Changing Network Support for Drinking: Initial Findings From the
Network Support Project
Mark D. Litt, Ronald M. Kadden, Elise Kabela-Cormier, and Nancy Petry
University of Connecticut Health Center
The aim of this study was to determine whether a socially focused treatment can effect change in the
patient’s social network from one that reinforces drinking to one that reinforces sobriety. Alcohol
dependent men and women (N ? 210) recruited from the community were randomly assigned to 1 of 3
outpatient treatment conditions: network support (NS), network support ? contingency management
(NS ? CM), or case management (CaseM; a control condition). Analysis of drinking rates for 186
participants at 15 months indicated a significant interaction effect of Treatment ? Time, with both NS
conditions yielding better outcomes than the CaseM condition. Analyses of social network variables at
posttreatment indicated that the NS conditions did not reduce social support for drinking relative to the
CaseM condition but did increase behavioral and attitudinal support for abstinence as well as Alcoholics
Anonymous (AA) involvement. Both the NS variables and AA involvement variables were significantly
correlated with drinking outcomes. These findings indicate that drinkers’ social networks can be changed
by a treatment that is specifically designed to do so, and that these changes contribute to improved
Keywords: alcoholism, social support, Alcoholics Anonymous (AA), cognitive–behavioral treatment,
It has long been suggested that an effective means to forestall
relapse in treated alcoholics is to alter the reinforcers for absti-
nence and drinking behavior in their home environment (e.g.,
Bigelow, Brooner, & Silverman, 1998). One way to achieve this is
to change the person’s social network. Steinglass and Wolin
(1974), among others, noted that the social milieu of an alcoholic
serves to support the drinking of those in the network.
Longabaugh and Beattie (Beattie & Longabaugh, 1999; Long-
abaugh & Beattie, 1986) coined the term “network support for
drinking,” referring to the degree to which people in the home
environment encourage drinking. Network support for drinking
has been found to be predictive of poor outcomes in treatment-
seeking patients (Havassy, Hall, & Wasserman, 1991; Long-
abaugh, Beattie, Noel, Stout, & Malloy, 1993; Project MATCH
Research Group, 1997).
Efforts to make existing social networks less supportive of
substance use have been proposed but have not been widely
adopted (e.g., Galanter, 1986, 1999). These efforts include the
community reinforcement approach (CRA), first proposed by Hunt
and Azrin (1973) and since refined (e.g., Meyers & Miller, 2001;
Sisson & Azrin, 1989), and the United Kingdom Alcohol Treat-
ment Trial Social Behaviour and Network Therapy study (UKATT
SBNT; Copello et al., 2002; UKATT Research Team, 2005). CRA
involves reinforcing the alcoholic’s sobriety and development of
activities incompatible with alcohol use, such as participation in
recreational and social activities and employment. Although CRA
is frequently cited as one of the most efficacious approaches to
treatment (e.g., Miller, Wilbourne, & Hettema, 2003), its use is not
widespread, possibly because of the time and effort required to
implement such a comprehensive intervention. Additionally, the
complexity of the intervention makes it difficult to determine what
features of CRA make it effective.
SBNT was an effort to identify, expand, and mobilize the social
network of drinkers, particularly family, friends, and acquaintan-
ces. In the UKATT Research Team’s (2005) study, both SBNT
and a comparison motivational enhancement therapy intervention
yielded significant decreases in drinking and in drinking-related
problems at 12 months, with no differences between treatment
conditions (UKATT Research Team, 2005). The authors did not
report whether SBNT acted on the social network as planned or if
changes in social network were related to outcomes.
The clearest example of an existing social network that supports
abstinence is Alcoholics Anonymous (AA). AA is a ready-made
sobriety-supporting network and fulfills several of the conditions
required of a behavioral choice model of relapse prevention
(Tucker, Vuchinich, & Gladsjo, 1990). AA provides alternative
activities to drinking, constrains access to alcohol (at least while
Mark D. Litt, Department of Behavioral Sciences and Community
Health, University of Connecticut Health Center; Ronald M. Kadden, Elise
Kabela-Cormier, and Nancy Petry, Department of Psychiatry, University of
Connecticut Health Center.
Portions of this article were presented at the International Conference on
the Treatment of Addictive Behaviors, Santa Fe, New Mexico, February
2006. Support for this project was provided by National Institute on
Alcohol Abuse and Alcoholism Grant R01-AA12827 and in part by Na-
tional Institutes of Health General Clinical Research Center Grant M01-
RR06192. We would like to acknowledge Eileen Porter, William Blakey,
Kara Dion, Abigail Sama, Nicole Paulin, Aimee Markward, Howard Stein-
berg, Patricia Gaupp, Anna Lane, and Christine Calusine for their work in
the conduct of this study.
Correspondence concerning this article should be addressed to Mark D.
Litt, Department of Behavioral Sciences and Community Health, MC3910,
University of Connecticut Health Center, Farmington, CT 06030. E-mail:
Journal of Consulting and Clinical Psychology
2007, Vol. 75, No. 4, 542–555
Copyright 2007 by the American Psychological Association
people are attending meetings), and provides a social group that
reinforces sober behavior. Several studies support the efficacy of
AA or similar groups in reducing alcohol use. Emrick, Tonigan,
and Montgomery (1993) concluded that AA members achieve
abstinence at a higher rate than do professionally treated alcoholics
and that AA participants who are more active in the fellowship
program fare better than less active participants. The findings of
AA studies are consistent with the idea that social support for
sobriety can enhance treatment outcome. Naturalistic studies by
Kaskutas and Bond (Bond, Kaskutas, & Weisner, 2003; Kaskutas,
Bond, & Humphreys, 2002) indicate that AA effects are partly
mediated by the changes that occur in patients’ social networks,
particularly changes in network support for drinking.
A difficulty with such naturalistic studies, however, is that
patients who actually attend AA are self-selected. Thus, it is not
possible to know what the true effect of AA is. To get an under-
standing of the true value of AA, researchers would have to
manipulate attendance at AA. To some extent, this was done in
Project MATCH, in which patients assigned to twelve-step facil-
itation (TSF) were encouraged to attend AA (Project MATCH
Research Group, 1993).
Analyses of the Project MATCH data set indicated that those
with networks supportive of drinking at intake had fewer percent-
age of days abstinent and more drinks per drinking day across all
follow-ups in that study (Longabaugh, Wirtz, Zweben, & Stout,
2001). A high level of network support for drinking was also
related to lower involvement in AA.
Network support for drinking also emerged as one of the more
interesting matching variables in Project MATCH. At the 3-year
follow-up, it was found that, among patients with high network
support for drinking at intake, those who had been assigned to the
TSF intervention had better outcomes than those assigned to
motivational enhancement therapy (Project MATCH Research
Group, 1998). Although network support for drinking per se was
not altered by TSF, causal chain analyses indicated that TSF did
result in greater involvement in AA, even among those with high
network support for drinking at intake. In contrast, for patients
whose social network at intake did not support continued drinking,
AA involvement had much less impact on outcome (Longabaugh,
Wirtz, Zweben, & Stout, 1998). The implication of these findings
is that a treatment that encourages a change of social network,
from one that is supportive of drinking to one that is supportive of
sobriety (e.g., by encouraging AA participation), may be effective,
especially for those whose pretreatment environments are initially
more supportive of drinking.
In the present article, the network support treatment is de-
scribed. Unlike SBNT, network support is more reliant on AA and
other established social infrastructures to change the social net-
work. AA attendance, as well as involvement in other nondrinking
networks, is manipulated by encouragement to attend sober net-
work functions (e.g., AA meetings, nondrinking social events) and
by reinforcing attendance in treatment.
Alcoholic patients drawn from the community were randomly
assigned to one of three treatment conditions: network support
(NS), network support ? contingency management (NS ? CM),
or a case management (CaseM) control condition. We hypothe-
sized that a NS intervention would result in more adaptive change
in social networks than would CaseM, and that such changes in the
social network would predict drinking outcomes.
We also hypothesized that direct reinforcement of network
change behaviors using contingency management procedures
would lead to greater (and faster) change in the social network, and
thereby more complete and lasting reductions in alcohol consump-
tion, than in the other conditions. Finally, we tested whether a NS
intervention would be most beneficial to those whose networks
were least supportive of abstinence at intake, consistent with the
finding in Project MATCH (Project MATCH Research Group,
1998; Zywiak, Longabaugh, & Wirtz, 2002). The present article
reports on results out to the 15-month follow-up.
Recruitment occurred from October 2002 through March 2005.
Participants were recruited through newspaper and radio adver-
tisements announcing free alcohol treatment and through other
research programs at our site, which is a university medical center.
To be eligible, individuals had to be at least 18 years old, meet
Diagnostic and Statistical Manual of Mental Disorders (4th ed.;
DSM–IV; American Psychiatric Association, 1994) criteria for
alcohol dependence or abuse, and be willing to accept random
assignment to any of the three treatment conditions. Individuals
were excluded from participation if they had acute medical or
psychiatric problems requiring inpatient treatment (e.g., acute psy-
chosis or suicide/homicide risk), current dependence on drugs
(except nicotine and marijuana), intravenous drug use in the pre-
vious 3 months, reading ability below the fifth-grade level, lack of
reliable transportation to the treatment site, or excessive commut-
ing distance. Individuals were also excluded if they were already
engaged in substance abuse treatment, if they denied any drinking
in the previous 60 days, or if they had attended more than three AA
meetings in the month prior to intake.
Of the 348 men and women who responded to advertisements
and were screened, 297 were eligible according to the criteria
described. Most (31) of the 51 excluded were already engaged in
some type of treatment. The remainder were excluded because of
other drug dependence or lack of transportation and/or stable
residence. Of the 297 initially considered eligible, 87 dropped out
of the study prior to randomization because of lack of interest or
concurrent drug abuse discovered after the baseline assessment but
before randomization. The remaining 210 participants were as-
signed to the three treatment conditions: NS (n ? 69), NS ? CM
(n ? 71), and CaseM (n ? 70). A sample size of 44 per cell was
determined to be sufficient to test all hypotheses (including the
interaction of Treatment ? Network Support Change) with a
power of .83 and alpha set at .05, on the basis of effect sizes
derived from previous studies of social network changes (Project
MATCH Research Group, 1997) and studies of contingency man-
agement procedures on treatment process measures (Petry, Martin,
Cooney, & Kranzler, 2000). Given the procedures used in each
treatment, participants, therapists, and research assistants could not
be blinded as to experimental condition. A diagram showing the
flow of participants through the recruitment, treatment, and
follow-up stages of the study is shown in Figure 1.
Participants were 58% male, with a mean age of 45 years (SD ?
11.4), and they were 86% White, 8% Black, 4% Hispanic, and 2%
other. Their mean years of schooling was 13.7 (SD ? 2.1), 71%
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Received December 15, 2006
Revision received April 27, 2007
Accepted May 10, 2007 ?
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