest (27.7%), the aftercare sites were too far (25.5%), and lack of time or
inconvenience (21.2%). Statistical comparisons between these individuals and the final
sample on age, marital status, employment status, ethnic background, and gender failed to
yield any significant differences.
Eighty-seven individuals were lost from follow-up after randomization. Those lost to
attrition were significantly younger (M= 35.8, S.D. = 9.0 vs. M= 38.3, S.D. = 9.5), less
educated (M= 11.4, S.D. = 3.0 vs. M= 12.2, S.D. = 2.7), had less time at their current job
(M= 6.9, S.D. = 5.7 vs. M= 9.2, S.D. = 8.2), had poorer employment functioning on the ASI
Sociodemographic, substance use, and psychosocial functioning of study participants (N= 133) randomized into
Age 38.0 9.3
Percent female (n) 32.2 (43)
Percent Caucasian (n) 92.5 (123)
Education 12.3 2.7
Married or cohabitating 36.8 (39)
Separated, divorced 24.8 (33)
Never married 38.4 (61)
Years at current job 8.4 7.6
Days worked prior to 30 days 5.7 8.5
Months worked in past 6 months 2.8 2.6
Days in treatment 24.3 7.3
Percent alcohol dependence (n) 28.6 (38)
Percent ETOH + drug dependence (n) 71.4 (95)
Abstinent days in the last 90 days 44.3 23.9
Years of alcohol use 11.0 8.5
Years of cocaine use 3.0 4.2
Years of cannabis use 5.6 7.6
ASI composite scores
Medical 0.13 0.14
Employment 0.57 0.30
Legal 0.10 0.17
Alcohol 0.32 0.22
Drug 0.15 0.09
Social/Family 0.28 0.20
Psychiatric 0.26 0.20
SCL-90 GSI (t) 68.4 9.4
T.G. Brown et al. / Addictive Behaviors 27 (2002) 585–604594
Employment Scale (M= 0.64, S.D. = 0.30 vs. M= 0.55, S.D. = 0.30), reported more previous
treatments for alcohol problems (M= 0.93, S.D. = 2.7 vs. M= 0.34, S.D. = 0.72), and had
spent less money on drugs in the previous 30 days (M= 156.7, S.D. = 437.4 vs. M= 417.7,
S.D. = 1458.3) than those retained in the study ( P< .05). Intake and 6-month follow-up data
were also compared. There were no between-group differences on any of the intake variables.
However, at 6 months follow-up, participants who refused randomization had significantly
lower mean Drug (M= 0.02, S.D. = 0.04 vs. M= 0.06, S.D. = 0.08, t(61.2) = 4.2, P< .001) and
Psychiatric Severity (M= 0.08, S.D. = 0.12 vs. M= 0.21, S.D. = 0.21, t(44.5) = 4.2, P< 0.001)
composite scores on the ASI.
3.2. Comparability between randomized groups
Initial comparisons between Groups AA and RP to assess the equivalence of the
experimental groups were undertaken on psychosocial indices, the variables used in the
urn randomization procedure, and the number of aftercare sessions attended. The ttests
revealed that only mean age differed significantly between the two groups [t(131) = 2.3,
P< .05], with Group AA being significantly younger (M= 36.3, S.D. = 7.9) than Group RP
(M= 40.0, S.D. = 10.4). No other differences emerged. Thus, in subsequent matching
analyses, age was forced as the first step of the hierarchical regression to account for this
between-group discrepancy. The mean number of experimenter-offered aftercare sessions
attended was 4.6 (S.D. = 2.3) overall, with a mean of 4.4 (S.D. = 4.1) for participants in Group
AA and 4.8 (S.D. = 3.7) for those in Group RP. Overall, the minimum exclusion strategy
adopted for this study resulted in a sample of participants that appeared fairly representative
of the population seeking intervention at public substance abuse treatment settings.
3.3. Determination of substance use profile
The substance use profile of the participants, involving predominantly alcohol, drug, or
multiple drug use, was determined by K-cluster analyses. The number of days of alcohol use,
drug use, and multiple substance use in the previous 90 days were used to classify the three
groups. As desired, this classification protocol yielded three groups characterized by: (1)
alcohol use (alcohol alone, M= 34.2 days, S.D. = 27.6; drugs alone, M= 0.60 days, S.D. = 2.6;
both, M= 2.4 days, S.D. = 5.1); (2) drug use (alcohol alone, M= 1.3 days, S.D. = 3.6; drugs
alone, M= 45.3 days, S.D. = 17.3; both, M= 4.4 days, S.D. = 7.9); and (3) multiple substance
use (alcohol only, M= 4.6 days, S.D. = 8.3; drugs only, M= 2.5 days, S.D. = 5.3; both,
M= 47.8 days, S.D. = 16.0). The validity of this classification was corroborated by one-
way ANOVA with Bonferroni corrected pairwise comparisons between these groups using
the ASI Alcohol and Drug composite scores. On the Alcohol scale, significant group
differences [ F(2,129) = 27.7, P< .001] were found between the drug group (M=0.13,
S.D. = 0.14) and both the alcohol (M= 0.37, S.D. = 0.20) and multiple substance groups
(M= 0.44, S.D. = 0.21). On the Drug scale, significant group differences were found between
the alcohol group (M= 0.10, S.D. = 0.07) and the drug (M= 0.20, S.D. = 0.07) and multiple
substance (M= 0.20, S.D. = 0.09) groups.
T.G. Brown et al. / Addictive Behaviors 27 (2002) 585–604 595
Preliminary analyses of short-term outcomes assessed immediately after treatment or
termination of the 10-week aftercare interventions failed to reveal any significant main or
matching effects. A number of main and interaction effects contributed significantly to the
prediction of the three substance abuse outcome measures at 6 months follow-up.
3.4. Substance abuse profile
A primary hypothesis of this study conjectured that RP would provide better outcomes for
those who presented with a multiple substance abuse profile than TSF. A significant treatment
by substance abuse profile was found when both Alcohol and Drug use Severity on the ASI
were considered. A square-root transformation was performed on the ASI Alcohol and Drug
composite scores to better meet statistical assumptions. With respect to alcohol use outcomes,
the overall regression was significant [ F(7,132) = 3.60, P< .001, R
=.17], as was baseline ASI
Alcohol score [ F(1,132) = 8.26, P< .01]. The interaction term of Substance Use Profile -
Aftercare Assignment was significant [ F(2,132) = 3.34, P= .035, R
= .05] when entered as
the last step in the stepwise regression. Posthoc analysis indicated that for those who presented
with a multiple substance abuse profile, assignment to TSF was associated with significantly
better alcohol outcomes than assignment to RP (M= 0.16, S.D. = 0.19 vs. M= 0.31, S.D. = 0.23).
This interaction is graphically depicted in Fig. 1 where higher scores indicate greater severity.
The means and standard errors on the dependent variables of those participants who refused
randomization (Group Usual Care) are provided in Figs. 1– 4 for comparative reference.
For drug use outcomes, a similar pattern emerged. The overall regression model was
significant [ F(7,132) = 14.67, P< .001, R
=.453]. Age [ F(1,132) = 9.68, P< .005] and initial
ASI Drug composite score [ F(1,132) = 33.27, P< .001] also contributed significantly to the
prediction of 6-month drug severity. The interaction term Substance Use Profile Aftercare
Fig. 1. Interaction effects between substance use profile and aftercare assignment on ASI Alcohol compo-
T.G. Brown et al. / Addictive Behaviors 27 (2002) 585–604596
Assignment was also significant as the last step of the regression [ F(2,132) = 7.04, P< .001,
=.10]. Posthoc analysis revealed that for individuals presenting with a multiple substance
abuse profile, assignment to TSF resulted in better overall drug use outcome than assignment
to RP (M= 0.05, S.D. = 0.06 vs. M= 0.10, S.D. = 0.09). This relationship is depicted in Fig. 2.
The overall regression model was significant [ F(5,132) = 6.07, P< .001, R
=.19] as was
the addition of age [ F(1,132) = 4.76, P< .05], initial ASI Alcohol score [ F(1,132) = 18.28,
P< .001], and the main effect for aftercare assignment [ F(1,132) = 5.65, P< .05]. The
Fig. 3. Interaction effects between gender and aftercare assignment on the ASI Alcohol composite score.
Fig. 2. Interaction effects between substance use profile and aftercare assignment on ASI Drug composite scores.
T.G. Brown et al. / Addictive Behaviors 27 (2002) 585–604 597
interaction term Gender Aftercare Assignment contributed significantly to the last step of
the regression [ F(1,132) = 9.02, P< .005, R
=.07]. For women, assignment to TSF was
associated with significantly reduced alcohol severity compared to assignment to RP aftercare
(M= 0.11, S.D. = 0.16 vs. M= 0.27, S.D. = 0.22). This relationship is depicted in Fig. 3.
3.6. Psychological distress
A final significant interaction was found between psychological distress and aftercare
programs with respect to the days of abstinence prior to the first use of any psychoactive
substance. The overall regression was significant [ F(4,132) = 4.36, P< .005, R
=.12], as was
the contribution of age [ F(1,132) = 5.99, P< .05]. Psychological distress was categorized
as High or Low with a cut-off at the 50th percentile of the range of scores (i.e. GSI,
Tscore = 67.5). The Psychological Distress Aftercare Assignment interaction was significant
[F(1,132) = 6.47, P< .05, R
=.05]. Fig. 4 depicts this interaction. Posthoc analysis revealed
that for individuals with high levels of overall psychological distress at intake, assignment to
TSF prolonged posttreatment abstinence as compared to assignment to RP. Moreover,
individuals expressing higher overall psychological distress had fewer abstinent days posttreat-
ment compared to those expressing overall lower distress. It is noteworthy that psychological
disturbance predicted both ASI Alcohol abuse severity [ F(1,132) = 5.08, P< .05, R
= .038] and
Drug abuse severity [ F(1,132) = 10.83, P< .001, R
3.7. Client preference for aftercare program
Of those participants expressing a preference (n= 107), 51 participants were randomized
into an aftercare program that was inconsistent with their preference, while 56 were
Fig. 4. Interaction effects between level of global psychological distress as measured by the SCL-90 and aftercare
assignment on the number of days until first use.
T.G. Brown et al. / Addictive Behaviors 27 (2002) 585–604598
randomized into the aftercare program they preferred. ASI Drug status at follow-up was
significantly different between groups [ F(1,106) = 4.2, P< .05, R
=.04] after accounting for
pretreatment differences. Those participants whose aftercare group was consistent with their
preference were functioning better with respect to drug use at 6 months follow-up (M= 0.04,
S.D. = 0.07) compared to the participants whose aftercare group was inconsistent with their
preference (M= 0.08, S.D. = 0.08). A significant difference was also discerned in the number
of days of substance use in the previous 90 days [ F(1,106) = 5.2, P< .05, R
whose preference was consistent with their assignment reported fewer days of use (M= 7.6,
S.D. = 13.6) compared to those whose preferences were not (M= 15.3, S.D. = 26.6).
3.8. Corroboration of self-report
Seventy-nine participants reported total abstinence. Corroboration for 35 of these individ-
uals was obtained from participant-designated informants. In only two cases out of 35 (5.6%)
did informants contradict the participant’s claim of abstinence.
The present study sought to clarify several matching hypotheses between different
aftercare treatment modalities and client characteristics in a naturalistic clinical substance
abuse population. Four matches that contributed significantly to 6-month substance use
outcome measures emerged. The identification of several significant patient– treatment
matches contrasts with the relative absence of support for matching from a recent large-
scale, highly controlled clinical trial (Project MATCH Research Group, 1997). This under-
lines the value of employing smaller, more naturalistic, and heterogeneous populations of
substance abusers to study potential Client Treatment interactions.
The importance of psychological disturbance on the outcome of substance abusers in this
study corroborates previous observations of generally poorer posttreatment outcomes with
high psychiatric disturbance. Differential treatment effects with RP in individuals with higher
levels of psychiatric disturbance were also noted, which represents a longstanding finding
(McLellan et al., 1983). Moreover, RP was less effective in maintaining posttreatment
abstinence in individuals with high psychological disturbance than for those with low levels
of disturbance. This finding is at odds with other matching studies that have found better
outcomes with RP in participants showing more severe psychopathology compared to
alternative approaches (Carroll, Rousaville, & Gawin, 1991; Kadden, Getter, Cooney, & Litt
1989). Both treatment modality and sample differences may have contributed to this
inconsistency, since these studies studied primarily alcohol- or cocaine-dependent individuals
exposed to different intensive phase treatments.
The naturalistic sample recruited in this study made possible the exploration of
interactions between substance use patterns and aftercare treatment. Substance use pro-
file was found to interact with aftercare treatment on both alcohol and drug severity
outcomes at 6 months follow-up. TSF assignment was associated with better outcomes
T.G. Brown et al. / Addictive Behaviors 27 (2002) 585–604 599
compared to RP for those participants presenting with a pretreatment profile of multiple
alcohol and drug use. This interaction was not in the hypothesized direction, since we
had conjectured that RP would better address the high risk for relapse typically seen in
multiple substance abusers. Only a few studies have looked at matching effects between
aftercare treatment and substance use patterns. One study found that individuals with
more severe substance abuse profiles fared better in more structured counseling situations
(Thorton et al., 1998). Based upon these findings, it could be posited that the added
complexity of dealing with several substances simultaneously is better served by a more
structured and didactic approach to aftercare. Thus, TSF aftercare may be more effective
in reducing overall alcohol and drug abuse severity in that it stresses complete ab-
stinence from all substances and relatively straightforward avoidance strategies for all
The present findings also raise questions about the appropriateness of a RP aftercare
approach for women. Assignment to TSF aftercare was more advantageous for women than
assignment to RP aftercare in terms of alcohol use severity. In males, no differences on any
of the outcome variables were found due to aftercare assignment. Some investigators have
suggested that a cognitive–behavioral approach may be better adapted to the specific needs
of women than AA-type interventions (Coughey et al., 1998; McKay, Rutherford, Cacciola,
Kabasakalian-McKay, & Alterman, 1996). Many clinical programs provide specialized
programs for women in the hope that they will better meet their specific needs. However,
the role of gender in the differential efficacy of intensive interventions is both uncertain
and understudied (Annis et al., 1998; McKay et al., 1996; Morgenstern et al., 1997;
Toneatto, Sobell, & Sobell, 1992). Additional study on gender-specific treatment inter-
actions is warranted.
A final outcome was that client preference in aftercare influenced posttreatment function-
ing. Random assignment that was consistent with participant preference was found to be
associated with better substance abuse outcomes at 6 months follow-up compared to
inconsistent assignment. Client preference for treatment is a potentially important, but often
neglected, factor in both the conduct of randomized clinical trials (O
¨jehagen & Berglund,
1992) and our understanding of the basis of successful treatment (DeLeon, 1998). This
finding corroborates the importance of self-selection in effective substance abuse treatment,
and cautions against disregard or statistical attenuation of this client factor in substance abuse
4.1. Clinical implications
This study sought to identify beneficial matches between aftercare programs and client
attributes in a naturalistic sample attending substance abuse treatment. Based upon the present
data, the benefits of TSF aftercare appear quite generalized across the client attributes
investigated here and are equal to or better than those seen with RP. Where little choice is
possible in providing aftercare interventions, the adoption of a well-supervised and structured
TSF-inspired aftercare program seems a reasonable strategy for most clients. In contrast, the
outcome from RP aftercare is more specific. Thus, care in prescribing RP aftercare, especially
T.G. Brown et al. / Addictive Behaviors 27 (2002) 585–604600
to individuals grappling with high psychological distress, multiple substance abuse, and who
are female, seems warranted. When choice in aftercare program is possible, however, an
aftercare program that is consistent with client preference can contribute to the overall
efficacy of aftercare intervention, regardless of the modality of treatment.
4.1.1. Limitations of the present study
This study has several strengths, including the recruitment of a naturalistic sample,
randomization, and an analysis based upon ‘intent-to-treat’ assignment to groups. Thus, it
is likely that the findings are robust with respect to the importance of treatment effects and
have clinical significance. At the same time, this study possesses some limitations. The
naturalistic nature of substance abuse complaints may make direct comparisons between
studies problematic. In addition, there was a primary reliance on self-report of substance use.
Corroboration was available in some cases, and revealed little conflict between the claims of
abstinence of the participant and the corroborator. Corroboration was not available for
roughly half of the subjects. Though other measures were taken to optimize the validity of
self-report, such as assurances of confidentiality and interviews conducted by researcher
personnel not involved in the participants’ treatment, the validity of the self-reports cannot be
As in most outcome studies in substance abuse, attrition was a significant occurrence
throughout this study. Measures were taken to appraise the impact of attrition on the
generalizability of the findings. With respect to refusal to participate, the available intake
data did not reveal substantial differences, although the meaning of this loss to the outcome
data is uncertain. Efforts were made to collect outcome data from those individuals who,
under other circumstances, might have been lost (i.e., those individuals who refused
randomization but accepted to be followed up). Qualitative comparisons on the patient-
treatment interactions were provided between those participants who accepted and those who
refused randomization. Moreover, quantitative analyses revealed that the drug and psycho-
logical outcomes of individuals who refused randomization were significantly better at
6 months than those who accepted. While not explicitly resolving the quandary of participant
attrition, these data hint at what impact the loss of similar ‘hard-to-recruit’ clients might have
on the data (Howard, Krause, & Orlinsky, 1986).
American Psychiatric Association (1987). Diagnostic and statistical manual of mental disorders (DSM-III-R).
Washington, DC: American Psychiatric Association Press.
Annis, H. M., & Davis, C. S. (1989). Relapse prevention. In R. K. Hester, & W. R. Miller (Eds.), Handbook of
alcoholism treatment approaches (pp. 170 – 182). New York: Pergamon.
Annis, H. M., Sklar, S. M., & Moser, A. E. (1998). Gender in relation to relapse crisis situations, coping, and
outcome among treated alcoholics. Addictive Behaviors,23 (1), 127 – 131.
Babor, T. F., Brown, J., & Del Boca, F. K. (1990). Validity of self-reports in applied research on addictive
behaviors: fact or fiction? Behavioral Assessment,12 (1), 5– 31.
Brown, T. G., Seraganian, P., & Tremblay, J. (1993). Alcohol and cocaine abusers 6 months after traditional
T.G. Brown et al. / Addictive Behaviors 27 (2002) 585–604 601
treatment: do they fare as well as problem drinkers? Journal of Substance Abuse Treatment,10 (6),
Brown, T. G., Seraganian, P., & Tremblay, J. (1994). Alcoholics also dependent on cocaine in treatment: do they
differ from ‘‘pure’’ alcoholics? Addictive Behaviors,19 (1), 105– 112.
Carroll, K. M., Rousaville, B. J., & Gawin, F. H. (1991). A comparative trial of psychotherapies for ambulatory
cocaine abusers: relapse prevention and interpersonal psychotherapy. American Journal of Drug and Alcohol
Abuse,17, 229– 247.
Connors, G. J., Maisto, S. A., & Zywiak, W. H. (1996). Section IIB. Extensions of relapse predictors beyond high-
risk situations: understanding relapse in the broader context of posttreatment functioning. Addiction,91,
S173 – S189 (Supplement).
Costello, R. M. (1980). Alcoholism aftercare and outcome: cross-lagged and path analyses. British Journal of
Addiction,75 (1), 49 – 53.
Coughey, K., Kelly, F., Cheney, R., & Klein, G. (1998). Retention in an aftercare program for recovering women.
Substance Use and Misuse,33 (4), 917 – 933.
Cronkite, R. C., & Moos, R. H. (1984). Sex and marital status in relation to the treatment and outcome of alcoholic
patients. Sex Roles,11 (1– 2), 93 – 112.
DeLeon, G. (1998). Commentary: reconsidering the self-selection factor in addiction treatment research. Psychol-
ogy of Addictive Behaviors,12 (1), 71 – 77.
Derogatis, L. R., Lipman, R. S., & Covi, L. (1973). The SCL-90: an outpatient psychiatric rating scale. Psycho-
pharmacological Bulletin,9(1), 13– 28.
Galaif, E. R., & Sussman, S. (1995). For whom does Alcoholics Anonymous work? International Journal of the
Addictions,30 (2), 161 – 184.
Gilbert, F. S., & Maxwell, P. J. (1987). Predicting attendance at follow-up evaluations in alcoholism treatment
outcome research. Journal of Studies on Alcohol,48 (6), 569 – 573.
Goldfried, M. R., & Wolfe, B. E. (1998). Toward a more clinically valid approach to therapy research. Journal of
Consulting and Clinical Psychology,66 (1), 143– 150.
Graham, K., Annis, H. M., Brett, P. J., & Venesoen, P. (1996). A controlled field trial of group versus individual
cognitive– behavioral training for relapse prevention. Addiction,91 (8), 1127 – 1139.
Hawkins, J. D., & Catalano, R. F. (1985). Aftercare in drug abuse treatment. International Journal of the
Addictions,20 (6 – 7), 917 – 945.
Howard, K. I., Krause, M. S., & Orlinsky, D. E. (1986). The attribution dilemma: toward a new strategy for
psychotherapy research. Journal of Consulting and Clinical Psychology,54 (1), 106–110.
Institute of Medicine. (1992). Prevention and treatment of alcohol-related problems: research opportunities.
Journal of Studies on Alcohol,53 (1), 5– 16.
Irvin, J. E., Bowers, C. A., Dunn, M. E., & Wang, M. C. (1999). Efficacy of relapse prevention: a meta-analytic
review. Journal of Consulting and Clinical Psychology,67 (4), 563– 570.
Ito, J. R., Donovan, D. M., & Hall, J. J. (1988). Relapse prevention in alcohol aftercare: effects on drinking
outcome, change process, and aftercare attendance. British Journal of Addiction,83 (2), 171– 181.
Kadden, R. M., Getter, H., Cooney, N. L., & Litt, M. D. (1989). Matching alcoholics to coping skills or
interactional therapies: posttreatment results. Journal of Consulting and Clinical Psychology,57 (6),
Mattson, M. E. (1994). Patient – treatment matching: rational and results. Alcohol Health and Research World,18
(4), 287– 295.
Maude-Griffin, P. M., Hohenstein, J. M., Humfleet, G. L., Reilly, P. M., Tusel, D. J., & Hall, S. M. (1998).
Superior efficacy of cognitive – behavioral therapy for urban crack cocaine abusers: main and matching effects.
Journal of Consulting and Clinical Psychology,66 (5), 832– 837.
McKay, J. R., Alterman, A. I., Cacciola, J. S., Rutherford, M. J., O’Brien, C. P., & Koppenhaver, J. (1997).
Group counseling versus individualized relapse prevention aftercare following intensive outpatient treat-
ment for cocaine dependence: initial results. Journal of Consulting and Clinical Psychology,65 (5),
T.G. Brown et al. / Addictive Behaviors 27 (2002) 585–604602
McKay, J. R., Rutherford, M. J., Cacciola, J. S., Kabasakalian-McKay, R., & Alterman, A. I. (1996). Gender
differences in the relapse experiences of cocaine patients. Journal of Nervous and Mental Diseases,184 (10),
McLatchie, B. H., & Lomp, K. G. (1988). An experimental investigation of the influence of aftercare on alcoholic
relapse. British Journal of Addiction,83 (9), 1045 – 1054.
McLellan, A. T., Grissom, G. R., Zanis, D., Randall, M., Brill, P., & O’Brien, C. P. (1997). Problem– service
‘matching’ in addiction treatment: a prospective study in 4 programs. Archives of General Psychiatry,54,
McLellan, A. T., Luborsky, L., Woody, G. E., & O’Brien, C. P. (1980). An improved diagnostic evaluation
instrument for substance abuse patients: the Addiction Severity Index. Journal of Nervous and Mental Dis-
eases,168 (1), 26– 33.
McLellan, A. T., Woody, G. E., Luborsky, L., O’Brien, C. P., & Druley, K. A. (1983). Increased effectiveness of
substance abuse treatment: a prospective study of patient– treatment ‘‘matching’’. Journal of Nervous and
Mental Diseases,171 (10), 597 – 605.
Megargee, E. I. (1972). The California Personality Inventory handbook. San Francisco: Jossey-Bass.
Miller, W. R., & Bennett, M. E. (1996). Treating alcohol problems in the context of other drug abuse. Alcohol,
Health and Research World,20 (2), 118– 123.
Morgenstern, J., Labouvie, E., McCrady, B. S., Kahler, C. W., & Frey, R. M. (1997). Affiliation with Alcoholics
Anonymous after treatment: a study of its therapeutic effects and mechanisms of action. Journal of Consulting
and Clinical Psychology,65 (5), 768– 777.
Nowinski, J., Baker, S., & Carroll, K. (1992). Twelve-step facilitation therapy manual. A clinical research guide
for therapists treating individuals with alcohol abuse and dependence. National Institute on Alcohol Abuse
and Alcoholism. Project MATCH monograph series, vol. 1. Washington, DC: NIAAA Press (DHHS (ADM)
O’Farrell, T. J., Choquette, K. A., & Cutter, H. S. G. (1998). Couples relapse prevention sessions after behavioral
marital therapy for male alcoholics: outcomes during the three years after starting treatment. Journal of Studies
on Alcohol,59 (4), 357– 370.
¨jehagen, A., & Berglund, M. (1992). Acceptance, attrition and outcome in an outpatient treatment programme
for alcoholics: a comparison between a randomized and a non-randomized process outcome study. European
Archives of Psychiatry and Clinical Neuroscience,242, 82– 84.
Ouimette, P. C., Finney, J. W., & Moos, R. H. (1997). Twelve-step and cognitive –behavioral treatment for
substance abuse: a comparison of treatment effectiveness. Journal of Consulting and Clinical Psychology,
65 (2), 230– 240.
Project MATCH Research Group (1993). Project MATCH: rationale and methods for a multisite clinical trial
matching patients to alcoholism treatment. Alcoholism: Clinical and Experimental Research,17 (6), 1130– 1145.
Project MATCH Research Group (1997). Matching alcoholism treatments to client heterogeneity: Project MATCH
posttreatment drinking outcomes. Journal of Studies on Alcohol,58 (1), 7 – 29.
Rychtarik, R. G., McGillicuddy, N. B., Connors, G. J., & Whitney, R. B. (1998). Participant selection biases in a
randomized clinical trial of alcoholism treatment settings and intensities. Alcoholism: Clinical and Experimen-
tal Research,22 (5), 969–973.
Scott, E., Anderson, P. (1990). Randomized controlled trial of general practitioner intervention in women with
excessive alcohol consumption. Drug and Alcohol Review,10, 313– 321.
Simpson, D. D. (1979). The relation of time spent in drug abuse treatment and posttreatment outcome. American
Journal of Psychiatry,136 (11), 1449 – 1453.
Sobell, L. C., Maisto, S. A., Sobell, M. B., & Cooper, A. M. (1979). Reliability of alcohol abusers’ self-reports of
drinking behavior. Behavior Research and Therapy,17 (2), 157 –160.
Spitzer, R. L., Williams, J. B., Gibbon, M., & First, M. B. (1990). User’s guide for the structured clinical interview
for DSM-III-R. Washington, DC: American Psychiatric Association Press.
Thorton, C. C., Gottheil, E., Weinstein, S. P., & Kerachsky, R. S. (1998). Patient– treatment matching in substance
abuse: drug addiction severity. Journal of Substance Abuse Treatment,15 (6), 505–511.
T.G. Brown et al. / Addictive Behaviors 27 (2002) 585–604 603
Toneatto, A., Sobell, L., & Sobell, M. (1992). Gender issues in the treatment of abusers of alcohol, nicotine and
other drugs. Journal of Substance Abuse,4(2), 209 – 218.
Tonigan, J. S., Toscova, R., & Miller, W. (1996). Meta-analysis of the literature on Alcoholics Anonymous:
sample and study characteristics’ moderate findings. Journal of Studies on Alcohol,57 (1), 65 – 72.
Vannicelli, M. (1978). Impact of aftercare in the treatment of alcoholics. A cross-lagged panel analysis. Journal of
Studies on Alcohol,39 (11), 1875–1886.
Walker, R. D., Donovan, D. M., Kivlahan, D. R., & O’Leary, M. R. (1983). Length of stay, neurophysiological
performance and aftercare: influences on alcohol treatment outcome. Journal of Consulting and Clinical
Psychology,51 (6), 900– 911.
T.G. Brown et al. / Addictive Behaviors 27 (2002) 585–604604