social settings and addiction relapse

journal of Substance Abuse, 7(2), 223-233 (1995)

BRIEF REPORT

Social Settings and Addiction Relapse

Maureen A. Walton

University of Michigan

Thomas M. Reischl

Michigan State University

Chathapuram S. Ramanathan

Wayne State University

Despite addiction theorists’ acknowledgment of the impact of environmental factors on relapse, researchers have not adequately investigated these influences. Ninety-six substance users provided data regarding their perceived risk for relapse, exposure to substances, and involvement in reinforcing activities. These three setting attributes were assessed in their home, work, and community settings. Reuse was assessed 3 months later. When controlling for confounding variables, aspects of the home settings significantly distinguished abstainers from reusers; perceived risk for relapse was the strongest predictor of reuse. Exposure to substances and involvement in reinforcing activities were not robust reuse indicators. The work and community settings were not significant determinants of reuse. These findings offer some initial support for the utility of examining social settings to better understand addiction relapse and recovery. Identification of setting-based relapse determinants provides concrete targets for relapse prevention interventions.

Addiction relapse rates are high across treatment modalities regardless of substance used (Brownell, Marlatt, Lichtenstein, & Wilson, 1986; Hunt, Barnett, SC Branch, 1971; Miller & Hester, 1986). Although addiction theorists acknowl- edge social and environmental factors as determinants of relapse, these factors have not been extensively studied. Many substance users live an “addictive lifestyle” that includes associating with users and substance-using activities (Marlatt & Gordon, 1985; Tucker, Vuchinich, & Gladsjo, 1991; Vaillant, 1988); in order to recover, they are advised to restructure their social settings by becoming involved with sober people, places, and things (Gorski, 1986; Marlatt & Gordon,

This research was supported by the Michigan Department of Public Health Center for Substance Abuse Services, the National Institute on Drug Abuse Grant DA05524, and the National Institute on Alcohol Abuse and Alcoholism Grant AA07477. Thoughtful comments by Kelly Bates and Lisa Thomson Ross on earlier versions of this manuscript are gratefully acknowledged.

Correspondence and requests for reprints should be sent to Maureen A. Walton, University of Michigan, Alcohol Research Center, 400 E. Eisenhower Pkwy., Bldg. 2, Suite A, Ann Arbor, MI 48108.

223

224 M.A. Walton, T.M. Reischl, and C.S. Ramanathan

1985). In this way, they may experience fewer risky situations, be exposed less

often to substa11ces, and be more involved with leisure activities that are

substance-free. This research was a prelitninary attempt at describing the impact

of social setting factors on addiction relapse.

Kesearch on setting-hased risk indicators needs to stat-t with two questions:

Which settings? Which setting dimensions i For this study, the home, work (or

school), and community settings were chosen to obtain maximum ecological co\‘-

erage of the recovering persons lifestyle or microsystems (Bronfenbrenner,

1979). ‘The choice of setting dimensions was guided by previous research on

addiction t-elapse. Three dimensions were examined: perceived risk or urge to

use. exposure to substances, and in~ol~~etnetit in reinforcing activities.

According to Marlatt and Gordon (198.5). relapse OCCLII~S as ;t response to ;i

risky ,situation under certain cognitive conditions. Relapsers report using more

often in certain types of risk, situations (Brown, Vik, & Creamer, 1989; C:um-

mings, Gordon, 8c Marlatt, 1980; Marlatt KC (cordon, 1985). Research regarding

the impact of risky settings, or the environmental location of’ risks (e.g., home.

bvork), on recovery is nonexistent. Instead, the literature examines risky .situcl-

tions, such as negative emotional states, regardless of where they occur. By exm-

ining ;I risky, .srtting the behavioral influences of setting-based role expectations

(or the anttctpated contingencies for abstinence or substance use) are taken into

account (Brottfenl~renner, 1979). A risky situation that occurs at work, in the

presence of others lvho disapprove of substance use, may have a different ou-

come than when the risky situation occurs at home, with no one present. Because

some situations are more risky than others, it follows that some settings might be

more risky than others.

l’xposut-e to substances during early recovery is considered potentially harm-

ful and hence should be a\wided (Got-ski, 1986). Support for this notion is that

exposure to substances is a cot~~t~~ot~ risky situation for relapse (Brown et al.,

191x9) and produces craving (O’Brien et al., 198X; Sjoberg Xc Olsson, I98 I ). .l‘he

literature has consistently docutnet~ted the positive benefits of associating tvith

people supportive of sobriety mci the negaztive impact of associating with people

using substances (Gordon 8c Cull, 199 1 ; Svanum 8.~ McAdoo, 1989). It is not

clear, however, how exposure to substances in a particular setting, or across set-

tinqs, affects relapse.

&me addiction theorists suggest that people recovering from the use of ad-

dictive substances need to be engaged in substance-free enjoyable activities. Re-

lapse is theoriLed to he ii response to the limited availability of alternati\,c

reinforcing activities (Tucker et al., 199 1) so that responsibilities, or “shoulds,”

must be equal to enjoyable acti\+ties, or “wants,” before lasting sobriet \r; will be

acliie\,ed (Mat-latt 8c (~ordoti, 198.5). Research validating these notions is sparse.

Studies have documented the benefits of family recreation in early recover)

(Bromet 8s Moos. 1977; Moos, Bromet, -1‘s~. & Moos, 1979) hut have not found

this relationship at 2 years (Finnep Moos, 8c Mewborn, 19X0). It may be that

leisure activities are more itiiportatit during early reco\‘et-y as the substance usel

establishes ;I new lifestyle. Alternatively, the reinforcement received from the

activity may be a more potent relapse determinant than the activity itself as re-

Social Settings 225

lapsed alcoholics perceived family leisure time more negatively (Moos et al., 1979).

Although these studies offer some support for the impact of risky situations, exposure to substances, and availability of reinforcing activities on addiction recovery, there is a need for more clarity on how these factors affect addiction relapse in different .~ettin~qs. Examining settings may be important because the reinforcement value of an activity or event varies widely according to the behavior setting in which it occurs (Wicker, 1972). To illustrate, going to a concert in the community may be more reinforcing than watching a concert on TV at home. Furthermore, all available settings should be examined because setting’s effects may be reciprocal. Several studies found that an alcoholic’s work environment was only related to outcome for those not living with a spouse (Bromet SC Moos, 1977; Finney et al., 1980).

This research focused on a person’s perceptions of’ their social environments, and not on observation of their behavior settings, because the meaning a person gives to different aspects of the environment,,f&ction, may be more powerful in determining behavior than the objective physical conditions,,fomn (Bronfenbren- ner, 1979; Perkins, Burns, Perry, 8c Nielson, 1988), regardless of whether these perceptions are accurate (Wicker, 1987). In addition, the use of nonintrusive observers is impractical for substance use that may take place in private nonob- servable settings (Perkins et al., 1988).

This study tested the hypothesis that setting attributes would prospectively determine substance reuse. Abstainers were expected to have fewer relapse risks, fewer exposures to substances, and greater involvement in reinforcing activities than substance reusers. Exploratory hypotheses examined the relative influence of these constructs across settings.

METHOD

Participants

Ninety-six persons completing treatment for alcoholism and/or drug addiction in the previous 6 months participated in this study. Participants were treated in the following types of programs: inpatient (n = 35), outpatient (n = 37) or residential (n = 24). Persons currently on methadone maintenance were ex- cluded from participating. Participants were recruited over a l-year period from multiple treatment settings and Alano Clubs in two mid-Michigan communities.

The majority of the participants were male (790/c), white (70%), and were not married (74%). The average age was 35 years, ranging from 20 to 58 years. Most participants were employed full-time (66%) and had 12 or less years of education (70%). The average monthly income was $1,084 and ranged from $0 to $10,000. Most participants identified themselves as primarily alcoholic (66%); 34% identified themselves as having primary problem with one or more other drugs (e.g., cocaine). Few participants had been in substance abuse treatment only once (5%); 66% had been treated two or three times; 29% had been treated more than three times. Participants’ abstinence periods varied: 64% had less


than 6 months of sobriety; 29% had 6 to 12 months of sobriety; 770 had 13 to 16 months of sobriety.

The participants in this study were similar to statewide treatment admissions, In 1991, 62% of statewide admissions were for alcohol problems (Community Epidemiology Work Group, 1991). The majority of statewide admissions were male (68%), and between ages 26 to 35 (57(Z), and not married (76%). In contrast to this sample, only 2 1% of statewide admissions were employed full-time and 45% were white; these differences are not surprising considering the city of De- troit is included in the statewide admissions.

Design and Procedures

A longitudinal design was used to assess the impact of setting factors on reuse 3 months later. At the pretest, participants signed an informed consent and com- pleted several instruments (not reported on here) including the Addiction Sever- ity Index, a social network assessment, a self-efficacy scale, and a setting risk indicator measure. The timeline calendar was administered at the S-month follow-up interview. Participants were compensated for their time in the amount of $10 for the pretest interview and $15 for the follow-up interview. Interviews were conducted at convenient locations (e.g., Alano clubs, restaurants, participants’ homes). In all locations, interviewers made sure that no one could over- hear the conversation. Complete follow-up interviews were obtained from 89 participants (retention rate = 93%).

MEASURES

In addition to demographic information, the Addiction Severity Index (ASI) provides composite scores for six problem areas including drug and alcohol use (McLellan, Luborsky, Woody, 8c O’Brien, 1980). These composite scores havt been shown to be reliable and valid (McLellan et al., 1985). Social wt7mrk.r were delineated according to four areas: partner, family, friends, professionals, others (Norbeck, Lindsey, 8c Carrieri, 1981). Q uestions were asked of each member’s frequency of contact and support for sobriety. A sobriety support variable was computed by taking the mean of the perceived support for sobriety question from network members seen at least weekly. Self-efficacy was measured using 16 items from the Situational Confidence Questionnaire (Annis, 1982). Response choices were modified from percentages to a 5-point Likert scale ranging from 0 (Itot ut all) to 4 (extrPmPly) (CX = .Yl).

Setting Risk Indicator

T’his measure assessed three variable domains within the home, work, and community settings: perceived risk for relapse, exposure to substances, and involvement in reinforcing activities. Work environments were only assessed for persons working in the last month.

For the risk &m&n, participants reported the number of days during the

Social Settings 227

month prior to the pretest that they had urges to use substances and felt at risk for relapse in the home, work, and community settings. For each setting, the perceived risk indicator was the largest of the two numbers (as opposed to add- ing the numbers) because many participants equated the presence of an urge with the feelings of risk and it was not clear whether the urge and the risk occurred on the same day or on different days. For the exposure domain, participants reported the number of days during the month prior to the pretest that they had been offered substances or in which someone used substances in their presence in the home, work, and community settings. For each of the three settings, the exposure variable was created by choosing the larger of the two numbers because it was not clear if the exposures occurred on the same day or different days. The risk and exposure variables had skewed distributions because most participants reported few days when they perceived a relapse risk or were exposed to substances. To compensate for the skewed distributions, the risk and exposure variables were transformed into ordinal variables: “0” indicated no risk/exposure days; “1” indicated 1 to 7 risk/exposure days; “2” indicated more than 7 risk/exposure days. Summary risk and summary exposure indices were created by summing the transformed specific setting variables (home, work, and community) for risk or exposure; these indices ranged from zero to six.

For the reinforcing activities domain, participants responded to a fixed list of activities that they were engaged in during the month prior to the pretest in the home setting (e.g., watching television, praying, cooking and eating, visiting with family or friends) and community settings (e.g., religious services, shopping, movies, sports/exercise). For the work setting, participants described the activities they were involved in at work. Next, participants reported the amount of time per day or week that they were involved in each activity in the last month, rounded to the half hour. For example, 1 hour of church a week for 4 weeks was counted as 4 hours, and 5 minutes of prayer every day for 30 days was counted as 2.5 hours. Finally, participants rated how much they enjoyed each activity (5- point rating) ranging from 0 (not at all) to 4 (extremely). Each activity was weighted by multiplying its enjoyment value by the proportion of time they were involved in that activity. These weighted activity ratings were then summed across all the activities in each setting. Thus, home, work, and community reinforcing activities scores ranged from zero to four with higher scores representing greater involvement in enjoyable leisure activities. A summary reinforcing activities index was created by averaging the specific setting variables (home, work, community); this ranged from zero to four.

Substance Reuse

The go-day Timeline Follow-back protocol was used to examine daily alcohol and drug consumption over the 3-month follow-up period (Sobell, Maisto, Sobell, 8~ Cooper, 1979); several studies have demonstrated the reliability and validity of this method (Sobell, Sobell, Leo, & Caneilla, 1988). At the follow-up, 72% of the participants remained abstinent and 28% reused substances. Because


the number of days of‘ substance use was highly skewed, a dichotomous abstinence/reuse variable was used for all analyses.

Data Analysis

Descriptive analyses were used to examine variation in the setting variables and reuse in order to control identified sources of‘ group nonequivalence in subsequent analyses. A series of‘ logistic regression analyses were conducted to determine the impact of setting factors on reuse, controlling for nonequivalence between abstainers and reusers.

RESULTS

Potential Confounding Variables

Abstainers and reusers were compared on several demographic and treatment variables. Income, age, race, gender, education, employment status, marital status, drug of choice, and number of‘ previous treatment episodes were got significantly related to reuse. Reuse was significantly related to ASI alcohol composite (t = -2.65, I < .05), ASI drug composite (t = -2.06, I < .05), treatment type, x2(2) = 10.95, p < .O 1, and sobriety months (1 = 2.40, Jo < .05). l&users had greater alcohol and drug problem severity scores, fewer months of’ sobriety. and were most likely from outpatient, followed by inpatient, and resident ial trea- ment, respectively, than abstainers.

The demographic and treatment variables described also ivere tested for theil relationship to the setting variables, and the following significant relationships were f’ound. Summary risk was significantly I-elated to the AS1 drug composite (Y = .Y6, p < .05); higher ~II-ug severity was related to higher risk. Summar) exposure was significantly related to treatment type, F(2, 60) = 4.1.1, p < .05) with outpatient participants having the highest exposure scores, f’ollowed by participants tram residential and inpatient treatment. Home reinforcing activities were significantly related to race (I = -2.79, p < .Ol); whites had greater reinforcing activities scores than minorities. Work reinf’orcing activities were signif’- cantly related to treatment type, t;(2, 60) = 4.82, p < .05; outpatient par1icipants had the greatest exposure scores, ti~llowed by participants f’rom inpatient and

residential treatment. Work exposure \V:;IS signiticantly related to treatment tyvlje, (F(2,60) = 3.49, p < .O:i; outpatient had the greatest exposure scores, follo~ved by participants f‘rom residential and inpatient treatment. Community risk was significantly related to the AS1 drug composite (1. = 0.48, p < .Ol) and to marital status (1 = -2.12, p < .05) where greatel- risk indicated greater drug problems arid not currently being married. Community exposure ~2s significantly related to the AS1 alcohol 0. = .30. p < .05) and drug composites (1. = .%i, p < .05); greater exposure indicated greater ;~lcohol and drug problems.

Using Setting Attributes to Predict Reuse

Four logistic regression analyses were conducted to examine the impact of’ social setting variables on reuse 3 months later (Table 1). First, an attempt was

Table

1.

Logis

tic

Regre

ssio

n

An

aly

ses

for

Set

ting

Vari

able

s Pre

dic

ting

Reuse

Sta

tus

Contr

ollin

g

for

Con

foun

din

g

Vari

able

s

Vari

able

Dom

ain

Sum

mary

In

dex

Hom

e S

etti

ng

(n =

89)

(n =

85)

B (W

ald

~2)

B (W

ald

~2)

Work

Set

ting

(n =

54)

B (W

ald

xp)

Com

munit

y S

etti

ng

(n =

89)

B (W

ald

x*)

step 1

:

Sobr

iety

m

onth

s

Inpa

tient

tr

eatm

ent

Out

patie

nt

trea

tmen

t

Alc

ohol

se

veri

ty

Dru

g se

veri

ty

Rac

e

Mar

ital

stat

us

Mod

el

log-

likel

ihoo

d (-

2 L

og

L)

Mod

el

x2

W c

orre

ctly

cl

assi

fied

Ste

p

2:

Perc

eive

d ri

sk

Subs

tanc

e ex

posu

re

Rei

nfor

cing

ac

tiviti

es

Mod

el

log-

likel

ihoo

d (-

2 L

og

L)

Mod

el

,T+’

‘i

corr

ectly

cl

assi

fied

-0.1

8 (3

.96)

*

-0.1

8(0.

11)

-0.8

7 (3

.75)

3.55

(3

.95)

*

4.74

(0

.56)

0.32

(0

.75)

0.01

(0

.001

)

80.7

4

24.9

6 **

*

77.5

3

-0.2

1

(4.4

3)*

-0.0

1 (0

.001

)

-0.8

0 (2

.98)

4.35

(5

.1.5

)*

4.52

(0

.49)

-0.4

5 (1

.3 1

)

72.8

7

26.3

8 **

*

80.0

0

1.25

(6

.39)

*

-0.6

9 (1

.55)

0.36

(0

.36)

63.3

3

9.54

*

X1.

18

-0.1

1 (1

.28)

0.02

(0

.001

)

-0.7

9 (2

.69)

2.61

(1

.11)

12.5

7 (1

.43)

n

48.5

4

18.7

3 **

79.6

3

0.90

(3

.14)

-0.3

5 (0

.30)

-0.0

3 (0

.004

) 4.

5.26

3.29

79.6

3

-0.1

6 (3

.59)

-0.0

8 (0

.03)

-0.7

8 (3

.26)

3.34

(3

.67)

5.24

(0

.68)

L

(

-0.0

1 (0

.001

)

81.5

0

24.2

0 **

*

77.5

3

0.24

(0

.24)

0.27

(0

.27)

0.13

(0

.07)

80.5

3

0.96

77.5

3

‘Var

iabl

e no

t in

clud

ed

in

mod

el.

*fi

< .0

5.

**p

< .

Ol.

***p

< .

OO

l.

_-


made to determine whether general setting factors have any impact on reuse when controlling for confounding variables. Because treatment type was ;I three- level categorical variable, two dummy variables were used: outpatient (yes/no) and inpatient (yes/no). All identified conf’ounding variables (sobriety months, ASI alcohol and drug composites, inpatient treatment, outpatient treatment, race, and marital status) were entered on Step 1; this base model was significant (Model x’(7) = 24.96, p < .OOl). The summary setting variables (perceived risk, substance exposure, and reinforcing activities) were entered on Step 2. The dit- f’erence in log-likelihood was rot significant (Model x2(3) = 5.85, $J > .05) indicat- ing that the summary setting variables did nut significantly improve the base model. Upon examining the unstandardized parameter estimates (betas), however, notice that the estimate f’or perceived risk is significant, suggesting that this variable may influence reuse.

Because this analysis does not examine the impact of’ the various domains according to the settings, or contexts, in which they occur, logistic regression analyses also were performed separately f’or the home, work, and community settings. In all settings, the confounding variables related to reuse were entered on Step 1 (sobriety months, ASI alcohol and drug composites, inpatient treatment, outpatient treatment); in the home setting analysis, race also was included, and in the community setting analysis, marital status also was included on Step 1. The specific setting variables were entered on Step 2. Analyses fr the home setting showed that these variables significantly improved the base model (Model x”(3) = 9.54, p < .05); home risk was the most powerful determinant of’ reuse. Analyses f’or the work and community settings showed that these variables did not significantly improve the base models (Model x’(3) = 3.29, p > .05; Model x’(3) = 0.96, p > .05, respectively).

Other Reuse Indicators

In order to better understand the setting factors examined in this study, the summary variables were compared to other reuse-related variables: self-efficacy and sobriety support. Summary risk was significantly correlated with self- efficacy (r = -0.41, p < .Ol); none of’ the setting variables were significantly correlated with sobriety support. A final logistic regression analysis was conducted to assess the impact of’ these more common relapse indicators on reuse. Confounding variables were entered on Step 1 (sobriety months, AS1 alcohol and drug composites, inpatient treatment, outpatient treatment, race, and marital status). Self’-efficacy and sobriety support were entered on Step 2; these variables did not significantly improve the model (-2 Log Likelihood = 75.12, Model x2 = 4.73, p > .05, / . O,J correctly classified = 81.82).

DISCUSSION

Results offer some initial support for the utility of’ examining social setting influences to explain relapse. Key findings were that a person’s perception of risk for relapse in a setting was the most potent construct in determining future

Social Setting 231

relapse and that the home setting had a greater influence on relapse than the work or community settings. In addition, home setting factors contributed to the understanding of relapse beyond typical relapse indicators such as self-efficacy and social network support for sobriety.

The finding that a person’s perception of risk for relapse effectively deter- mines relapse is consistent with the previous findings regarding high-risk situations (Marlatt & Gordon, 1985). However, this study found that abstainers and relapsers differed regarding their perceptions of risk for relapse in particular settings. These findings are consistent with the notion that the actual determinant of relapse resides in the contingencies present in a particular setting in which the risky situation occurs. Theoretically, a person’s perception of risk might serve as a self-fulfilling prophecy and result in reuse; indeed, a greater perceived setting risk was associated with lower self-efficacy. Alternatively, the perception of risk might be an accurate assessment of environmental pressures for relapse that are present in a setting. A person may be identifying people, places, and things associated with substance use; these setting attributes are incompatible with a lifestyle that is substance-free, which makes these settings risky (Gorski, 1986; Marlatt & Gordon, 1985; McCrady, 1989). Future research might investigate further the basis of risk perceptions.

Although those with more frequent exposures to substances were more likely to reuse substances 3 months later, substance exposure had a minor influence on reuse. When refining the exposure construct, it may be useful to assess if an individual was exposed to their drug of choice, or to legal versus illegal substances. For example, an alcoholic who never used marijuana may not be tempted by someone using marijuana in front of him or her. Also, whether other persons present in the setting during the exposure were supportive of substance use or of abstinence should be included, because relapse behavior is theorized to be determined by anticipated reactions (punishment or reinforcement) from others for substance use or sobriety (McCrady, 1989).

In contrast to theories suggesting the importance of leisure activities to addiction recovery, involvement in reinforcing activities was not a potent determinant of relapse. It may be that negative aspects of settings, such as perceived risk for relapse, are more powerful influences on relapse than positive setting attributes, such as involvement in reinforcing activities. Similarly, Billings and Moos (1983) found that avoidance of negative situations was a more powerful coping strategy than participation in positive environments. Alternatively, this null finding may be attributed to the fact that this study did not assess whether the reinforcing activity (e.g., viewing movies) involved using substances. Future research might focus on changes from pretreatment substance-using activities to those that are substance free; assessment of activities might also be limited to those in which the person is invested, as opposed to all the activities that take place in a setting.

Limitations

The uniqueness of the approach taken in this preliminary study to measure setting attributes and the heterogeneity of the sample warrants caution in asser-


tion of’ findings until additional replications can be made. The generaliability of this study is compromised by the requirement that participants had to complete treatment and volunteer for a research study. This selectivity may explain the high abstinence rate (725%). Although the f’ollow-up used in this study was brief’, research suggests that the majority of’ those who relapse do so within 1 to 3 months following treatment (Hunt et al., 197 1). Nonetheless, f‘uture studies should examine these preliminary findings on the extent of‘ relapse, as opposed to simply abstinence or reuse, with longer follow-ups. These studies also would be strengthened by examining the relationship between specific setting in which reuse occurs and the setting’s characteristics.

Future Research and Implications

Setting-type data may be useful because it provides clinicians and researchers with markers f& “high-risk” people and concrete targets for relapse prevention interventions. Relapse prevention approaches with people who perceive the home setting as risky might focus on aspects of’ this setting that make it risky so that coping strategies could be taught to restructure the person’s perception of the risk or the response to the risk. Alternatively, advocacy approaches (Fagan 8.~ Mauss, 1986) or social network therapy (Galanter, 1993) could be implemented to attenuate the risk, even if’ that requires changing relationships or moving to a new home. ‘The examination of’social setting influences on relapse is promising and justifies continued research in order to better understand and eventually prevent relapse.

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Social Settings 233

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