RESEARCH ANALYSIS

and

UTILIZATION SYSTEM

Relapse and

Recovery

in Drug Abuse

DEPARTMENT OF HEALTH AND HUMAN SERVICES

Public Health Service

Alcohol, Drug Abuse, and Mental Health Administration
Relapse and Recovery

in Drug Abuse

Editors:

Frank M. Tims, Ph.D.

Carl G. Leukefeld, D.S.W.

Division of Clinical Research

National Institute on Drug Abuse

NIDA Research Monograph 72

1986

DEPARTMENT OF HEALTH AND HUMAN SERVICES

Public Health Service

Alcohol, Drug Abuse, and Mental Health Administration

National Institute on Drug Abuse

5600 Fishers Lane

Rockville, Maryland 20857

For sale by the Superintendent of Documents, Congressional Sales Office

U.S. Government Printing Office, Washington, DC 20402
NIDA Research Monographs are prepared by the research divisions of the

National institute on Drug Abuse and published by its Office of Science. The

primary objective of the series is to provide critical reviews of research problem

areas and techniques, the content of state-of-the-art conferences, and

integrative research reviews. Its dual publication emphasis IS rapid and targeted

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Editorial Advisors

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Temple University School of Medicine

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RICHARD E. BELLEVILLE, Ph.D.

NE Associates, Health Sciences

RockviIle, Maryland

KARST J. BESTEMAN

Alcohol and Drug Problems Association

of North America

Washington, D.C.

GILBERT J. BOTVIN, Ph.D.

Cornell University Medical College

New York, New York

JOSEPH V. BRADY, Ph.D.

The Johns Hopkins University School of

Medicine

Baltimore, Maryland

THEODORE J. CICERO, Ph.D.

Washington University School of

Medicine

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MARY L. JACOBSON

National Federation of Parents for

Drug-free Youth

Omaha, Nebraska

REESE T. JONES, M.D.

Langley Porrer Neuropsychiatric lnstitute

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College of Physicians and Surgeons of

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Yale University School of Medicine

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New Jersey State Department of Health

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NIDA Research Monograph Series

CHARLES R. SCHUSTER, Ph.D.

Director, NIDA

THEODORE M. PINKERT, M.D., J.D.

Acting Associate Director for Science, NIDA

Parklawn Building. 5600 Fishers Lane, Rockville, Maryland 20857
Relapse and Recovery

in Drug Abuse
This monograph is based upon papers and discussion from the RAUS

Review Conference on Relapse and Recovery in Drug Abuse which took

place on September 19 and 20, 1985, in Rockville, Maryland. The

review was sponsored by the Office of Science and the Division of

Clinical Research, National Institute on Drug Abuse.

COPYRIGHT STATUS

The National Institute on Drug Abuse has obtained permission from

the copyright holders to reproduce certain previously published

material as noted in the text. Further reproduction of this

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and may be used or reproduced without permission from the Institute

or the authors. Citation of the source is appreciated.

The U.S. Government does not endorse or favor any specific

commercial product. Trade or proprietary names appearing in this

publication are used only because they are considered essential in

the context of the studies reported herein.

Opinions expressed in this volume are the views of the authors and

do not necessarily reflect the official position of the National

Institute on Drug Abuse or any other part of the U.S. Department of

Health and Human Services.

DHHS Publication No. (ADM)90-1473

Alcohol, Drug Abuse, and Mental Health Administration

Printed 1986, Reprinted 1988, 1990

NIDA Research Monographs are indexed in the Index Medicus. They

are selectively included in the coverage of American Statistics

Index, Biosciences Information Service, Chemical Abstracts, Current

Contents, Psychological Abstracts, and Psychopharmacology Abstracts

iv
Preface

The Research Analysis and Utilization System (RAUS) is designed

to serve four functions:

Collect and systematically classify the findings of all

intramural and extramural research supported by the

National Institute on Drug Abuse (NIDA);

Evaluate the findings in selected areas of particular

interest and formulate a state-of-the-art review by a

panel of scientific peers;

Disseminate findings to researchers in the field and to

administrators, planners, instructors, and other

interested persons;

Provide a feedback mechanism to NIDA staff and planners

so that the administration and monitoring of the NIDA

research program reflect the very latest knowledge

gleaned from research in the field.

Since there is a limit to the number of research findings that

can be intensively reviewed annually, four subject areas are

chosen each year to undergo a thorough examination.

Distinguished scientists in the selected field are provided with

copies of reports from NIDA-funded research and invited to add

any information derived from the literature and from their own

research in order to formulate a comprehensive view of the

field. Each reviewer is charged with writing a state-of-the-art

paper in his or her particular subject area. These papers,

together with a summary of the discussions and recommendations

which take place at the review meeting, make up a RAUS Review

Report in the NIDA Research Monograph Series.

Relapse and recovery are two related areas which are central to

drug abuse treatment and research. This view of drug addiction

and dependence as chronic, relapsing disease is supported by both

v
research and clinical experience. Recent research shows that

many drug abusers have relatively short "addiction careers" and

suggests that with a better understanding of relapse (and its

prevention), we may be able to assist clients more effectively in

reaching a state of recovery.

The meeting on which this monograph is based took place September

19-20, 1985, at the National Institute on Drug Abuse. Its focus

was on: (1) a review of available theoretical perspectives;

(2) reviews of long-term studies of treated samples to assess

patterns of relapse and recovery over protracted time spans;

(3) understanding relapse and recovery through examination of

controlled studies and shorter term followup research; and

(4) implications of research for clinical practice. The meeting

was jointly chaired by Frank M. Tims, Ph.D., and Carl G. Leukefeld, D.S.W. Ms. Jacqueline P. Ludford, Chief, Research Analysis

Branch, Office of Science, is coordinator of NIDA's RAUS system.

vi
Contents

Preface

Relapse and Recovery in Drug Abuse: An Introduction

Frank M. Tims and Carl G. Leukefeld

Theories of Relapse and Recovery and Their Implications

for Drug Abuse Treatment

Donald R. Wesson, Barbara E. Havassy, and David E. Smith

The Drug Dependence Syndrome Concept as an Organizing

Principle in the Explanation and Prediction of Relapse

Thomas F. Babor, Ned L. Cooney, and Richard J. Lauerman

Acquisition, Maintenance, Cessation, and Reacquisition:

An Overview and Behavioral Perspective of Relapse to

Tobacco Use

John Grabowski

Relapse and Recovery in Substance Abuse Careers

James F. Maddux and David P. Desmond

Multivariate Description of Alcoholism Careers:

A 10-Year Followup

Colin Taylor, David Brown, Anni Duckitt, Griffith

Edwards, Edna Oppenheimer, and Margaret Sheehan

Relapse and Recovery Among Opioid Addicts 12 Years

After Treatment

D. Dwayne Simpson and Kerry L. Marsh

The Process of Smoking Relapse

Thomas H. Brandon, Stephen T. Tiffany,

and Timothy B. Baker

Commitment to Abstinence and Relapse to Tobacco, Alcohol, and

Opiates

Sharon M. Hall and Barbara E. Havassy

v

1

5

20

36

49

72

86

104

108

vii
Explaining Relapse to Opiate Addiction Following Successful

Completion of Treatment

William E. McAuliffe. Barry Feldman, Rob Friedman,

Elaine Launer, Elizabeth Magnuson, Carl Mahoney,

Susan Santangelo, and William Ward

Relapse to Use of Heroin, Cocaine, and Other Drugs

in the First Year After Treatment

Robert L. Hubbard and Mary Ellen Marsden

Smoking Cessation and Relapse Among Cardiac Patients

George E. Bigelow, Cynthia S. Rand, Janet Gross,

Thomas A. Burling, and Sheldon H. Gottlieb

Clinical Implications of Relapse Research

Bruce J. Rounsaville

Relapse and Recovery: Some Directions for Research and

Practice

Carl G. Leukefeld and Frank M. Tims

List of NIDA Research Monographs

136

157

167

172

185

191

viii
Relapse and Recovery

in Drug Abuse: An Introduction

Frank M. Tims and Carl G. Leukefeld

From the treatment perspective, relapse and recovery are key

issues. The high rate of relapse is an especially frustrating

problem, and the notion of a "cure" remains elusive. Substance

abuse careers are episodic, with periods of abstinence, reduction

of use, and relapse the prevailing pattern, often with the course

of events being influenced by external factors such as availability

of drugs and societal pressures. Given the patterns of relapse and

remission, a variety of interpretations of the nature of substance

abuse as a disease condition, how it should be treated, and what

the goals of treatment should be, have evolved.

High relapse rates among substance abusers remain old news.

Numerous studies have documented that high relapse rates prevail

across classes of substances--for example, Marlatt (1979) has found

that the average time from abstinence to relapse varies from 4 to

32 days for tobacco, alcohol, and opiates. But there are a host of

questions which should be addressed in attempts to understand

relapse, as well as recovery. Prominent among these questions is

one of definition. What constitutes relapse in treatment

populations where a variety of post-treatment substance use

patterns may be observed? If treatment is for a particular

substance abuse problem, how are we to consider such issues as

controlled or occasional use, substitution, and continuation of use

of another, perhaps lesser, substance which may constitute abuse?

A common solution to this dilemma of classifying relapse to a

specific substance is to apply a criterion of loss of control or

return to some level of use (For example, see Hall, this volume).

There is also a problem presented by the complexity of substance

use patterns, as seen in the contrast between polydrug abusers and

opiate addicts. As Hubbard and Marsden (this volume) point out,

multiple drug use among clients being admitted to treatment is

common, and use of a given substance in the early posttreatment

period is often continuation of the pattern present at termination

of treatment. It appears that some subgroups maintain positive

treatment outcomes and have lower relapse rates, although these

groups need sharper definition and elaboration. Also, there is a

need to better understand how treatment brings about desired

1
behavioral changes, and how these changes can be maintained for

specific client types.

Like relapse, recovery is an area where knowledge is lacking.

While relapse is observable almost immediately, recovery is a

complex, long-term phenomenon. There are criterion problems. At

what point is recovery achieved, or, stated dlfferently, is

recovery a continuing process over a lifetime of high risk?

Research using data from the Drug Abuse Reporting Program (DARP)

has noted that while a large percentage of opiate addicts

eventually cease use after treatment, marijuana use appears to be a

lasting pattern among many clients otherwise drug abstinent

(Simpson and Sells 1982). Duckitt and others (1985) have also

raised the questin regarding relapse after treatment for

alcoholics. Clinicians recognize that "slips" or occasional lapses

may occur without return to regular use, and researchers have noted

that ex-addicts may occasionally use opiates without returning to

regular use (Waldorf 1983). Understanding the recovery process is

not easy since this is an area of incremental knowledge growth, and

the study of long-term careers is essential for this development.

Nevertheless, there are some favorable indications in the area of

opioid addiction. Simpson and others (1982) found that an

increasing percentage of opioid addicts reach and maintain

abstinence over a 6-year period, with more than half this sample

opioid abstinent at 6 years. Moreover, findings from another

sample of opioid addicts in the DARP treatment population revealed

reasonably stable outcomes over a much longer period (Joe et al.

1984). These DARP outcome studies are a sharp contrast to those of

treatment samples from the 1950s.

In attempts to better understand relapse and recovery, numerous

theoretical formulations have been advanced, often with limited

data. Better integration of theory and empirical findings,

organized to build on promising treatment approaches, could make a

major contribution. This would serve to: (1) clarify existing

theory and assess the relative utility of those theories to better

explain relapse and recovery; (2) critically examine recent

long-term studies of substance abuse clients, with a view to

identifying differential outcome patterns and predictors;

(3) review more short-term, controlled studies which have the

potential for increased understanding of relapse and recovery; and

(4) consider the implications of theory and research findings for

clinical practice. Thus, the structure and outline of this

volume. Because a key question has to do with the extent to which

relapse and recovery are generalitable across categories of

substances, a major objective here was to include researchers and

studies focused on varied addictive or dependency-producing

substances--especially opiates, alcohol, and tobacco. In addition,

a variety of disciplinary, theoretical, and clinical perspectives

are represented.

The first chapters deal with theory from differing perspectives.

Dr. Thomas Babor. who led the discussion on theory, presents recent

work on the utility of the drug dependence syndrome construct as an

2
organizing principle in clinical research. Dr. Donald Wesson

presents a more general review of existing theory in the substance

abuse field, and Dr. John Grabowski reviews perspectives from the

smoking literature, with particular emphasis on behavioral

approaches to explaining dependency, its treatment, and relapse.

A number of longitudinal studies are then examined for insights

into relapse and recovery. Dr. James F. Maddux led the discussion

in this area, and presents findings from a number of studies across

categories of substances. Longitudinal data presentations are also

given by Colin Taylor, who discusses a cohort of employed male

alcoholics, Dr. D. Dwayne Simpson, who reports long-term findings

for opioid addicts treated in community-based programs, and Dr.

Timothy Baker, who presents a data on clients treated for tobacco

dependency.

The third group of chapters focus on the theme, "understanding

relapse and recovery," and are primarily concerned with controlled

and interpretive studies of short term treatments. Discussion in

this area was led by Dr. Sharon M. Hall, who presents findings on

relapse among opiate, alcohol, and tobacco clients treated in

short-term programs (under 30 days) and followed weekly

thereafter. Dr. William McAuliffe reports findings on relapse

among opioid addicts who were discharged as completing treatment

and abstinent. Dr. Robert Hubbard provides a useful examination of

drug abuse patterns at admission to treatment, and patterns of drug

use after treatment, for a large sample of clients, and raises

interesting questions as to how to view "relapse" when multiple

drug use is the prevailing pattern and when drug substitution

(licit or illicit) occurs after treatment. Dr. George Bigelow

examines relapse to cigarette smoking (and intervention to prevent

relapse) among a sample of patients who suffered myocardial

infarction, further exploring the insights which are available to

the drug abuse field from studies of relapse to tobacco smoking.

Clinical implications of existing research on relapse and recovery

research are addressed in a paper by Dr. Bruce Rounsaville.

Finally, a series of recommendations based on the deliberations of

the above-mentioned authors and other participants was developed,

and is presented in the concluding chapter of this monograph. The

meeting was jointly chaired by the authors of this chapter.

REFERENCES

Duckitt. A.; Brown, D.; Edwards, G.; Oppenheimer, E.; Sheehan, M.;

and Taylor, C. Alcoholism and the nature of outcome.

Br J Addict 80:153-162, 1985.

Joe, G.W.. and Chastain, R.L. Onset, continuation, and

termination of heroin addiction. In: Heroin Addiction: 12

Year Posttreatment Followup Outcomes, Symposium conducted at

the meeting of the Southwestern Psychological Association, New

Orleans, 1984.

3
Marlatt. G.A. A cognitive-behavioral model of the relapse

process. In: Krasnegor, N.A. (ed.) Behavioral Analysis and

Treatment of Substance Abuse, National Institute On Drug Abuse

research monograph no. 25 (Washington: U.S. Govt. Printing

Office 1979).

Simpson, D.D.. and Sells, S.B. Evaluation of drug abuse

treatment effectiveness: Summary of the DARP follow-up

research. NIDA Treatment Research Report (Washington: U.S.

Govt. Printing Office 1982).

Simpson. D.D.; Joe, G.W.; and Bracy, S.A., Six year follow-up of

opioid addicts after admission to treatment Arch Gen

Psychiatry 39:1318-1323, 1982.

Waldorf, D. Natural recovery from opiate addiction: Some

social-psychological processes of untreated recovery. J Drug

Issues 13(2):237-280, 1983.

AUTHORS

Frank M. Tims, Ph.D.

Carl G. Leukefeld, D.S.W.

National Institute on Drug Abuse

5600 Fishers Lane

Rockville, Maryland 20857

4
Theories of Relapse and Recovery

and Their Implications for Drug

Abuse Treatment

Donald R. Wesson, Barbara E. Havassy, and David E. Smith

Psychotherapists, drug abuse counselors, treatment program planners, and

researchers have theories about what relapse is, why it occurs, and how it is

prevented. Such theories are important because they shape the treatments

provided to drug abusers. For example, a therapist who believes that drug abuse

is a chronic, relapsing disease will treat a patient who has relapsed differently

from one who views drug abuse as a secondary symptom of underlying

psychopathology. A clinical researcher who accepts a theory of inherited

endorphin deficiency will design and test treatments for relapse differently from

a researcher who believes that drug abuse is learned behavior.

In this chapter, we review selected theories of relapse and the antithesis of

relapse, recovery. We selected theories that are of current importance: those that

form the foundations of currently used treatment modalities, or those that mold

common notions about the behavior of drug abusers. We will describe the

theory, give examples of research which support the theory, and discuss how the

theory influences treatment.

Relapse can be defined as a discrete event, which occurs at the moment a person

resumes drug use. or as a process which occurs over time. In the latter view, it

may mean resumption of addiction; return to drug use of the game intensity as in

the past; daily drug use for a specified number of sequential days (e.g., daily use

for 1 week); or a consequence of the drug use, such as the return to the hospital

for further drug abuse treatment (e.g., Litman et al. 1983).

The definition of relapse may be shaded by the treatment modality and the goals

of treatment. For example, in a methadone maintenance client for whom the

only realistic treatment goal is reduction in illicit drug use, relapse generally

means resumption of frequent or daily opiate use.

Relapse rates are dependent on: (1) the definition of relapse used, (2) the

method of detecting relapse, and (3) the method used to compute them. Given

the different meanings of relapse previously stated, it is apparent that large

variations in relapse rates could result from the definition of relapse used.

Methods of detecting relapse also vary widely. In drug treatment outcome

research, an interview with the subject combined with urine testing to validate

current drug use is a common method of assessing relapse. The method is not

5
precise, however, because urine testing analytic methods vary in sensitivity, in

specificity, and in the drugs that can be detected. For example, EMIT is

extremely sensitive for morphine, marijuana, and benzoylecgonine (a cocaine

metabolite) and can detect them in urine for several days following use. Thinlayer chromatography, another commonly used screening method, is less sensitive

for these drugs and may miss some drug use which would be detected with

EMIT.

Two time frames are in common use in computing relapse rates. One ascertains

current drug use at specific time intervals following treatment termination (e.g., 1

year after the end of treatment). This does not capture intermittent drug use

unless it is occurring at the time of followup. The other method ascertains

whether there was drug use at any time during the followup period. Since drug

abusers often have periods of abstinence interspersed with use, the second

method will generally produce higher relapse rates (Pickens et al. 1985).

A final variation in computing relapse rates is in the handling of missing data.

Since investigators are unable to contact all subjects in followup studies,

assumptions must be made about subjects lost to followup. They may be

assumed to have relapsed, or they can be “replaced” by subjects who could be

located. The method of handling missing data is often not overtly specified in

reports of relapse rates; yet, it can account for considerable variance.

GENETIC THEORIES AND RELAPSE

The vulnerabilities to drug dependence that are under genetic control are usually

discussed as risk factors in developing drug dependency, but they also have a

relationship to relapse.

Adoption, twin, and animal studies provide evidence of important genetic factors

in alcoholism. The risk of developing alcoholism is closely associated with the

degree of genetic relationship to an alcoholic parent. Offspring of alcoholic

parents have an increased risk of developing alcoholism, a relationship which

holds even when the children are raised separately from each other and from the

biological parents (Schuckit et al. 1985).

The theory postulates a genetically transmitted biochemical abnormality that

predisposes some individuals to abuse of a drug if they use it. The abnormality

has not yet been identified; however, examples of altered metabolism of alcohol

in young men with a family history of alcoholism (who are assumed to be at

higher risk of developing alcoholism should they use alcohol) have been

described (Schuckit and Duby 1982). Their subjects had more facial flushing in

response to alcohol than controls without a family history of alcoholism. The

flushing in response to alcohol ingestion is similar, but less intense, to that which

occurs in some Orientals, North American Indians, and Eskimos. It is the result

of blood acetaldehyde. a metabolite in the breakdown of ethanol. The

relationship between this particular finding and alcoholism is not clear as one

might logically expect that the flushing, generally perceived as unpleasant, would

offer protection from development of alcoholism. The finding of this example of

altered metabolism in subgroups of individuals adds weight to the genetic theory.

The genetic theory explains why not everyone who drinks heavily develops

alcoholism and why people who have the abnormality are more likely to relapse

if they depart from abstinence.

6
A genetic theory has also been proposed for opiate dependence. Goldstein (1978)

hypothesized that some individuals might be predisposed to develop narcotic

dependency. He hypothesizes that a person could inherit an endorphin

deficiency. If people with the deficiency happened to use narcotics, they would

discover a “normalizing” or euphorogenic effect in excess of that experienced by

people without the abnormality. This effect would predispose them to

dependency opiates and make it harder to remain abstinent.

Implications for Treatment

Genetic theory is used to bolster the illness model of drug dependence.

Vulnerability on a genetic basis is used as a “nonjudgmental” way of explaining

to drug abusers why they cannot return to “controlled” drug use.

METABOLIC THEORIES

In the early 1960s, Dole and Nyswander were studying the metabolic kinetics of

morphine when they observed improvement in subjects’ functioning in response

to substituting methadone for morphine. Long before the discovery of narcotic

receptors, endorphins, or enkephalins, Dole and Nyswander postulated that

repeated exposure to narcotic drugs might induce metabolic changes in neurons

(Dole and Nyswander 1967, p. 22). Methadone corrected the metabolic change.

Since methadone was meeting a metabolic need of the patient, replacement

methadone therapy, perhaps lifelong, was rational and the treatment fit a medical

model (i.e., like exogenous insulin for a diabetic).

The hypothesis that exposure to narcotics produces metabolic alterations is

supported by more recent work with opiate receptors, beta-endorphin, and

enkephalins. After the discovery by Goldstein in 1971 that some neurons had

specialized recognition sites on the cell’s membrane for opiates, scientists

searched for an endogenous substance with opioid activity that would bind to the

receptor. Several endogenous substances meeting the criteria were subsequently

found: beta-endorphin, a fragment of beta-lipotropin; and two pentapeptides,

methionine-enkephalin and leucine-enkephalin. Goldstein (1978) speculated that

a relationship existed between beta-endorphin levels and heroin addiction. He

hypothesized that the use of heroin would suppress endorphin production,

analogous to feedback regulation of other hormones. Further, persistent opiate

withdrawal symptoms would result from endorphin deficiency, and protracted

narcotic withdrawal symptoms could help account for the high relapse rate among

opiate addicts.

Ho et al. (1980) provide empirical support for Goldstein’s hypothesis that betaendorphin levels are abnormal in opiate addicts. They compared plasma levels of

endorphins in heroin addicts and nondrug-using controls and found that the

mean level of immunoassayable plasma endorphin activity, which reacts with

beta-endorphin and beta-lipotropin, was reduced in the heroin addicts to about

one-third the level of the nonaddict controls.

Implications for Treatment

The metabolic theory of opiate dependence supplies support for opiate

dependency as a disease. Reduced endorphin levels of narcotic addicts provide

plausible medical reason for a relapse. Metabolic theories bolster the medical

disease model of narcotic drug abuse and provide a medical foundation for

narcotic maintenance therapy (e.g., methadone and LAAM). The endorphin

7
deficiency model also has an implication about the duration of methadone

treatment. If one supposes that the addict inherited an endorphin deficiency,

analogous to insulin deficiency in diabetics, then “replacement” could be lifelong. Many providers of methadone maintenance do not use this model. They

view the need for methadone maintenance to be temporary and the appropriate

use of methadone to be to provide a time-limited period of psychosocial

stabilization while rehabilitation occurs. Widespread acceptance of this latter

perspective has led to legislation that prohibits maintenance therapy of unlimited

duration. Typically, in the United States, opiate addicts are provided methadone

maintenance for periods of 1 or 2 years.

LEARNING THEORIES

Learning theories have been developed to explain initiation of drug use,

habituation, withdrawal, and relapse. We will restrict our discussion to the

learning theories most relevant to relapse: (a) conditioning theory, and (b) social

learning theories.

CONDITIONING THEORY

Wikler (1961, 1965, 1973) proposed the conditioned withdrawal syndrome to

explain why formerly addicted persons who appear to be “cured” of their

addiction while in treatment or in jail return to opiate use when no longer

physically dependent. According to Wikler, environmental and social stimuli

formerly associated with actual withdrawal and drug-seeking became classically

conditioned stimuli for a conditioned withdrawal syndrome. Wikler and Pescor

(1967) demonstrated a conditioned withdrawal syndrome in rats. Rats that were

no longer morphine dependent showed signs of narcotic withdrawal (e.g., “wet

shakes”) when they were returned to the cage in which they had previously

suffered narcotic withdrawal.

With Ludwig, Wikler extended the conditioned withdrawal model to alcohol

relapse (Ludwig and Wikler 1974). Over time, craving and other alcohol

withdrawal phenomena become conditioned to environmental and emotional

stimuli through temporal continuity. Once conditioned, exposure to the same or

similar stimuli would cause an abstinent alcoholic to experience withdrawal.

Some evidence of conditioned abstinence in intravenous heroin addicts was found

by Sideroff and Jarvik (1980). Eight addicts who were completing a l4-day

detoxification program were shown a 6-minute videotape depicting scenes of

heroin being prepared for injection and being injected. Compared to a control

group of two heroin users who snorted heroin and six patients who were not

drug dependent, the intravenous heroin users, while watching the videotape,

developed greater increases in anxiety, depression, drug cravings, galvanic skin

resistance, and heart rate. These investigators propose that the psychological and

physiological changes they observed demonstrated conditioned withdrawal.

Implications for Treatment

A direct application of classical conditioning is aversion treatment of alcoholism

with emetine. Patients have sessions in which they are given emetine, which

produces severe nausea and sometimes vomiting, while being allowed to smell or

taste their preferred alcoholic beverage. With repeated pairings of alcohol with

nausea, instead of the usual pleasurable feelings, alcohol loses its appeal.

8
To prevent relapse to narcotic use, Wikler (1980) proposed active extinction of

the classically conditioned abstinence syndrome and the operantly conditioned

drug-seeking behavior by eliciting the abstinence syndrome while preventing the

reinforcing effects of opiates. He predicted that repeated elicitation of the

conditioned withdrawal syndrome while the reinforcer (i.e., the relief obtained

from the narcotic) is blocked with an orally effective, long-acting narcotic

antagonist (such as naltrexone) should eventually extinguish the conditioned

withdrawal syndrome, and the drive for self-administration of narcotics should

cease.

SOCIAL LEARNING THEORIES

Social learning models of addiction and relapse acknowledge the role of classical

and operant conditioning; however, they focus on cognitive-mediated processes in

the acquisition, maintenance, and modification of behavior. The various social

learning theories complement conditioning theory by focusing on the cognitive

processes occurring between stimulus and behavior.

A general model of relapse in a social learning framework has three

components: first, the patient encounters a high-risk situation during abstinence;

second, the patient has expectations about whether the situation can be handled

without use of drugs; and third, the patient has a limited repertoire of behaviors

and skills to cope with the high-risk situation.

What follows the high-risk situation depends on whether the situation resulted in

drug use. The model holds that avoiding use leads to heightened expectations

about personal control, mastery, and continued abstinence. Using a drug in

response to the high-risk situation can lead to feelings of failure and guilt, which

can precipitate further use.

Consequences of relapse have been discussed by Bandura (1978) and Marlatt and

Gordon (1980). “Catastrophizing” (Bandura 1978) is an exaggerated or extreme

response to an occasion of use. Persons who doubt their ability to control their

use, e.g., those with low efficacy expectations, are likely to overreact or

“catastrophize” the consequences of a single lapse and view the lapse as a global

failure. The Marlatt and Gordon (1980) abstinence violation effect (AVE) is a

similar construct. It has two components: cognitive dissonance (having a selfimage as a nonuser which conflicts with the actual drug-using behavior) and

personal attribution of the transgression as a sign of weakness and failure.

Although the AVE varies in intensity, its occurrence will increase the probability

of repeating the drug use since the dissonance and the attribution of weakness

will drive behavior to reduce the dissonance.

Implications for Treatment

The work of social learning theorists contains specific formulations regarding

relapse prevention. Treatment derived from social learning theories attempts to

prevent relapse by intervening at different points in the chain of behaviors,

beginning with antecedents to the high-risk situation and extending through

actual relapse. The interventions are tailored to the particular stage in the

sequence and to the particular person.

Social learning theorists agree that a critical point of intervention is at the time

of experiencing a situation of risk. Treatment goals include fostering recognition

of the situation as one of risk, maximizing expectations of efficacy in handling

9
the situation, and enhancing the behavioral repertoire to cope with the situation.

The person is taught to recognize his or her high-risk situation and to practice

coping skills needed to avoid drug use should the situation be encountered.

Following a slip or a relapse, interventions include teaching clients how to limit

or contain an episode of drug use and how to apply cognitive restructuring.

Cognitive restructuring involves conceptualizing the episode of use as a limited

slip rather than a major disaster; analyzing the high-risk situation; and learning

new coping skills.

PSYCHOPATHOLOGY AS A CAUSE OF RELAPSE

Many psychodynamically trained practitioners view addiction as a symptom of

underlying psychopathology. Their view is based on observations that many

drug-dependent persons display a broad range of symptoms and behaviors that

match one or more DSM III diagnostic categories (e.g., personality disorders,

major affective disorders). Divergent opinions often revolve around whether the

psychiatric symptoms are the result or the cause of drug abuse. Many alcoholics,

for example, show certain personality characteristics (high extroversion and

anxiety) on the Minnesota Multiphasic Personality Inventory (MMPI). The

methodological difficulty is to determine whether the personality traits predated,

and perhaps contributed to, the development of alcoholism, or whether the

personality traits are a product of being alcoholic. The latter interpretation is

supported by prospective studies of men who later became alcoholics. The

studies found no evidence of childhood psychiatric problems or “neuroticism”

when compared to adequate control populations (Schuckit et al. 1985).

Some chemically dependent patients do, however, have severe psychopathology

which predates their drug use; and the psychopathology will persist, or become

more overt, after sustained abstinence from drugs. Referred to as dual diagnosis

(a major psychiatric disorder not caused by drug abuse combined with a

substance abuse disorder), such patients are difficult to treat in traditional

substance abuse treatment programs and often do not do well with psychotherapy

or other modes of psychiatric treatment. Many bounce back and forth between

drug treatment programs and mental health clinics or hospitals, generally creating

havoc in both.

Implications for Treatment

The theory that all substance abusers have underlying psychopathology has

practical ramifications in treatment: many therapists view the drug dependency

as a secondary symptom that will disappear when the underlying psychopathology

is adequately treated. As a consequence, they choose not to address the drug use.

A related position is that the patient is using drugs to self-medicate

psychopathology; therefore. the treatment intervention is directed at the

underlying pathology. With both of these approaches, abstinence is viewed as

evidence that the psychopathology is resolving; relapse means that the

psychopathology is not resolved.

An approach that is gaining favor is to treat the addiction as the primary

problem and to delay treatment of the overt psychopathology until a period of

abstinence has been achieved. Depression or other psychopathology may be

secondary to the drug use and may therefore resolve without specific intervention

apart from treatment of the chemical dependency, e.g., the acute depression

1 0
following cocaine use (Gawin and Kleber 1985, Smith and Wesson 1985).

Treatment of relapse would directly address the drug use.

THE ROLE OF STRESS AND SOCIAL SUPPORT IN RELAPSE

The notion that stress and social support are related to relapse is embedded in

many different relapse theories; therefore, we discuss stress and social support

separate from any specific theory of relapse.

STRESS

Reference to the role of stress in contributing to relapse is ubiquitous in the drug

abuse literature. Stress, operationalized as negative life events, is implicated in

treatment failure (Benfari et al. 1982) or as a cause of relapse (Shiffman 1982;

Marlatt and Gordon 1980; Mermelstein et al. 1983a, 1983b; Ogbru 1976). Despite

the frequent references to stress as a cause of relapse, mechanisms of this implied

relationship are not clear.

The role of stress as one of several contributors to relapse following treatment

has been well-articulated by a group of investigators associated with the Social

Ecology Laboratory (e.g., Cronkite and Moos 1980; Finney et al. 1980; Moos et

al. 1979). Finney et al. (1980) found that a large number of posttreatment

negative life events were associated with poorer posttreatment outcome in

alcoholics. Moos and Finney (1983) report negative life events more prevalent

among relapsed alcoholics than among recovering alcoholics or a matched

nonalcoholic community sample (Moos et al. 1981). The number of negative life

events at 6 months posttreatment predicted complaints of physical symptoms and

depression at 2 years posttreatment even after socioeconomic variables and level

of functioning at treatment intake were controlled (Finney et al. 1980).

Cronkite and Moos (1980) found that posttreatment stress affects alcohol

treatment outcome, especially level of depression. Among the three

posttreatment factors in their path-analysis model, stressors and coping responses

were more strongly related to outcome than family environment. More stressors

are associated with poorer outcomes. The way in which the data were collected,

however, does not make it possible to separate the stressors produced by the

relapse (e.g., separation from spouse due to return to drinking) from stressors

leading to a relapse (e.g., drinking in response to a separation).

SOCIAL SUPPORT

A dominant hypothesis in the literature is that social support functions as a

buffer to stressful life experiences--i.e., the negative consequences of stressful

life events--are mitigated by social support. There has been, however. a growing

accumulation of challenges to the buffer hypothesis (e.g., Gore 1978; Thoits 1982;

Mitchell 1984).

Another hypothesis is that social support has a generally beneficial effect,

independent of whether persons have stressful events in their lives, and that

those who receive social support. have greater well-being. In a recent review,

Cohen and Wills (1985) concluded that there is evidence consistent with both

models. According to Cohen and Wills, evidence for a buffering effect is found

when social support is measured as a resource available in response to particular

stressful events. Evidence is found for the generally salubrious effects of

support when it is assessed as the extent of a person’s integration in a social

11
network. Each represents a different conceptualization and measurement of

processes by which social support affects well-being.

Of relevance to drug abuse treatment is how social support functions in relation

to relapse. Both of the above models of support may have value in this regard.

Other important aspects of the role of support in relapse, though not necessarily

mutually exclusive, include the possible negative consequences of social support,

the issue of drug-specific versus general social support, and the role of support

from family and significant others.

Negative Aspects of Social Support

A common, though not explicit, assumption is that social support is always of

positive value. Only a few investigators (e.g., Lehman et al. 1983; Mitchell 1984;

Schaefer et al. 1981; Shinn et al. 1983) have examined the quality of social

support or acknowledge negative aspects of various forms of social support, i.e.,

there are sometimes negative consequences to having support. Negative aspects

of being involved in supportive relationships include the demands made by

others, the constraints they exert over one’s choices, the efforts required to

sustain the contact, and the disappointment often inherent in relationships when

help is needed and expected, but not forthcoming.

The potentially negative aspects of social support are acknowledged in the

addictions literature (Tucker 1979; Reed 1985). Social support can either assist in

the maintenance of abstinence or foster relapse. Some family interactions that

appear to be supportive may, in fact, promote relapse (e.g., Coleman 1980;

Stanton et al. 1982; Todd 1984). For example, smoking treatment clients who

have spouses who also smoke and who are not in treatment have a lower

probability of successfully stopping (Lichtenstein 1982).

Peer groups can also provide social support that can promote relapse. Certainly,

friends who are still using drugs are more likely to support relapse than recovery.

Empirical evidence that peer pressure can promote relapse is found in the work

of Marlatt and Gordon (1980). They report situations in which patients describe

that being offered a drug or being around others who are using, even if the drug

is not offered, were relapse precipitants for 18% of smokers (n = 35), 25% of

alcoholics (n = 70), and 34% of opiate users (n = 32).

Drug-Specific Versus General Social Support

Drug users may receive general social support, but it may not include support for

achieving and maintaining abstinence. If network members are unaware of, or

not sensitive to, the users’ problem. the support they provide may not be a

resource to cope with issues concerning maintaining abstinence. Or, if network

members also have problems with the drug, the support offered may be in the

service of relapse. This consideration of social support, general versus drugspecific, in relation to drug use and relapse is relatively new and has not received

sufficient attention.

Mermeistein et al. (1983b) explored partner support specific to smoking cessation

treatment. In the last week of treatment, after the target quit date, subjects

rated their spouses on the frequency of supportive behaviors related to smoking

cessation and how helpful these behaviors were for maintaining abstinence.

Subjects were divided into three groups at each followup point: those who never

quit, those who quit and relapsed, and those who were abstinent. At all three

12
followup points, there was significant group effect on helpfulness

scores: subjects who never quit rated their spouses’ behavior significantly less

helpful than the subjects who were abstinent or who relapsed. Differences

between relapsers and abstainers did not reach significance.

In research concerning commonaiities of relapse in three drug groups (smokers,

alcoholics, and opiate abusers) (see Hall and Havassy, this volume), the

relationship of both general and abstinence-specific social support to

posttreatment relapse was assessed (Havassy et al., in press). Subjects provided

information about the support from network members for treatment and

abstinence. They also completed measures concerning helpfulness of abstinencespecific support from a significant partner (adapted from Mermelstein et al.

1983b), general social support and negative social support. Preliminary findings

on the first 77 subjects of a sample of 230 indicate that greater general social

support predicted longer periods of abstinence following treatment for all three

drug groups. Greater experienced helpfulness of abstinence-specific support

from a partner predicted a longer time before relapse, but did not attain a .05

level of significance; greater drug use of network members and their

encouragement of drug use predicted shorter periods of abstinence.

In related work, Janis and Hoffman (1970, 1982) experimentally manipulated

abstinence-specific support from a treatment partner to maintain abstinence from

smoking. In long-term followup interviews conducted 1 and 10 years

posttreatment, they found that clients treated in pairs who were in the highpartner contact condition (daily calls for 5 weeks) were more successful in

maintaining abstinence than were clients in the low-contact or the control

condition. According to Janis (1983), high-contact partnerships meet the

following criteria of effective helping relationships: high disclosure of personal

information relevant to the problem, e.g., smoking cessation; disclosures

accompanied by mutual acceptance; reference to the antismoking norm in the

contact; and contact beyond the duration of the formal treatment.

Spouse/Partner and Family Support and Relapse

The support available from spouses, significant others, and families in relapse

prevention treatment has been explored with mixed results, i.e., support can have

both positive and negative consequences. Studies in which levels of spousal or

familial support are investigated occur most notably in the weight-loss treatment

(e.g., Brownell et al. 1978; Stuart and Davis 1972; Mahoney and Mahoney 1976)

and in the smoking-cessation literature (e.g., Mermeistein et al. 1983b). Mahoney

and Mahoney (1976) found family support to be positive; Stuart and Davis (1972)

found it detrimental to weight loss. Although there were no differences among

the groups in mean weight reduction at the end of treatment in the Brownell et

al. (1978) study, at 3 and 6 months posttreatment, subjects whose spouses had

been trained with them in behavioral weight-loss techniques lost significantly

more weight than subjects whose spouses had not been trained.

Naturally occurring marital and family support and their correlation with

posttreatment outcome have been studied by Moos and his colleagues and, more

recently, by Havassy et al. Moos and Finney (1983) report results of alcohol

treatment studies indicating that marital and familial cohesion correlated with

better outcome in several areas, including posttreatment alcohol consumption.

Havassy et al. (in press) found subjects (in three drug treatment groups: alcohol,

tobacco, and opiates) with partners had significantly longer periods before relapse

than those with no partners:

13
Implications for Treatment

As numerous studies point to the contribution of stress to relapse, therapists

should recognize that patients are vulnerable to relapse during times of stress.

Teaching techniques for coping with stress is one example of how therapists

counter the relapse potential of stressful life events.

Examples of deliberate manipulation of social support to prevent relapse may be

seen in such programs as Alcoholics Anonymous (AA), Synanon, Weight

Watchers, or drug treatment aftercare programs that emphasize or create a “buddy

system” (or sponsor). Treatment programs, especially those for obesity and

cigarette smoking, frequently establish overt support conditions to assist clients in

withstanding and overcoming stressful situations without relapse.

THEORIES OF RECOVERY

In the context of addictive behavior, the term “recovery” can mean “cure” of

addiction, “abstinence” from drug use, or “remission” of the drug-dependent state.

Theories about recovery usually describe a process of achieving and maintaining

abstinence that is not necessarily related to any specific type of treatment. These

theories reflect notions about influences of major life changes in producing and

sustaining abstinence.

MATURATION THEORY OF WINICK

Using 1955-60 data from the Federal Bureau of Narcotics registry, Winick (1962)

noted that most opiate addicts began use in their late teens and early twenties

and disappeared from the narcotics registry after age 35. From this observation,

Winick hypothesized that, by age 35, most opiate addicts “mature out” of the

problems that originally led to heroin use. After 35 years of age, they find the

drive to continue drug use not sufficiently compelling for them to continue the

life-style necessary for opiate use.

Subsequent longitudinal studies do not support the maturation hypothesis. For

example, Harrington and Cox (1979), in a 20-year followup of 51 heroin addicts,

found that only 1 was drug-free after age 40. Likewise, Vaillant (1973), in a 20-

year longitudinal study of addicts admitted to the U.S. Public Health Service

Hospital in Lexington in 1952, found that only 35% of addicts could be classified

as “matured out” by age 40.

NATURAL RECOVERY FROM OPIATE ADDICTION

Waldorf (1983) studied 201 ex-opiate addicts (half were treated, and the other

half had quit without treatment). He concluded that the concept of “maturing

out,” preconditions such as “hitting bottom,” and existential crises were not

adequate to explain the variety of recovery experiences. The ability to quit was

not necessarily related to treatment. Addicts used a variety of methods to obtain

and maintain abstinence. Those who were successful generally broke ail ties with

opiates users and created new interests, new social networks, and new social

identities.

14
TWELVE-STEP RECOVERY MODEL

Members of AA or other 12-step recovery groups use the term recovery to mean

more than abstinence from drug and alcohol: being “in recovery” implies that the

person has accepted that addiction as a lifelong, incurable disease; that the person

is participating in 12-step recovery groups; and that the person is learning to live

a comfortable and responsible life without the use of psychoactive drugs.

Additionally, a model of recovery evolving from 12-step “recovery” groups views

cessation of drug use as an active, continuing process.

Recovery groups accept that once alcohol or drug dependence has developed, the

illness will persist throughout the remainder of a person’s life. Therefore,

maintenance of sobriety requires strict abstinence, aided by continued

participation in recovery groups. When 12-step recovery group members speak

of the quality of someone’s recovery, they mean the number of meetings he is

attending, his giving the maintenance of his sobriety the highest priority in his

life, his level of comfort in living without drugs or alcohol, and the step he is

currently “working.” An important method of maintaining sobriety and

reinforcing a person’s long-term recovery is called “twelve-stepping” or helping

others with the problem.

The recovery model stresses abstinence from all mood-altering substances

(generally excluding nicotine and caffeine), and any use of drugs or alcohol is

called a relapse. Behavior may be labeled as relapse even before return to drug

use. In the recovery model, it is stressed that relapse does not happen as a

single, isolated event, but is proceeded by a period of altered attitudes and

cognitive style. Members of AA refer to this pattern of thinking as “stinking

thinking.” First, the person begins to view himself or herself as “cured” and no

longer in need of attending meetings and being constantly vigilant to prevent

relapse. The person reduces or stops attending AA or other 12-step meetings.

Next, the person questions the need to maintain abstinence from all psychotropic

drugs and eventually tries a drug, not necessarily the primary drug of abuse, “to

see” if this leads to a compulsive use of the primary drug of abuse. If it does

not, the notion that strict avoidance of all psychoactive drugs is not necessary is

confirmed. Lastly, the person “tests” his or her ability to control use of the

previously abused drug. If loss of control is not immediate, the notion of the

“cure” is reinforced, and the person is further estranged from recovery support

peers. Since the recovery model assumes that drug dependency is a lifelong

illness, the drug use is viewed as a return of the illness.

Implications for Treatment

Although many forms of treatment include or encourage their patients to

participate in AA or other forms of 12-step recovery, the participation is viewed

as a treatment adjunct. Twelve-step recovery incorporates many of the change

forces described by Waldorf in natural recovery: new social networks, new social

identity, and new interests. Many addicts, however, reject If-step involvement

because of the religious overtones. The challenge to substance abuse treatment is

finding ways to engage more patients in 12-step recovery and in creating

alternatives to harness the potent change forces active within 12-step recovery.

1 5
CONCLUSION

There is a great diversity of theory about relapse and recovery. This diversity

can be considered from both a treatment and a scientific perspective. From the

treatment perspective, the diversity has an important practical consequence:

different theoretical positions translate to different treatments and interventions.

What happens to someone who relapses depends on the treatment provider’s

response, and that depends on the theoretical model that influences the provider.

In some formulations, most notably social learning theory, a relapse can facilitate

learning about high-risk situations. In other models, a relapse may convince

people that they are unable to maintain “controlled” drug use. Thus, relapse need

not be synonymous with treatment failure.

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ACKNOWLEDGMENTS

This work was supported in part by research grant numbers ROl-DA-03082 and

R02-DA-03516 from the National Institute on Drug Abuse and number BRSG

S07-RR05755 from the National Institutes of Health.

AUTHORS

Donald R. Wesson, M.D.

Director, Substance Abuse Research

San Francisco Veterans Administration Hospital

4150 Clement Street/l16F

San Francisco, California 94 121

Barbara E. Havassy, Ph.D.

University of California, San Francisco

Department of Psychiatry

San Francisco General Hospital

1001 Potrero Avenue (7M)

San Francisco. California 94110

David E. Smith, M.D.

Director of Research

Merritt Peralta Institute

435 Hawthorne

Oakland, California 94609

19
The Drug Dependence Syndrome

Concept as an Organizing Principle

in the Explanation and Prediction

of Relapse

Thomas F. Babor, Ned L. Cooney, and Richard J. Lauerman

Common sense suggests that addictive behaviors are at once

biologically based illnesses, personality-related psychological

disorders and socially learned "bad habits." All of these common

sense notions have provided a basis for theories of addiction,

typically described in the academic literature as the medical,

psychological, and social models of substance use, respectively.

Depending on the relative emphasis given to disease processes,

self-contol, psychological vulnerability, or social learning,

common sense theory reflects the implicit assumptions ordinary

laymen have about the "problem" of psychoactive substance use.

In this chapter we will consider a theory of dependence that

contains elements of all of these common sense notions of

addiction; namely, that dependence is a socially learned,

biologically based, psychologically mediated condition that impairs

an individual's ability to exercise voluntary control over such

substances as alcohol, nicotine, and other drugs. In the process

of describing and evaluating this drug dependence syndrome (DOS)

concept, we will give special emphasis to its implications for the

understanding of both relapse to, and recovery from, a variety of

addictive disorders.

The term relapse refers to the return to substance use, following a

period of voluntary or enforced abstinence, at a level of intensity

comparible to that attained before abstinence. Recovery means

either the stabilization of abstinence, or the regular consumption

of a substance without the negative consequences previously

associated with drug use.

THE DRUG DEPENDENCE SYNDROME CONCEPT

The drug dependence syndrome concept was developed (Edwards et al.

1981) within the context of the World Health Organization's ongoing

program on nomenclature and classification of alcohol- and

drug-related problems. Previous work by a WHO Expert Committee

(1964) had recommended abandonment of the concepts of addiction and

habituation in favor of drug dependence, which was differentiated

20
into psychic and physical manifestations. Subsequent developments

in the classification of alcoholism within International

Classification of Disease-9th Edition led to the substitution of

the words "alcohol dependence syndrome" for such terms as

alcoholism and alcohol addiction. The more generic drug dependence

syndrome concept grew out of earlier formulations of alcohol

dependence (Edwards et al. 1976; Edwards et al. 1977).

The essential postulates of the syndrome concept of dependence

include: 1) the clustering of certain cognitive, behavioral, and

physiological elements which are all related to a common

psychobiological process; 2) the distribution of these elements

along a continuum of severity; 3) recognition of individual

differences in the patterning of elements according to such

influences as culture and personality; and 4) conceptual as well as

statistical independence of dependence and syndrome-related

disabilities. Although no assumptions are made with respect to the

progressiveness of the syndrome or its irreversibility, there has

been some suggestion (Edwards and Gross 1976) that very severe

alcohol dependence is not reversible. Tolerance and withdrawal can

exist in the absence of the behavioral and cognitive elements.

When this occurs, the term "neuroadaptation" is employed to suggest

that tolerance and withdrawal are not identical to the broader

phenomenon of a psychobiological dependence syndrome. Beyond the

biological changes associated with both physical withdrawal and

tolerance is the behavioral manifestation of the syndrome "in which

the use of a given psychoactive drug, or class of drugs, is given

much higher priority than other behaviors that once had higher

value" (Edwards et al. 1981).

The drug dependence syndrome (DDS) as a construct is the organizing

principle for a general theory of dependence. The core syndrome

elements include the cognitive, behavioral, and physiological

symptoms summarized in table 1. The broader dependence model,

described in detail by Edwards et al. (1981), postulates that the

initiation and maintenance of drug-taking behavior is a function of

both distal and immediate antecedent variables ranging from genetic

to social influences. The general DDS theory maintains that a

complete explanation of an individual's substance use must include

statements concerning the frequency and severity of dependence, the

kinds and degrees of disability, and the personal and environmental

influences on substance use. What ties together the elements of

the syndrome and helps to account for their interrelationships is

an often unstated set of assumptions about the learning processes

behind the acquisition and maintenance of drug dependence. These

processes include classical conditioning, operant conditioning, and

cognitive mediation.

As a theory of relapse, the DDS postulates that readdiction

liability is a direct function of the severity of the syndrome

before abstinence was begun. Relapse is portrayed as the

re-emergence of previously conditioned responses that had been

associated with substance use. Recovery, on the other hand, is

described in terms of the extinction of conditioned responses that

takes place during or after treatment. Because the theory behind

21
the drug dependence syndrome construct is a synthesis of both

general learning theory and more specific conditioning models of

dependence (Wikler 1965), it may be instructive to review related

theories of alcohol and drug abuse whose assumptions complement or

resemble those of DDS. This will provide a context for reviewing

empirical evidence supporting or refuting hypotheses derived from

DOS theory or related models.

TABLE 1

Constituent Elements of the Alcohol and Drug

Dependence Syndrome

Elements

Narrowing of the repertoire

Salience of substance-taking

behavior

Increased tolerance

Repeated withdrawal symptoms

Use to avoid withdrawal

Compulsion to use substance

Readdiction liability

Interpretation/Examples

A tendency for the drinking

or drug use to become

stereotyped around a

regular schedule of almost

continuous daily consumption

Substance use given higher

priority than other

activities, in spite of its

negative consequences

More and more of substance

required to produce

behavioral, subjective and

metabolic changes; large

amounts of substance can be

tolerated

Tremulousness, sweatiness,

nausea, etc. after short

periods of abstinence

Relief or avoidance of

withdrawal symptoms by

further substance use,

especially in morning

Subjective awareness of

craving for substance, as

well as impaired control

over quantity and frequency

of intake

A tendency for the syndrome

to be rapidly reinstated

when substance use is

recommenced after a period

of abstinence

Based on Edwards et al., 1976; 1981.

22
RELAPSE THEORIES

Behavioral psychology has provided theories linking different

elements of the drug dependence syndrome to relapse after

treatment. Wikler (1965) proposed a model of opiate relapse based

on respondent conditioning principles. In Pavlov's conditioning

paradigm, a neutral stimulus is repeatedly paired with an

unconditioned stimulus that naturally elicits an unconditioned

response. With repeated trials, the neutral stimulus takes on the

properties of a conditioned stimulus and elicits a conditioned

response. In a regular drug user, certain environmental stimuli

are repeatedly paired with pharmacologic withdrawal symptoms

arising from episodes of acute abstinence between drug doses.

These previously neutral stimuli become capable of producing

conditioned withdrawal reactions long after cessation of drug use.

These conditioned withdrawal reactions may be labeled "craving" by

the addict or alcoholic, and prompt the individual to seek relief

through substance use.

Siegel (1979) proposed a dif

conditioned craving. In his

erent mode of acquisition of

model, the environmental stimuli that

reliably predict drug effects enable the addict to make adaptive,

compensatory, physiological responses in anticipation of these

effects. These conditioned responses are opposite to the acute

drug effects and thus maintain homeostatic balance. This process

can explain the development of tolerance. Furthermore, when these

conditioned physiological responses are not followed by drug

consumption, they may be experienced as conditioned withdrawal or

craving. Thus, Wikler and Siegel used respondent conditioning to

link drug craving, tolerance, and withdrawal. Impaired control can

also be explained by this theory. The most reliable cue for drug

effects are drug self-administration procedures. The process of

"cooking up" heroin, gulping a first drink, or puffing on a

cigarette in a previously dependent individual provides a complex

of strong conditioned stimuli producing conditioned craving or

withdrawal responses. Such responses may dramatically increase

motivation for substance use and lead to a perception of loss of

control. Ludwig and Wikler (1974) suggest a slightly different

process underlying loss of control in alcoholics. They hypothesize

that loss of control represents an inability to accurately utilize

information from interoceptive cues (e.g., perceived intoxication)

necessary to regulate the rate or quantity of alcohol consumed.

Although Wikler (1965) and Siegel (1979) developed their classical

conditioning models based on opiate dependence, these conditioning

concepts have been adapted to explain alcohol dependence (e.g.,

Ludwig and Wikler 1974) and nicotine dependence (Pomerleau 1981).

An alternative behavioral conceptualization of relapse has been

proposed by cognitive social learning theorists. Bandura (1977),

writing about processes underlying all coping behavior, suggested

that coping is partially determined by expectations that one is

capable of performing a coping response. It has been suggested

that the strength of an individual's expectation regarding coping,

his or her perceived self-efficacy, influences the probability of

23
relapse after first use of a drug following a period of

abstinence. If individuals who are severely alcohol dependent also

believe that they are unable to cope with temptation after a first

drink, then rapid relapse in dependent individuals may be mediated

by their low perceived self-efficacy (Rollnick and Heather 1982;

Wilson 1978). In this view, the belief that one will lose control

after a single drink becomes a self-fulfilling prophecy.

Some theories of drug abuse derived or borrowed from traditional

reinforcement theory also incorporate a wide variety of other

explanatory constructs. Thus, while Frederick (1980) views drug

abuse as a learned behavior, personality and motivation are seen as

particularly important in bringing about relapse. In McAuliffe and

Gordon's (1980) combination of effects theory, it is the potential

for enjoying opiate euphoria, in combination with the relative

permanence of acquired reinforcers, that plays a crucial role in

relapse. In this model, long-term abstinence by addicts is

hypothesized to be facilitated by successful reintegration into

society, which provides an alternative system of rewards. Zinberg

(1980) has emphasized the influence of social settings that,

operating through such mechanisms as social sanctions and rituals,

play an active role in controlling use, even by those who at one

time have been severely dependent.

The drug dependence syndrome model may also be seen as related to

biologically-based theories which stress the ability of drugs and

alcohol to alter body biochemistry and metabolism. Dole and

Nyswander (1980) attribute relapse and the persistence of physical

dependence to residual tolerance and metabolic deficiencies induced

by opiate-type drugs. Schuckit (1980) believes that genetic

factors play a role in the physiological drive to return to drugs,

as mediated by a protracted abstinence syndrome, or through

inherited psychological vulnerabilities.

This review of theories of alcohol and drug relapse suggests that

relapse is a complex phenomenon with multiple determinants.

Although many of the theories have been developed in terms of a

single drug of abuse (e.g., alcohol, opiates), the following

learning theory principles may be applicable to relapse with any

substance: 1) classical conditioning of drug/alcohol related cues;

2) operant reinforcement of drug/alcohol seeking behavior;

3) cognitive mediation of conditioned responses; and 4) social

reinforcement of recovery-related behaviors.

EMPIRICAL EVIDENCE

Having reviewed the DDS concept, the theoretical model that it is

embedded in, and a number of related theories, we will now focus on

some of the empirical research conducted to test hypotheses

concerning the relationship between dependence concepts and relapse.

Alcohol Dependence

Several alcohol administration studies have examined the

relationship between dependence and reaction to a priming dose of

24
alcohol. Hodgson et al. (1979) found that severely dependent

alcoholics significantly increased, while moderately dependent

alcoholics decreased, the speed with which they consumed a standard

alcoholic drink 3 hours after consuming a priming dose. A

subsequent study (Stockwell et al. 1982) independently manipulated

the expected and actual alcohol content of a priming dose and found

that severely dependent alcoholics increased their drinking speed

after actual alcohol consumption, regardless of whether they were

told the priming drink contained alcohol. This suggests the

importance of internal, physiological drinking cues as triggers for

craving in severely dependent drinkers. In another priming dose

study, Kaplan et al. (1983) found that severely dependent

alcoholics were more likely than moderately dependent alcoholics to

choose an additional drink instead of a lottery ticket after a

priming dose.

Marlatt and Gordon (1980) emphasize the importance of coping skills

as mediators of relapse. Such skills may also mediate between

dependence and relapse. Litman et al. (1977) found a relationship

between the self-rated degree of alcohol dependence and the use of

specific skills for coping with potential relapse situations. More

dependent individuals tended to utilize thinking of the negative

consequences and guilt associated with drinking. They also engaged

in active behavioral avoidance of drinking-related situations more

than less dependent drinkers. However, only avoidance was judged

by them to be an effective coping strategy.

An important test of the validity and utility of the dependence

syndrome concept is how well dependence predicts treatment

outcome. Seven alcoholism treatment followup studies have assessed

individual differences in severity of dependence. In the first

such study, Orford et al. (1976) randomly assigned 100 married

males to brief advice or more intensive treatment. Both treatments

were abstinence-oriented. Sixty-five subjects and their wives were

contacted 2 years after entering treatment. Among the 26 subjects

with "good" outcomes, controlled drinkers were more likely than

abstainers to obtain low scores on a seven-item dependence symptom

scale.

The Rand study (Polich et al. 1981) followed a national sample of

treated alcoholic males for 4 years. In an analysis of 200

subjects, alcoholics aged 40 or over who had high scores on a

6-item dependence scale were less likely to be drinking with

dependence symptoms at 4 years posttreatment if they were abstinent

at an 18-month followup. On the other hand, alcoholics under age

40 with low dependence scores on admission who engaged in moderate

drinking at 18 months were less likely to be drinking with

dependence symptoms at 4 years than those who were abstinent at 18

months. For the other two groups, older men with low dependence

symptoms and younger men with high dependence symptoms, the

interaction was more complex, with marital status playing an

important role.

25
In the first analysis of alcohol dependence in female subjects

(Hesselbrock et al. 1983), 67 male and 47 female treated alcoholics

were followed after abstinence-oriented inpatient treatment. A

dependence symptom scale was significantly correlated with drinking

status at a 6 month posttreatment followup for male subjects but

not for female subjects.

Heather et al. (1983) administered the Severity of Alcohol

Dependence Questionnaire (SADQ; Stockwell et al. 1979) to 35 male

and 15 female inpatient alcoholics. Six months after

abstinence-oriented treatment, 67 percent of the subjects were

contacted. The SADQ did not significantly predict abstinence

versus drinking, and, among the drinkers, the SADQ did not predict

regular nonproblem drinking. In addition to assessing severity of

dependence at intake, subjects completed a scale assessing beliefs

about their control over drinking. This "Subjective Dependence

Scale" significantly predicted regular nonproblem drinkers among

those reporting any drinking at the posttreatment followup. These

results support the contention that a relationship between

dependence and relapse is mediated by beliefs about control over

drinking (Wilson 1978).

Litman et al. (1984) followed a sample of 194 men and 64 women

treated in an abstinence-oriented inpatient program. A 6-item

dependence questionnaire did not discriminate light/moderate

drinkers from abstainers and relapsers at a 6- to 12-month

posttreatment followup.

Foy et al. (1984) randomly assigned 62 male veterans to behavioral

inpatient alcoholism treatment with or without training in

controlled drinking skills. A five-item dependence scale was

administered at admission to treatment. All but three subjects

were followed up 12 months post-discharge. Pretreatment dependence

was significantly correlated (r=-.22) with a variable reflecting

the percentage of drinking days in which alcohol consumption was

moderate. Although this correlation was statistically significant,

the clinical significance of the prediction is questionable.

Finally, an unpublished study by Kivlahan et al. (in press)

followed a sample of 268 male veterans in inpatient alcoholism

treatment. Pretreatment dependence was assessed using the Alcohol

Dependence Scale (ADS) (Skinner and Allen 1982). Nine-month

followup interviews were completed on 78 percent of the sample.

Although the ADS did not predict amount of drinking, there was a

weak but reliable association with drinking relapse status (t=.16),

with relapsing patients obtaining higher ADS scores at admission.

In summary, at least seven studies have examined the relationship

between pretreatment alcohol dependence and posttreatment outcome.

One study found a strong relationship between dependence and

controlled drinking, but in an analysis of only 26 subjects (Orford

et al. 1976). Two other studies found that predictions based on

dependence were moderated by age, marital status (Polich et al.

1981). or gender (Hesselbrock et al. 1983). Two studies found that

26
predictions were statistically but not clinically significant (Foy

et al. 1984; Kivlahan et al., in press). Finally, two studies

found no reliable predictions could be made from dependence

measures.

There are several possible reasons for equivocal or conflicting

findings in the above studies. Perhaps there are major differences

between the various dependence scales employed. However, Cooney et

al. (1986) found that four different dependence scales were highly

correlated with one another and thus were functionally equivalent.

Various outcome measures were employed in the studies, including

relapse status, light or moderate drinking, and drinking without

dependence symptoms. Only the latter provides a true test of the

reinstatement hypothesis (Polich et al. 1981) and no study measured

rapidity of reinstatement. Finally, widely varying statistical

methods were employed in these studies. It may be necessary to

control for age, marital status (Pollch et al. 1981). gender

(Hesselbrock et al. 1983), and beliefs about control (Heather

et al. 1983) to examine the predictive validity of dependence

measures.

Nicotine Dependence

Nicotine dependence has been thought to underlie tobacco smoking.

Russell (1974) stated that there is "little doubt that if it were

not for the nicotine in tobacco smoke, people would be little more

inclined to smoke than they are to blow bubbles or to light

sparklers" (p. 793). Evidence for the role of nicotine in tobacco

smoking comes from studies of nicotine regulation, tobacco

tolerance, and tobacco withdrawal phenomena.

Jarvik (1979) asserted that tolerance to tobacco products has been

clearly demonstrated in both humans and in animals. A tobacco

withdrawal syndrome has been identified (Shiffman 1979) with much

individual variability but some consistent patterns. Objective

indicators of the withdrawal syndrome include changes in EEG and

cardiovascular function, decrements in psychomotor performance, and

weight gain. Subjective symptoms include irritability, anxiety,

inability to concentrate, insomnia, and craving for cigarettes.

Although Shiffman (1984) has more recently questioned the

importance of withdrawal symptoms in promoting relapse after

smoking cessation, others have suggested that managing these

symptoms may be crucial to the maintenance of nonsmoking (Jarvik

1979).

Investigators have attempted to measure individual differences in

smokers' degrees of nicotine dependence. The most widely used

measure of smoking dependence is dosage, measured by self-reported

smoking rate, serum nicotine, or its metabolite cotinine. Studies

that used biochemical measures of dosage reported more consistent

relationships between dosage and tolerance, withdrawal, and

cessation success (Hughes 1984). For example, Hall et al. (1984)

followed 114 smokers in a behavioral smoking cessation clinic.

Although self-reported pretreatment smoking rate, self-reported

27
nicotine dose per day, and cotinine level predicted abstinence

status up to 1 year after treatment, cotinine level was found to

account for more variance in outcome than the other measures.

Since the half-life of cotinine is approximately 20 hours, blood

levels of cotinine may provide an accurate index of daily nicotine

intake.

Several questionnaires have been used to assess dependence

phenomena related to smoking. Fagerstrom's (1978) "Tolerance

Questionnaire" has been validated against physiological measures of

withdrawal (temperature change) and tolerance (heart rate response

to smoking). Other studies have failed to replicate the

relationship of the questionnaire to withdrawal and tolerance

(Hughes and Hatsukami 1983). Shiffman and Jarvik (1976) developed

a questionnaire to measure withdrawal reactions. Pomerleau et al.

(1983) found that heavy smokers reported more withdrawal symptoms

on this questionnaire than light smokers after overnight cigarette

deprivation.

A crucial test of the clinical value of the dependence construct is

to demonstrate that dependent smokers are especially likely to

benefit from dependence-based treatment. Two treatment procedures

have recently been developed that take nicotine dependence into

account. Monitored nicotine fading is a behavioral procedure

wherein subjects switch to cigarette brands with progressively

lower nicotine content (e.g., Foxx and Brown 1979). Nicotine

chewing gum is a pharmacological approach. We are not aware of any

research showing that dependent smokers are especially responsive

to nicotine fading procedures. But at least seven studies have

examined the relationship between dependence and response to

nicotine chewing gum. Two studies using dosage (Brantmark et al.

1973; Hall et al. 1985b) and five studies using the Fagerstrom

questionnaire (Christen et al. 1984; Fagerstrom 1982; Hall et al.

1985a; Hughes and Hatsukami 1983; Jarvik and Schneider 1984) found

that dependent smokers had higher quit rates on nicotine gum than

without the gum, while nondependent smokers had similar quit rates

with or without nicotine gum.

Opiate Dependence

Although no specific research has been conducted to test the

predictive validity of the DDS concept in samples of opiate

addicts, there is considerable evidence for the existence of

syndrome elements in the cycle of addiction and relapse observed In

chronic opiate users. Donegan et al. (1983) and McAuliffe and

Cordon (1980) have reviewed the literature and concluded that:

1) opiates have a high potential to serve as reinforcers;

2) repeated administration of opiates typically results in the

development of pronounced tolerance and physiological dependence;

3) stimuli associated with habitual administration can elicit a

variety of compensatory or withdrawal effects; and 4) former heroin

addicts are especially vulnerable to relapse when in stressful

situations. However. in one of the most extensive tests of

Wikler's notion of conditioned abstinence, Meyer and Mirin (1979)

28
did not confirm the hypothesis that opiate craving is internally

signaled by the unpleasant effects of withdrawal. Rather, craving

was most likely when subjects had cognitive expectancies about the

availability of heroin. Furthermore, Chaney et al. (1982) reported

that only 16% of 38 opiate relapse episodes could be attributed to

conditioned withdrawal defined as negative physiological states not

associated with prior substance abuse.

In summary, the empirical evidence suggests that severity of

dependence may be an important determinant of relapse to use of

alcohol, opiates and tobacco, but further research is needed to

confirm this hypothesis. The severely dependent person is likely

to have a narrow range of effective coping strategies. He or she

may experience conditioned craving or withdrawal symptoms,

especially after a priming drug dose. Such a person is also likely

to have little belief in his or her ability to control consumption

once it is started.

EVALUATION AND CRITIQUE

Before attempting to evaluate the adequacy of the DDS construct as

an organizing principle for a theory of relapse behavior, it will

be important to consider briefly the more general issue of minimal

standards for establishing a theory of relapse. Modern behavioral

science derives many of its methods and assumptions from the

principles of natural science. These include the requirements

that: 1) the theory leads to empirical predictions which can

determine its validity by their confirmation; 2) the terms in the

predictions be operationally defined and the conditions clearly

specified; and 3) the possibility exists to disprove the theory.

These minimal criteria, accurate prediction, public verifiability,

and scientific falsifiability, are complemented by such

characteristics as breadth, depth, uniqueness, elegance, and

clinical utility. For example, theories whose derivations permit

causal control over important aspects of behavior are more useful

than those that do not. Also desirable are theories that encompass

many empirical phenomena and derive predictions from a relatively

parsimonious set of assumptions. First, it should be noted that

the DDS model is fairly representative of other theories in the

general field of alcoholism and drug dependence (Lettieri et al.

1980). In its broader outlines, it is rather loosely constructed

and incorporates a wide variety of antecedent and explanatory

variables. Where it differs from other theories is in its attempt

to tie together biological, psychological, and social variables in

a network of reciprocal causation using concepts borrowed from

learning theory. The syndrome elements are the building blocks of

the theory. The syndrome concept, borrowed from clinical medicine,

is the basis for defining the shape and boundaries of dependence.

Learning theory is the glue that holds the model together and

provides the derivation of postulates and hypotheses.

With regard to the criterion of accurate prediction, DDS theory and

related learning theory models do suggest rather clear hypotheses

about mechanisms of relapse. They are less clear about the

29
implications of high dependence for recovery, except to suggest

that with increasing time, the conditioned responses evoked by

environmental and interoceptive stimuli should be extinguished,

thereby making abstinence more likely and easy to maintain.

A major problem with the criterion of public verifiability is the

operational definition of syndrome elements and related

constructs. The. Alcohol Dependence Syndrome was postulated as a

provisional formulation, and was based on a combination of clinical

experience and theoretical speculation (Edwards et al. 1976,

1977). The Drug Dependence Syndrome model was formulated in the

context of a discussion of nomenclature and classification of

alcohol- and drug-related problems (Edwards et al. 1981). This

should be kept in mind when considering the model as a formal

theory of dependence.

The definition of several syndrome elements presents difficulties.

Research attempting to establish operational measures of the

elements that are reliable and valid is needed. "Narrowing of the

drug-taking repertoire" suggests that the individual's drug use is

stereotyped and functionally autonomous. The element "salience of

drink- (drug-) seeking behavior" contends that priority in

maintaining drug intake supplants the individual's attention to

personal, interpersonal, and social obligations. Both of these

elements describe gross, macro-level behavioral phenomena that

represent much more complicated levels of analysis than the

elements of withdrawal and tolerance. "Subjective awareness of

compulsion to drink (take drugs)" is another element that is

somewhat unclear. For example, it is uncertain whether the

individual ingests the drug and loses control, or decides not to

exercise control over the amount of the drug that is taken into the

system. The inclusion of a cognitive element in the dependence

syndrome raises questions about the role of private experience in a

scientific theory of behavior. Given the general acceptance of

subjective feelings and thoughts in contemporary behavioral

science, their inclusion in this model is no more problematic than

other cognitive behavioral theories that emphasize the importance

of cognitive mediation. The final element, reinstatement of the

syndrome, is a characteristic rather than an element of the

syndrome, and can only be operationalized by a synthetic

combination of the syndrome elements. When considered in this way,

reinstatement becomes an hypothesis to be tested under specific

conditions, such as when a "slip" occurs for an abstinent

alcoholic.

The operationalization of elements (i.e., establishing loose

parameters) of the DDS construct has just begun to occur and has

already been subject to a variety of disciplinary interpretations.

Whether these elements do in fact cluster, and are interrelated

aspects of the same syndrome can only be borne out by further

research.

Critics of the dependence syndrome concept have contended that

owing to its phenomenologlcal ambiguity, it is but another

30
restatement of the traditional disease concept (Shaw 1979). The

argument that the syndrome is a restatement of the disease concept

stems from the tendency to interpret the syndrome primarily in

psychobiological terms. Syndrome proponents have provided a less

than complete explanation of both behavioral and subjective

mechanisms underlying the syndrome. Edwards and Gross (1976) do

state that should a clinician opt to use the syndrome for

diagnostic purposes, a "conservative approach is generally the most

responsible, and that abstinence is normally the safest choice of

goal" for treatment. Critics have seized this position as

reflective of syndrome proponents' orientation toward abstinence

and the traditional disease concept. Syndrome proponents, however,

dismiss the disease concept since it is too confused for empirical

inquiry. In summary, the strength of the DDS is also its weakness,

in that ambiguity prompts attempts to establish operational

definitions of the elements, and also fosters idiosyncratic and

unidiscipllned efforts to define syndrome elements and the syndrome

itself. Attempts to examine and study the syndrome have opened a

heretofore dichotomously labelled (i.e., alcoholic versus not

alcoholic, dependent versus not dependent) area of clinical

inquiry. Regardless of Edwards' and Gross' formulation, interest

in drug dependence has been engendered and has suggested avenues

for research into biological, behavioral, and situational

determinants of relapse.

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ACKNOWLEDGMENTS

The writing of this paper was supported by grants from the National

Institute on Drug Abuse (R01 DA 3814) and the National Institute on

Alcohol Abuse and Alcoholism (T32 AA 07290, P50 AA 03510, and KOl

AA 00025).

AUTHORS

Thomas F. Babor, Ph.D., M.P.H.

Ned L. Cooney, Ph.D.

Richard J. Lauerman, Ph.D.

Department of Psychiatry

University of Connecticut Health Center

Farmington, Connecticutt 06032

35
Acquisition, Maintenance,

Cessation, and Reacquisition: An

Overview and Behavioral Perspective of Relapse to Tobacco Use

John Grabowski

Tobacco use is a prototypic case of drug dependence and an appetitive habitual

behavior. It encompasses many of the phenomena studied in the behavioral

pharmacology laboratory and related clinical settings. It also has been studied by

scientists and clinicians representing a wide range of other theoretical and

disciplinary orientations. Acquisition, maintenance, and treatment of tobacco use

have obvious elements of, and commonalities with, drug self-administration

models, schedule induction models, coping models, social learning models. and

others. More important, it represents a spectrum of biobehavioral disorders

which ultimately and unfortunately produce patients for practitioners of

behavioral or medical disciplines. Therefore, a precise and systematic analysis of

tobacco use presents a unique opportunity to contribute to both the treatment of

drug abuse disorders and the broader area of behavioral medicine disorders.

Despite the extensive literature and considerable interest in the area, the apparent

success in the treatment of tobacco use has not been notable. This chapter will

include consideration of various theoretical perspectives, a basic behavioral

analysis, and a view toward future research and treatment strategies.

THEORIES OF ACQUISITION, MAINTENANCE, CESSATION, AND RELAPSE

Wesson et al. (this volume) have argued that “having a theoretical framework is

important in providing drug abuse treatment because treatment guided by

theoretical constructs results in clear decisive interventions.” It is not at all clear

that this has been the case in drug abuse treatment, despite the fact that theories

are myriad and proliferating. For example, a volume titled Theories on Drug

Abuse (Lettieri et al. 1980) presented 43 alternative theories. These theories were

grouped into four areas, including “relationship to self,” “relationship to others,”

“relationship to society,” and “relationship to nature.” Nevertheless, none of these

theories can be viewed as amply descriptive or predictive to greatly enhance

treatment and, thus, they do not achieve the goal proposed by Wesson et al.

Instead, a sound set of practical therapeutic recipes with parallel tracks and

options based on the best available data, may be what is needed to guide

treatment of drug abuse in many of the settings in which it is practiced.

36
Thompson, citing Claude Bernard, has noted vis a vis theories, that

these men start, in fact, from an idea which is based more or less

on observation, and which they regard as an absolute truth. They

then reason logically and without experimenting, from deduction

to deduction they succeed in building a system which is logical

but which has no sort of scientific reality . . . the mind becomes

bound and cramped by the results of its own reasoning; it no

longer has freedom of action and so lacks the power to break

away from that blind faith in theories which is only scientific

superstition. (Thompson 1984, p. 213)

It can readily be argued that “theory” in its least intrusive form might be useful.

Unfortunately, theory builders in the drug abuse arena have not sought to be

unobtrusive, as even the casual reader of Lettieri et al. (1980) would discern.

And, in the area of etiology and treatment of tobacco use, Leventhal and Cleary

(1980) as well as Cummings et al. (1980) have argued that there is a need for

theory. Ironically, Leventhal and Cleary decry the schism between various

research perspectives and the failure of integration without noting that this is a

common result of building theoretical edifices.

Generally accepted is the view that the benefit and merit of theories resides in

the generation of studies which, in turn, will support or refute their premises.

One might question whether our techniques are so poor, and our science so weak,

that we can only do battle in the arena of the straw men (people?) concocted

from current theoretical models. Rather, at this point, a robust description

derived from sound research may be of the greatest utility. In turn, there is a

need to recognize conditions, well beyond the scope of any therapeutic

intervention, which contribute substantially to the problems of tobacco use.

Lichtenstein (1982) observed that the tobacco literature is so vast that inclusive

surveys are untenable. It is now also the case that theoretical analyses become

unduly encumbered in attempts to account for the manifold results with many

disparities. Since theories can generate research far beyond the need, they may,

at this point, hinder rather than breed success in the therapeutic domain. More

data in the realm of basic research may well be of value since it has been from

this source that much of the current precision in therapeutics has arisen. In

summary, what is needed more than a “good theory,” as proposed by some

authors, is a good description of the behavior as provided by Lichtenstein (1982),

Lichtenstein and Brown (1982), and others, and in turn, an integrated therapeutic

strategy based on the data.

A PARSIMONIOUS DESCRIPTION OF ACQUISITION,

MAINTENANCE, AND ELIMINATION OF TOBACCO USE

A question has emerged, particularly recently, as to why the study of tobacco use

is relevant to the issue of drug abuse. There are several often-stated reasons.

First, tobacco use in its several forms is a clear public health problem and thus,

for direct clinical-scientific reasons, it is worthy of study. Second, as previously

noted, the study of tobacco use is in many respects a prototypic, healthimpairing, appetitive, habitual behavior which has commonalities with a wide

range of other biobehavioral (as well as social-behavioral) disorders (Pomerleau

1979, Levinson et al. 1983). And third, tobacco use generally, and smoking in

particular, has all of the characteristic elements of other forms of drug abuse.

That is, the rate and pattern of the behavior itself, the paraphernalia associated

37
with use, and the pharmacological agent, give rise to the view that this is a

prototype which will likely give considerable insight into drug abuse and other

disorders (see Henningfield 1984).

ACQUISITION

The theoretical literature (e.g., Lettieri et al. 1980) provides a broad range of

options in specification of the generative conditions for acquisition of drug

abuse. Distilled, these have several essential elements (rarely clearly stated), for

example, physiological, behavioral (including “cognitive” components), social,

environmental, and pharmacological factors, and their interactions.

The conditions antecedent to sustained drug use include social factors, commonly

in the form of friends and family; environmental factors, including drug

availability; and biological factors, including the possible predisposition to the

reinforcing properties of the pharmacological agent itself. However, the relative

contribution of these factors to an individual’s first use of tobacco varies.

Clearly, the event of initial use is multiply determined, and results from the

interaction of diverse factors to which most people in Western culture are

exposed from a very young age. Perhaps a major environmental difference for

young people is the frequency of tobacco use in their immediate environment by

parents and siblings. The importance of the presence of tobacco-using parents in

the home may be twofold: first, there exists a basis for learning through

modeling; and second, in view of recent data on passive smoking, it is likely that

there could be gradual evolution of tolerance to the aversive properties of

cigarette smoke through chronic low-grade exposure.

While acknowledging that offspring of those who do not use tobacco do initiate

use, and that the converse is true as well, most learning models would predict

“imitation” or “modeling” to be a major antecedent to initial use. In the absence

of this major risk factor (Surgeon General’s Report, 1979), there exist the range

of early exposures serving as sufficient alternative stimulus arrays which are

setting conditions for the initiation of smoking. They exist in the media, in the

behavior of peers, and the general evidence of acceptability of tobacco use in

public settings. (In this regard, the development of isolated smoking salons in

public environments might have benefits well beyond those typically suggested.)

As Lichtenstein has noted (1979, 1982), there are more than adequate numbers of

descriptions of this acquisition process, and an abundant supply of speculative

accounts. However, it is patently clear that the complex and intricate theories in

this domain have contributed little more to the development of an understanding

of the acquisition process.

Perhaps the most parsimonious description of tobacco and nicotine use derives

from animal and clinical laboratory studies. These data can be succinctly

summarized. When nicotine is made available on a response-contingent basis and

delivered via an indwelling intravenous catheter, persistent drug selfadministration evolves. As often described in the behavioral pharmacology

literature, this simple demonstration indicates the lawfulness of the process of

drug self-administration. The appropriate direct parallel of inhalation has also

been studied in both the animal and human laboratories and clinical settings (e.g.,

Jarvik 1967; Griffiths et al. 1982; Gust and Pickens 1982). To paraphrase and

extrapolate to the natural environment: when tobacco is made available and

when the conditions for use are established through diverse stimulus conditions--

38
including advertising, parents, peers, and others--the teenager engages in selfadministration.

A particularly interesting relationship illustrating the parallels between nicotine

self-administration in the laboratory and tobacco use in the natural environment

is the finding by Salber and Abelin (1967) indicating that 85% to 90% of those

who smoke four cigarettes become chronic smokers. In the laboratory setting,

following initial exposure (at times provided by an investigator-initiated priming

dose--peer pressure?), the probability of acquisition of self-administration is

similarly high,

The self-administration model and the extensive database on the importance of

specific reinforcement schedules and stimulus conditions as determinants of drug

use promulgated by behavioral pharmacologists, is not widely accepted by those

who theorize on drug abuse, its treatment, or relapse. Nevertheless, these data

point to the essential ingredients of a powerful, manageable, and perhaps most

important, useful model of acquisition of tobacco use (Henningfield 1984).

Further microanalysis of environmental determinants of initiation of tobacco use

for the individual is not necessary here, and there are ample sources on which

the scientist or clinician can draw. There is clearly a substantive database

indicating the power of a range of environmental factors as contributors to the

initiation of use.

MAINTENANCE

Maintenance of tobacco use has also been the focus of complex theoretical

machinations. Oral gratification and other descriptions readily succumbing to

Occam’s razor are numerous. Lichtenstein (1979, 1982) has described the general

factors associated with maintained use of tobacco. Frederiksen (1979) has

similarly listed factors in the context of controlled smoking, and Pomerleau

(1979) has provided an overview of factors within the context of reviewing

commonalities of what he terms self-management disorders. More recently,

Pomerleau and Pomerleau (1984) have specified a series of neurotransmitter

alterations and physiological effects of nicotine administration and abstinence

which are correlated with well-documented behavioral manifestations.

Henningfield (1984) has provided an excellent comprehensive review directed at

summarizing the behavioral pharmacology of cigarette smoking. Viewed in

combination, the preponderance of evidence points to orderly and systematic

patterns of sustained tobacco use modulated by an array of environmental and

pharmacological factors. And, this evidence stands without recourse to elaborate

hypothetical constructs.

Clinical and animal laboratory studies have provided clear data on the role of

both operant and classical conditioning in the maintenance of drug use generally

(e.g., see Grabowski and O’Brien 1981) and tobacco specifically (Pomerleau 1979;

Pomerleau and Pomerleau 1984). It is clear that the dominant active

pharmacological agent in tobacco, nicotine, can serve to strengthen and maintain

behavior, which leads to its administration for nonhuman and human subjects

alike (Goldberg et al. 1981; Henningfield and Goldberg 1983a and 1983b). Use

of nicotine via smoking or smokeless tobacco is more complex for humans in

their natural environment, not so much for the character and pattern of selfadministration which closely resembles the behavior engendered in the laboratory,

but for the manifold interactions between smoking, other behaviors (including

39
concurrent use of drugs such as caffeine or ethanol), and other, abundant

environmental conditions and events, i.e., the context.

Fortunately, laboratory research with both humans and animals has provided a

means for systematically examining both behavioral and environmental factors.

The relative power of environmental stimuli as determinants of drug-taking has

been amply demonstrated (e.g., Goldberg and Shuster 1967, 1970; Schuster and

Woods 1968; Davis and Smith 1974; Thompson et al. 1971; Carnathan 1977;

Goldberg 1973), and these factors have been repeatedly referred to as

contributing to relapse (Wikler 1965, 1974, 1977; O’Brien et al. 1974, 1975, 1977,

1980; O’Brien and Ternes 1977; Childress et al. 1985). Only a few of the

relevant studies have been cited, but the potential contribution of these factors in

sustained drug use is clear. There can be little question of their importance and

influence in the natural environment.

While characteristics and patterns of self-administration evidenced in

experimental settings parallel those under natural conditions, the cumulative

frequency of dosing by inhalation through cigarette smoking may be far beyond

that studied for any agent in laboratory settings. As Pomerleau has noted, the

average one-pack-per-day smoker emits puffing behavior 70,000 times per year.

Few other behaviors are so regularly emitted and reinforced. In turn, few other

reinforcers and the antecedent behaviors are so regularly associated with a

plethora of environmental stimuli which then further contribute to maintained

drug-taking. These relationships have been summarized by Lichtenstein (1982),

Henningfield (1984), and others. Thus, there are both laboratory-based accounts

(e.g., Nevins 1979) and clinical data that predict the strength of maintained

tobacco use without reference to elaborate theoretical constructs.

It must be emphasized that the strength and persistence of a behavior determines

the ease or difficulty with which it will be changed. A satisfactory case can be

made that a range of simple appetitive behaviors occurring in diverse

environments with great frequency are particularly impervious to modification.

This has been evidenced by the seeming lack of success of the techniques used to

alter these behaviors, including tobacco use.

TREATMENT AND CESSATION

Tobacco use cessation efforts are numerous and diverse. Grabowski and Hall

(1985) defined five interdependent levels and modalities of cessation efforts,

including public intervention or information campaigns, self-help programs,

group support programs, individualized behavioral intervention programs, and

pharmacological interventions. Pechacek (1979) outlined the categories somewhat

differently, but the parallels are clear. The origins of the programs vary. Some

have evolved from the standard strategies of publicly addressing health problems,

while others have been derived from rather elaborate theoretical schema (e.g.,

Marlatt 1982, 1985) and still others have derived from precise clinical science

(e.g., Hall et al. 1984, Hall and Miller 1985).

Historically, the success of drug abuse cessation efforts generally, and tobacco

use cessation in particular, have not been notable. Furthermore, in the area of

smoking the results appear to many to be less impressive since tobacco use is

traditionally viewed, even by some clinicians, as a trivial habit. Like all “habits,”

it is considered subject to modification through a modest infusion of “essence of

will power.” In any case, the lack of successful interventions was best

summarized, and perhaps “justified,” by the data of Hunt et al. (1971) as depicted

40
in the widely published figure comparing reacquisition of heroin, alcohol, and

tobacco use after treatment (“relapse”). Treatment success, as defined by

continued abstinence at 3 to 12 months, has hovered between 20% to 30%.

Lichtenstein (1982), Pechacek (1979), Pomerleau (1979), Marlatt (1985), and

others have suggested that behaviorally based techniques--(variously labelled

behavioral intervention, behavior modification, behavior therapy, and the like)--

have reached inherent limits. As Marlatt (1985) indicated (following

Lichtenstein’s 1982 observation), one consequence of limited success was an

increase in the use of multimodal strategies which proved to be no more

successful than the simpler strategies. However, it should be noted that Marlatt

enunciates this view in the context of the presentation of an elaborate model of

“Relapse Prevention” not dissimilar from many of the multimodal programs. In

addition, it should be noted that Leventhal and Cleary (1980). in their thorough

review, indicated that increments were evidenced in some, but not all,

multimodal programs. It is interesting that despite elaboration and reiteration of

essentially the same basic techniques, smoking cessation program success rates

remain inexplicably low given the energy invested therein, although there are a

few notable exceptions. For example, in two separate programs, Hall and Killen

(1985) have described results with combinations of “skills training” and nicotine

gum which approach the 50% success rate at 12 months. The focus of the

programs appears to be a few essential elements derived from the extensive

repertoire of clinical behavioral scientists with special attention given to the

behavioral and pharmacological consequences as well as correlates of tobacco use

and cessation.

While multimodal treatments have been generally criticized, some of the

criticisms are specific. For example, Lichtenstein (1982) noted that at times, the

combined treatments were made up of components which had not been

demonstrated to be effective. Combined treatments may well be effective, as

demonstrated by Hall and Killen (1985) and Hall et al. (1984). The combined

treatments may be additive or synergistic; however, these greater changes will not

occur because of their combination per se but because of the inherent

effectiveness of the combined treatments themselves. Several other points

concerning treatment are worth noting. As cited above, there has been extensive

research concerning the role of stimulus factors established through operant and

classical conditioning and there has been extensive comment in the literature on

this issue. However, no program has adequately dealt with the role of these

stimuli in intervention. Indeed, there has been greater attention to these events

in treatment for alcohol and opiate abuse (e.g., Marlatt 1985, Childress et al.

1985), and yet the role of such stimulus factors in tobacco use may be greater

given their ubiquitous character.

A second major concern in treatment is linked to the duration and strength of

the behavior in question, as discussed earlier. It is impressive that treatment

programs are effective to the extent that they are, given their brevity and lack of

intensity compared to the usual tobacco use history.

A third point of interest is that the effectiveness of treatment programs might be

greatly enhanced if implementation were in conjunction with naturally occurring

and related environmental events (e.g., see Bigelow, this volume). In the main,

interventions are established in special settings under conditions which make

compliance and attendance at treatment sessions difficult. Alternatively, they

take the form of “self-help” programs of uncertain utility.

41
Initiating treatment at moments of other health-related interventions (Bigelow,

this volume) or in relation to work or other environments might well convey

greater strength to many therapeutic strategies. There are both behavioral

markers and environmental conditions providing more suitable points for

interventions. The potential for altering critical features for tobacco use

cessation goes well beyond other drug abuse treatment, in part because of the

general social tolerance of the behavior. While one cannot, for example, publicly

announce and implement a cocaine treatment program at 12:30 p.m. each day on

company premises and expect high levels of voluntary attendance, tobacco use

cessation programs have been established in this fashion. In brief, treatment

programs have not consistently attended to major obvious behavioral and

environmental features which might enhance success.

REINITIATION, REACQUISITION, OR RELAPSE

The focus of this volume is relapse (to drug use). There are two terminological

issues which cloud the discussion in both philosophical and practical terms. The

application of the word to the behavioral phenomena falling under the rubric of

“relapse” is unfortunate, as noted by Marlatt (1985). It connotes, coincident with

its origins in a medical model, a dichotomous state. One “has” the “disease” of

drug abuse or one does not. The conceptual error is evident in the phrasing.

One “has” the disease or condition of diabetes, cholera, trisomy 21, or hepatitis,

but one engages in the behavior of drug abuse. Behavioral factors of drug abuse

generate ‘physiological consequences that a patient “has,” and they must be

medically treated. However, it is well documented that these treatments do not

ameliorate the original behavioral disorders. Thus, one can relapse to illness, but

relapse to drug abuse is an inept articulation of the problem. Marlatt (1985)

redeems “relapse” through the use of a corollary definition, although it would be

most appropriate to place it in the same pasture with the word addiction, which

has also grown ungainly with age (Grabowski and O’Brien 1981).

It appears that behavior and debilitating consequences of drug abuse are best

described by the previously considered behavioral-pharmacological model and

terminology. The individual acquires the behavior of drug use (in this case

tobacco use) as previously noted. This behavior is strengthened and maintained

by interacting behavioral pharmacological and environmental factors. It is

eliminated as a consequence of one or more levels and models of intervention

(Grabowski and Hall 1985, Pechacek 1979).

Interestingly, laboratory models for the study of drug abuse acquisition and

maintenance parallel closely the human case in the natural environment. In

addition to the studies already cited, there has been explicit attention devoted to

analysis of naturally occurring behavioral sequences such as those represented by

concurrent administration of ethanol, opiates, amphetamines, caffeine, and other

agents with tobacco use (Griffiths et al. 1976; Kozlowski 1976; Schuster et al.

1979; Henningfield and Griffiths 1981; Mel1 et al. 1980a, 1980b; Mintz et al.

1981).

Ostensibly, it is in the area of elimination and reacquisition of the behavior that

the behavioral pharmacological analysis derived from the laboratory appears not

to be applicable because of the conditions under which treatment is usually

implemented. However, there are numerous studies in which cessation of drug

self-administration has been examined inadvertently or otherwise, and this

literature has been concisely and articulately reviewed (Poling and Appel 1979).

Occlusion of an infusion catheter results in cessation of responding for drug.

42
The explicit experimental manipulation of making an infusion pump inoperative

likewise leads to cessation of responding. Administration of an opiate antagonist

or mecamylamine to the subject (human or nonhuman), self-administering

morphine or nicotine, respectively, leads to cessation of drug-taking.

“Preloading” reduces drug-maintained responding. In brief, nonavailability of a

previously self-administered drug or the functionally similar manipulation of

blocking or reducing its effect leads to abstinence.

Reestablishing conditions for self-administration by unclogging the catheter,

reactivating the infusion pump, or discontinuing antagonist (or agonist)

administration leads to reinitiation of self-administration (“relapse”). Over

successive nonavailability conditions, cessation (i.e., extinction, failure to

respond) occurs more rapidly. Similarly, reinitiation of the behavior also occurs

more rapidly within the constraints of pharmacological effects (i.e., gradual

reemergence of opiate tolerance is related to gradual reacquisition of previous

levels of self-administration). There are similarities between some of these

conditions and the elimination of human drug-taking (Poling and Appel 1979).

The discrepancies and divergence between these laboratory cases and the human

case are clear and the fundamental antecedents to reacquisition are similarly

evident. Furthermore, the problems are more evident in the case of tobacco use

than for other forms of drug use. The elaborate methodologies, models, and

theories currently evolving reside in an anomalous social and therapeutic

condition which should be considered.

Clearly, all therapeutic strategies contend with the fact that the drug

nonavailability condition exists to some degree for some drugs and is nonexistent

for tobacco use. Attending to this issue, Wikler (1965) suggested there is a need

to remove the drug user from the environment during treatment, thereby

modifying the risk of relapse. Grabowski et al. (1984) have noted that the

advantage of this strategy is obviated by the fact that when reintroduced to the

natural environment, the individual remains susceptible to the diverse stimuli

previously associated with drug use. Concurrently, it is evident, as proposed by

Childress et al. (1984), and others, that presentation and extinction of the

discriminative and conditioned stimuli during the period of removal from the

drug use environment may reduce the strength of these stimuli. This might

reduce the probability of reacquisition of drug-taking when the individual

returns to the natural environment. This strategy has not, however, been

effectively implemented. In the case of tobacco use, it may be practical to

implement, in addition to other behavioral strategies, discrete regular sessions in

the natural environment to reduce the probability of reacquisition.

It has been noted that many of the basic elements of tobacco use are common to

drug abuse as well as other biobehavioral disorders. The drug self-administration

model applies admirably to conditions of acquisition and maintenance. It appears

to apply less well to cessation and maintenance of cessation. or its inverse,

reacquisition, not because of a failure in the description but because of the

anomalous conditions under which cessation strategies are initiated and abstinence

must be maintained. Walker and Lidz (1983) have discussed this issue and

summarized it in terms of normative and control ambiguity. That is, there are

social and contextual factors which concurrently and emphatically direct use and

vigorously oppose use. In the laboratory, parallel stimulus conditions can be

established. The formal study directed at analysis of this issue has not been

undertaken. However, there are ample parallels. The prediction is readily made

that, when presented with (a) stimuli associated with the null condition (no drug

43
availability) and (b) stimuli associated with the powerful drug effects and drug

availability itself, drug-taking is highly probable. It is clear that appropriate

steps must be taken to reduce the strength of stimulus factors precipitating

reinitiation of use.

Provided with the conditions described concerning the context of precluding

reacquisition, or “relapse prevention,” several facts are evident. First, one can

delineate, as has been done with great precision and care, the conditions under

which cessation is likely to be maintained, and these discriminations can be made

along the dimension of stimulus variables, coping strategies, individual

characteristics, or social environs (e.g., Lichtenstein and Brown 1982, Marlatt

1985, Shiffman 1982, Havassy et al., in preparation). Second, based on the data

derived from these studies as well as the refinements made to date in relatively

simple but effective strategies (e.g., Hall and Killen 1985; Hall et al. 1984,

Lichtenstein and Rodrigues 1977), improved success rates are probable. In turn,

these efforts, combined with the gradual shift in perceptions concerning smoking,

if not smokeless, tobacco effects, may further enhance success rates. In brief,

the focus, albeit sometimes distorted, on the multiple factors contributing to

reacquisition can be predicted to provide gradual improvements in outcome.

Most important is that it appears that the behavioral strategies considered here

aptly describe the situation and, when judiciously and systematically applied,

they are likely to be effective.

CONCLUSIONS

The primary point of this chapter is that there has been extensive laboratory and

clinical research devoted to the analysis of behavioral mechanisms of acquisition,

maintenance and elimination of drug-taking. The results have been translated,

with varying but increasing success, to the clinic. Unfortunately, there has also

been increasing and perhaps disproportionate attention to theory development

rather than refinement of the simplest effective treatment strategy. This is not to

ignore the utility of theory in some situations. Instead, it is suggested that, at

least in the area of smoking cessation, and quite possibly in other areas of drug

abuse and biobehavioral disorder treatment, effective implementation based on

current data rather than further theory development, is needed.

Finally, the above considerations not withstanding, the major problem

confronting therapists and scientist-clinicians is the previously noted anomalous

environment in which the therapeutic strategies are devised; that is, an

environment in which tobacco use is not only legal but substantially encouraged

on one hand and deemed hazardous and unacceptable on the other hand. This

issue is not resolvable through better theory. The greatest increments in

enhancement of the diverse interventions will come less from future refinements

in the techniques (which are already quite striking in their effectiveness), and

more through changes in the social environment via legislation and public policy.

In particular, attention must be given to all of those steps which would reduce

the availability and complexity of the conditions under which the interventions

must be implemented. In the interim, those engaged in the development of more

effective interventions can perhaps take solace in the fact that the elegance and

overbuilt character of the resulting interventions will likely be extremely useful

in resolution of other diverse biobehavioral disorders.

44
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AUTHOR

John Grabowski. Ph.D.

Assistant Director

Center for the Study of Drug Development

Tufts University

Boston, Massachusetts 02111

48
Relapse and Recovery in

Substance Abuse Careers

James F. Maddux and David P. Desmond

During the 1950s it was often asserted that few individuals ever

recovered from addiction. Then, in the 196Os, Winick (1962, 1964)

produced data suggesting that approximately two-thirds of narcotic

addicts mature out of their addiction in their thirties. Subsequent long-term followup studies have pointed to a truth somewhere

between these two extremes of pessimism and optimism. With alcoholism, the concept of the incurable skid row derelict has given

way to recognition in the latter half of the 20th century that

many alcoholics achieve long periods of abstinence, sometimes enduring for a lifetime. In this report, we shall attempt to identify the major features of substance abuse careers, with emphasis

on relapse and recovery. We shall concentrate on the use of alcohol and opioids because use and abuse of these two psychoactive

substances have been studied intensively. Less information is

available about the long-term careers of persons who use tobacco,

marijuana, cocaine, and other commonly abused substances. While

we shall mainly describe patterns of behavior, we shall also comment on theory, for data without theory have restricted meaning.

We draw on three theoretical aproaches which have served to integrate and explain observations about substance abuse: 1) pharmacological theory--concepts about the interaction of exogenous

substances with body tissues and organs, especially with the

central nervous system; 2) learning theory--especially the paradigms of classical conditioning and operant conditioning; and 3)

psychodynamic theory--concepts developed from exploration of

subjective mental experience. In psychodynamic theory, it is

assumed that past experience shapes current behavior--that is,

antecedent experience has persisting consequences. This etiological assumption probably pervades most contemporary psychosocial

science. Psychodynamic clinicians and psychosocial scientists

also seem to assume that current circumstances affect behavior.

Some clinicians and scientists also find etiology in the anticipated future. Personal goals and plans seem to affect current

behavior. Thus, in a broadly conceived psychodyanmic theory,

stored representations of past experience, perceptions of current

49
circumstances, and anticipated future experience contain potential

etiological factors.

DEFINITIONS

The absence of generally accepted criteria for different levels of

substance use--for abuse, for dependence, for relapse, and for

recovery--have required that investigators develop definitions and

criteria based primarily on their own research questions and

methods. These varied criteria, plus variations in methodology,

have contributed to wide variations in reported recovery and

relapse rates, and have handicapped comparison of the findings of

different studies.

While the advent of the third edition of the Diagnostic and Statistical Manual of Mental Disorders, DSM-III (American Psychatric

Association 1980), has provided standard criteria for diagnosis of

substance use disorders, the rubrics include wide variation in

severity of the disorders. The Manual does not provide criteria

for recovery.

In this chapter we use the term "opioid" to refer to any substance

of natural or synthetic origin which has morphinelike effects.

Occasionally, when citing the work of others, we use the older

term "narcotic" in a sense approximately synonymous with

"opioids."

The term "dependence" unfortunately has some ambiguity, for two

meanings are ascribed to it. The term is used to refer to an

altered physiological state due to continued use of a substance,

and it is also used to refer to behavior--that is, to regular

compulsive use. When we refer to the altered physiological state,

we use the expression, "physical dependence." We use substance

"dependence" in accordance with DSM-III criteria, and consider it

approximately synonymous with the older term, "addiction." We use

the term "addiction" occasionally in citing the work of others who

use this term.

We use the term "alcoholism" in a broad sense to include not only

alcohol abuse and alcohol dependence, but also problem drinking

which may not meet the DSM-III criteria for abuse or dependence.

The term "abstinence" also has two meanings. It is used to refer

to the abstinence syndrome, a disorder which follows cessation of

use when physical dependence on a substance exists, and also to

refer to a continuing state of abstaining from substance use. We

use "withdrawal" (the DSM-III term) to refer to the abstinence

syndrome, reserving abstinence to refer to the continuing drugfree state.

ANTECEDENTS OF SUBSTANCE ABUSE

Because conditions preceding and contributing to the onset of

substance abuse may also have a role in relapse, we note here

50
several factors thought to have etiological importance in the

onset of substance abuse.

An antecedent personal vulnerability seems an important etiological condition for alcohol dependence and opioid dependence. Only

a small proportion of persons who use these substances become

compulsive users. Accumulating evidence points to a genetic

factor in alcoholism (Goodwin 1979), and there is somewhat less

evidence in opioid dependence. Rats have been selectively bred

for susceptibility to morphine addiction (Nichols and Hsiao 1967).

Evidence of a heritable influence in tobacco use has also been

offered (McClearn 1983). In our study (Maddux and Desmond 1981)

of opioid use careers we found a high prevalence of substance

abuse among relatives of our subjects. Twenty-eight percent of

the fathers were considered alcoholic, and 37% of the subjects had

one or more opioid-using siblings; we do not know whether genetic

inheritance or social learning accounts for these high rates of

substance abuse in the families of our subjects.

Adverse childhood experience has been implicated as a contributor

to alcoholism vulnerability in both retrospective and prospective

studies (Vaillant 1983), but in Vaillant's own prospective studies, adverse childhood experience did not predict alcoholism, with

the exception that having one or two alcoholic parents predicted

alcoholism. In this latter case, the effect of genetic inheritance becomes confounded with that of environment. Vaillant also

found that origin in an ethnic group that tolerated adult alcoholism but discouraged children from learning safe drinking

practices also predicted alcoholism.

Clinical and other retrospective studies (Chein et al. 1964; Craig

and Brown 1975; Seldin 1972) have implicated adverse childhood

experience in the etiology of opioid dependence. Prospective

studies starting with children before the onset of opioid dependence have not been reported. In retrospective study of the

childhood experience of our subjects, we found ample evidence of

adverse experience, but when we compared the parental family

experience of 50 addicts with their nonaddict brothers, we did not

find noteworthy difference (Maddux and Desmond 1984). We should

note, however, that almost 50% of the nonaddict brothers had

histories of alcohol abuse.

Retrospective studies have indicated that alcoholics began their

drinking to decrease tension, anxiety, or depression (Jellinek

1960). Relief of chronic emotional distress may serve as the

consequence which reinforces alcohol use. Vaillant (1983) did not

find evidence of more emotional distress existing premorbidly

among alcoholics than among nonalcoholics. However, he did find

that alcoholics were more likely to be premorbidly antisocial than

nonalcoholics. Since antisocial behavior often conceals anxiety

or depression (Vaillant 1975), hidden emotional distress may have

existed abundantly in his pre-alcoholic subjects.

51
Clinical studies have also indicated that opioid users began their

repeated opioid use to relieve chronic emotional distress (Wikler

and Rasor 1953; Khantzian et al. 1974; Wurmser 1974; Khantzian

1985). While few of our subjects gave histories of chronic

emotional distress, the majority showed evidence of antisocial

behavior preceding opioid use, On several measures of early

deviant behavior, 50 of our subjects were significantly more

deviant than their nonaddicted brothers (Maddux and Desmond 1984).

Our opioid users as well as Vaillant's alcoholics may have concealed their emotional distress in their antisocial behavior

before the onset of the substance use disorder.

CHRONICITY AND RELAPSE

Although chronicity of alcohol abuse has probably been observed

for centuries, biblical and other ancient reports seem to comment

more on the excesses and failures of the drunkard rather than on

the chronicity of the condition. Austin (1979) cited a law

enacted in 1672 in Plymouth, Massachusetts, which stated that

alcohol misuse was a chronic condition among certain drunkards.

Jellinek (1960, p. 220) noted a 19th century report on the danger

of relapse after cure. While Jellinek was primarily concerned

with the concept of alcoholism as a "disease," his descriptions of

the types of alcoholism note both its chronicity and periodicity.

While opium has been known and used for many centuries, the problems of chronic compulsive use and relapse after a period of

abstinence did not become identified until the 19th century. In

his "Confessions of an English Opium Eater," initially written in

1821, De Quincey (1966) first described the seemingly uncontrollable compulsion to continue using opium. He had multiple periods

of abstinence followed by relapse. When he revised the Confessions for the last time at age 71, he had struggled unsuccessfully

with his laudanum habit for 52 years.

Jones (1953) chronicled a similar lifelong struggle with tobacco

dependence in his biography of Sigmund Freud. Recognition of

compulsive smoking as an addiction or chronic disease was slow to

develop (Jaffe 1977). Tobacco dependence did not enter the official diagnostic nomenclature of the American Psychiatric Association until 1980. In the DSM-III the course of the disorder was

described as "variable" with some individuals repeatedly

attempting to give up tobacco without success, and others able to

achieve total cessation after a relatively brief episode. Relapse

was alleged to be unlikely among persons who achieved a year or

more of abstinence. Russell, in a review of mostly British

studies (1971), reached a more pessimistic conclusion, asserting

that "as many as three out of four smokers wish to or have tried

to stop their smoking, but less than one in four ever succeeds in

becoming a permanent ex-smoker" (Russell 1971, p. 3).

VARIABILITY IN SUBSTANCE ABUSE CAREERS

Psychoactive substance use seems to vary in adult populations not

only by the substance used and by the number of substances used,

52
sequentially or concurrently, but also as a continuum of severity.

This continuum ranges from no use, to nonproblem personal or

social use, to episodic or continuous problem use, to dependence

with inability to abstain, and finally to death as a direct or

indirect consequence of the substance use. The substances used

and the severity vary not only from person to person, but over

time in a given person.

Jellinek (1960) described different levels of severity of

alcoholism and labeled these alpha, beta, gamma, delta, and

epsilon. Delta alcoholism was the most severe level; it included

both physical dependence and inability to abstain. Jellinek

considered alcoholism a progressive disease, but he did not

describe the long-term alcoholic career. Vaillant (1983) has

offered the major contemporary contribution in this area. His

book not only presents the findings from three prospective

longitudinal studies conducted by Vaillant and his colleagues; it

also summarizes the major preceding longitudinal studies and

followup studies. Alcoholism becomes a progressive disease in

only a minority of alcohol abusers. Some heavy drinkers on

occasions will develop problems which meet the DSM-III criteria

for alcohol abuse but will progress no further; some of these

return to social drinking. Among those whose drinking comes to

meet the diagnostic criteria for alcohol dependence, the course

also becomes variable: they have successive periods of abstinence, of social drinking, and of relapse to alcohol dependence.

The periods of abstinence are often introduced by treatment or by

participation in Alcoholics Anonymous. Alcohol dependence commonly leads either to prolonged abstinence or to social incapacity or

death.

Like the course of alcohol dependence, the course of opioid dependence also varies greatly. In addition to irregular periods of

abstinence, occasional use, daily use, and treatment, the modern

opioid user often has long periods of incarceration. Since 1966,

my colleagues and I have been engaged in a prospective followup

study of 248 opioid users who resided in San Antonio. The findings

in this study illustrate the variable nature of opioid use

careers. The subjects, all men, were hospitalized at the former

Public Health Service Hospital in Fort Worth, Texas. Their mean

age in 1966 was 28, and, if all were alive, it would have been 47

in 1985. Fifty-three (21%) have died. The methods and preliminary findings of the study have been published (Maddux and Desmond

1981).

Figure 1 shows the marked variations in the 20-year opioid use

careers of ten subjects. Subject 071 used heroin daily for

approximately two years, then served 18 months of a five-year

prison sentence as a patient at the Public Health Service Hospital. Aged 29 when paroled, he remained abstinent from opioids

for 10 years, through age 39 at the time of our last interview.

Subject 067, in marked contrast, remained dependent on heroin or

methadone during most of his adult life, although he did have

several periods of voluntary abstinence lasting three to 14

53
FIGURE 1

Substance use careers of ten San Antonio opioid users.

(Maddux and Desmond 1981.) Copyright 2982, Praeger

Publishers.

months. The longest period of abstinence occurred while he was

working for a defense contractor overseas, away from his usual

source of drugs. He died in a hospital at age 41 following

surgery for peptic ulcer.

Similar variability probably exists in the long-term tobacco use

career, but studies of tobacco use patterns over two years or

longer are uncommon (Schwartz 1977; Krasnegor 1979), and mention

of the concept of career in the context of tobacco use disorder is

rare. Our review of the literature turned up only one reference

to a "tobacco use career" (Kozlowski 1979).

RELAPSE AFTER TREATMENT

The majority of treated alcoholics relapse to alcohol abuse or

dependence. Vaillant (1983, p. 284) pooled the results of four

studies in which a total of 685 treated alcoholics were followed

for two years. At the end of two years 63% were abusing alcohol;

21% were abstinent or drinking socially. In Vaillant's own sample

at the end of two years, 67% were abusing alcohol; 20% were

abstinent or drinking socially. By the end of the eight-year

followup period, 95% had resumed drinking at some time, but not

all had relapsed to alcohol abuse or dependence.

54
Relapse not only occurs frequently after treatment, it also occurs

rapidly after treatment. Gottheil and associates (1982) reported

that only 19% of 20 treated alcoholics remained abstinent during

six months after treatment; 48% became relapsed drinkers during

that time. The authors cited two other studies, having a combined

total of 499 treated alcoholics, in which only 18% remained abstinent during six months after treatment.

Frequent and rapid relapse after treatment also occurs in opioid

dependence. Duvall et al. (1963) found that 97% of 43 opioid

users became readdicted at some time during five years of followup

after treatment. An estimated 67% became readdicted during the

first six months after discharge. In our study (Maddux and

Desmond 1981) of careers of opioid users, we found that 70% of

1,653 treatment and correctional interactions over a mean period

of 20 years were followed by less than one month of abstinence.

Eighty-seven percent were followed by abstinence of less than six

months. In their followup of 2,099 opioid addicts in the Drug

Abuse Reporting Program, Simpson and Sells (1982) reported that

56% to 77% of opioid addicts in different treatment groups resumed

opioid use within one year after completion of treatment.

Frequent and rapid relapse has also been reported following treatment of tobacco dependence. Hunt et al. (1971) plotted relapse

curves of treated alcoholics, heroin addicts, and smokers and

found the three to be essentially the same. In their reviews of

smoking treatment outcomes, Hunt and Bespalec (1974) and Krasnegor

(1979) concluded that most smokers, 70% to 80%, resumed tobacco

use within one year. Hall and associates (1984) more recently

reported a lower relapse rate following treatment with a relapse

prevention component.

Vaillant (1983, p. 180) identified five factors which he considered important in relapse to alcoholism. Two of these were

factors which also made the person vulnerable before the onset of

alcoholism. The five factors included: 1) a genetic predisposition; 2) a psychological predisposition; 3) physical dependence,

which may persist for months after abstinence; 4) operant and

Pavlovian conditioning; and 5) absence of protective conditions,

such as a stable social network.

Nearly 50 years ago Kolb (1927) identified three factors which he

considered important in relapse to opioid dependence: 1) a

primary psychic factors, which made the person vulnerable to the

original opioid dependence and to relapse after abstinence; 2)

physical dependence--Kolb felt that his factor became more important with increasing years of opioid use; some of his subjects who

were addicted 10 or more years reported feelings of lassitude and

undue fatigue which lasted six to nine months after cure; 3)

memory associations and habit. The repeated relief of discomfort

by taking morphine or heroin formed a strong association between

physical and mental distress and the taking of the drug.

55
While Kolb reported environmental adversities which seemed to precipitate relapse, he attributed more importance to the person's

inability to cope, i.e., the primary psychic factor.

Since Kolb's report, protracted withdrawal existing for six months

following opioid dependence has been measured and described, and

its possible role in relapse has been assessed (Martin 1972).

Thus, in both alcohol and opioid dependence, protracted withdrawal

seems a likely etiological factor in rapid relapse. Withdrawal

may also be a factor in relapse to tobacco dependence (Pomerleau

1979; Shiffman 1979).

The "memory associations and habit" conceived by Kolb have been

reformulated into classical and operant conditioning hypotheses.

Both tpyes of conditioning have been demonstrated (mainly in rats)

to have roles in relapse (Wikler 1980).

In our study of careers of opioid users, we attributed relapse in

part to protacted withdrawal, to conditioning, and to stress, such

as the onset of marital conflict. Additionally, we inferred a

subjective motivational state revealed more in action than in

words. Our subjects came to most treatment interactions under

external coercion, and they rarely seemed to have a desire persistent enough to overcome their opioid dependence.

Many factors associated with relapse to tobacco dependence have

been identified. Prominent ones include the "overlearned" nature

of the habit (Hunt and Matarazzo 1970); withdrawal discomfort

(Schachter 1970; Jarvik 1970); use of other substances, particularly alcohol (Shiffman 1982); social pressures (Marlatt and

George 1984); negative affect (anxiety, tension, and depression)

(Kozlowski 1979; Shiffman 1982); and deficient coping skills (Hall

et al. 1984; Marlatt and George 1984).

LONG-TERM OUTCOMES

The studies which have followed substance abusers for five years

or longer seem almost entirely limited to studies of alcohol and

opioid users. We found only one five-year followup study of

smokers (West et al. 1977). All studies found that small percentages of subjects were abstinent at varying followup periods.

Kendell and Staton (1966) followed a group of 62 British alcohol

addicts for an average of 6.7 years after they rejected or were

denied admission to treatment. At followup, 18% had died, 8% had

returned to "normal social drinking," and 15% had been abstinent

at least one year (mean duration was approximately four years) at

followup. Only one of the nine abstinent subjects received no

treatment during the followup.

Hyman (1976) studied a group of 54 New Jersey alcoholics, aged 30

to 54 at admission to treatment, for a period of 15 years from

termination of treatment. At followup, 33% had died, 17% were

"unimproved problem drinkers," 20 were moderate drinkers, and 11%

56
were total abstainers for a period of a least three years before

followup. Nineteen percent could not be located or refused to

participate.

Edwards et al. (1983) studied 99 married alcoholic men for an

average period of 11 years. Eighteen had died, 13 were lost to

followup, and 68 were personally interviwed. We recomputed the

published outcome status statistics by using the starting sample

of 99 as the denominator. At followup, 27% were "doing well," 32%

were drinking in an "uncontrolled fashion," 9% were in a category

labeled "equivocal outcome," 18% were dead, and 13% were unknown.

In their summary, Edwards and associates noted that "Pathways to

recovery are individual and complex," and that an important final

path may be ". . . certain psychological shifts." Data from the

Edwards study were reanalyzed by Taylor and associates (1985).

Approximately 25% of the subjects alive throughout the ten-year

study period were continuous drinkers, and 15% were continuously

abstinent. The remaining 60% exhibited a patchwork of abstinence

and troubled drinking; in other words, most experienced multiple

periods of remission followed by relapse.

Vaillant and Milofsky (1982) reported that among 110 alcohol

abusers followed from age 20 to age 47, 21 (19%) became "securely

abstinent," i.e., had achieved three years or more of continuous

abstinence--actually, a mean of 10 years. Some of the most symptomatic drinkers were among those who achieved secure abstinence.

Although alcoholism occurs with demonstrated severity and frequency among Native Americans, a 10-year followup by Westermeyer

and Peake (1983) suggested long-term outcomes similar to those

cited above. At the time of followup, the 45 subjects were found

in the following statuses: abstinent for two years or more, 16%;

problem drinking, 58%; dead, 20%; and unknown, 7%.

The long-term followup studies of opioid addicts have also found

small percentages abstinent at different periods of followup. In

their followup of 453 opioid addicts, Duvall et al. (1963) found

that, at five years after followup, 46% of living subjects were

addicted, 2% were voluntarily abstinent, and 24% were

involuntarily abstinent.

In his study of Kentucky opioid addicts, O'Donnell (1969) described the careers of 266 subjects during an average period of 12

years after their first admission to the Public Health Service

Hospital in Lexington. He found that 13% of the subjects

displayed "much abstinence" (more than 50% of noninstitutional

time), and 10% displayed "complete abstinence" after treatment.

Thirty percent were addicted throughout their posthospital

careers. O'Donnell emphasized the general lack of clear-cut

longitudinal patterns, noting that 60% of the subjects were "seen

to shift from one status to another, with periods of narcotic

addiction broken by shifts to other drugs, and frequently by

periods of complete abstinence, sometimes quite long."

57
Valliant's followup studies of New York City heroin addicts are

perhaps the most widely cited addiction career studies. In both

his 12-year followup (1966a, 1966b) and his 20-year followup

(1973), Vaillant emphasized a three-year abstinence criterion:

". . . urban heroin addicts who achieve more than three years of

abstinence can usually maintain this abstinence indefinitely." Of

100 addicts admitted to treatment in 1952, 23% had died by 1970,

35% had achieved what he called stable abstinence, and 25% were

still using opioid drugs.

Vaillant's 20-year followup depended primarily on institutional

records. Most of the followup studies of British opioid addicts

(Gordon 1983; Cottrell et al. 1985; Willis and Osbourne 1978)

suffer from the same methodological problem. Other followup

studies have relied primarily on self-reports from subjects, with

variable confirming data from other sources. The validity of data

obtained in followup studies represents a continuing problem.

In our study of 248 opioid users from San Antonio, we learned that

a three-year abstinence does not portend a lifetime abstinence.

In 1981 we reported that 33% of our subjects who achieved three or

more years of abstinence eventually resumed opioid use (Maddux and

Desmond 1981, p. 101). By the end of 1983, 31 subjects had

achieved five years or more of opioid abstinence during their

careers but had later resumed daily use. Of these 31, 12 subjects

(39%) resumed opioid use after periods of abstinence ranging from

five to nine years, and one subject resumed opioid use after 13

years of abstinence.

Ninety-three of our 248 addicts began opioid use in 1954 or before

and were followed either until death or through calendar year

1984. In figure 2 are shown the percentages of subjects in different drug use statuses during July of each year from the year of

first use through the 30th year after first use. The percentage

of subjects in each status is represented by the width of the horizontal bands. Individual subjects shifted among these statuses

over time. For more than 20 years, the percentage of subjects

using illicit opioids daily remained approximately 40%. The percentage abstinent during the first two decades ranged from 7% in

year 1 to 24% in year 4. The main changes during these two

decades were the decrease in occasional use, which was most marked

in the first three years, and the large increase in percentage

institutionalized, which peaked in year 12. After the 20-year

mark a steady decline in daily illicit opioid use began, along

with a noticeable decrease in institutionalization. By July of

year 30, only two subjects were using heroin daily and 11 were

maintained on methadone. Twenty (22%) died by the 30th year.

In the 30th year after initial use, 14 (15%) of the 93 subjects

had three years or more of continuous voluntary abstinence from

opioids, no evidence of alcohol or nonopioid drug abuse or dependence, full-time employment of three years duration, and no

arrests for at least three years. The mean duration of abstinence

in this recovered group was eight years as of the 30th career

58
FIGURE 2.

Drug use status of 93 San Antonio subjects during July of years 1-30 after onset of

opioid use.
year. We have continued to follow the subjects beyond that point,

however; and at the time of our most recent interview, these men

had accrued an average of four additional years of abstinence,

making a mean of 12 years of continuous abstinence. Four of the

14 subjects experienced episodes of alcohol abuse or dependence

after the 30th career year, however, and one subject received a

lengthy prison term for a drug law violation.

The trend of increasing abstinence with passage of time has also

been reported by Duvall and associates (1963), O'Donnell (1969),

and Vaillant (1973). Kolb (1924) also reported excessive use of

alcohol among his subjects following opioid withdrawal. Vaillant

(1983) also found a trend of increasing abstinence among his

alcholics.

Death occurs as a longterm outcome with notable frequency. The

death rates for alcohol and opioid abusers are reported to be approximately three times higher than the expected rates (O'Donnell

1969; Maddux and Desmond 1981; Vaillant 1983). The death rates of

cigarette smokers are approximately 1.7 times those of nonsmokers

(Public Health Service 1979).

RECOVERY

The study of recovery from substance dependence has been impeded

by a lack of agreement as to the meaning of the term. Diverse

labels have been applied to the phenomenon, including "cure,"

"maturing out," remission, "de-addiction," cessation, stable

abstinence, and "quitting." Some of the terms imply a permanent

status (cure), while others include possibly temporary or fluctuating conditions (remission, cessation).

Treatment evaluators have used varied concepts of recovery, and

they have used multiple criteria for recovery, including indicators of social adjustment. Duration of abstinence suggestive of

recovery varies, with most followup studies specifying one to

three years of abstinence. Alcohol studies frequently use a

duration of less than three years, and most smoking studies use a

duration of one year or less. Many investigators ignore infrequent lapses, "slips," or occasional "chipping." Debate over the

issue of reduced or controlled substance use versus abstinence

continues. A committee of the American Medical Association (1970)

developed criteria for recovery from drug dependence which included three years of abstinence from the primary drug and no abuse of

other substance. Bejerot (1975) recommended five years of abstinence as a criterion for recovery.

The term recovery conventionally means "the act of regaining or

returning toward a normal or usual state" (Webster 1971). It

refers to a process rather than a state. Members of Alcoholics

Anonymous refer to themselves as "recovering alcoholics," thus

emphasizing the process rather than a state. If recovery is

viewed as a process, then it becomes possible to identify and

describe, more or less arbitrarily, levels in the process. Levels

such as the following could be defined:

60
Level 0. Continued daily use of primary substance for one

month or longer, or incarcerated, for one month or longer.

Level 1. Daily substitute medication (e.g. methadone) for

primary substance for one month or longer.

Level 2. Abstinent from primary substance with no substitution for one month or longer. Recovered from acute withdrawal.

Level 3a. Only occasional nonproblem use of primary or other

substance for one year or longer. Possible tobacco dependence. Full-time employment for one year or longer unless

physically disabled.

Level 3b. Same, with less employment.

Level 4a. Continuous voluntary abstinence from primary

substance with only occasional use of other substances.

Possible tobacco dependence. Full-time employment for one

year or more unless physically disabled.

Level 4b. Same, with less employment.

Level 5a. Continuous voluntary abstinence from all substances, except possibly tobacco, for one year or more.

Full-time employment for one year or more unless physically

disabled.

Level 5b. Same, with less employment.

The levels could be extended for two years, three years, or

longer. The use of levels of recovery avoids the difficulty of

attempting to determine whether the person has regained a "normal

or usual state." The person who has had a substance use disorder

may never completely return to his "usual" state which preceded

the disorder. Some remnants of the disorder, such as the loss of

liver cells or the memories of substance effects, probably endure

for a lifetime.

Several studies have identified pretreatment variables which

predicted recovery. Among alcoholics, these include social

stability--especially with respect to employment and family;

absence of arrests, and late onset of alcoholism (Vaillant 1983,

p. 168). Among opioid addicts, the criminal history predicted

posttreatment outcomes with respect to opioid use, employment, and

criminality (Simpson and Sells 1982). Pretreatment criminality,

employment, and alcohol use also predicted, respectively, posttreatment criminality, employment, and alcohol use. Duration of

treatment was a better predictor of outcome than type of treatment. Several predictors of recovery after smoking treatment have

been identified. Among older studies, gender was one of the most

powerful; women consistently had more difficulty quitting

(Kozlowski 1970). Among men, high extraversion and low neuroti61
cism predicted good outcome. Other predictors included lower

pretreatment cigarette consumption, low use of other substances--

particularly alcohol and caffeine, having fewer relatives and

friends who smoke, lower levels of chronic illness, and absence of

"negative affect" smoking (Schwartz 1977; Kozlowski 1979).

In our study of opioid use careers, we found several background

variables that were weak but statistically significant predictors

of years of abstinence during the first 10 years after first

opioid use. These included intact parental family, no opioidusing relative, no convictions before first opioid use, number of

months from first use to daily use, and age at first daily use.

These findings suggest that a better family background leads to

better coping skills and less alienation, and these in turn lead

to less deviant behavior and later onset of daily use; the combination then leads to a somewhat less severe opioid use career.

These predictor variables account for only 18% of the variance in

years abstinent.

Other studies which have focused on the relationship of both

pretreatment and treatment variables to long-term outcome have

typically found that the predictor variables explained only a

small fraction of the outcome variance (Zahn and Ball 1972;

Whitman et al. 1982; Judson and Goldstine 1982; Simpson et al.

1982). These findings, together with the recognition that formal

treatment only initiates the recovery process (Edwards 1984;

Pechanek 1979; Wille 1980), have prompted some investigators to

look more closely at posttreatment variables. Many substancedependent persons begin recovery without treatment (Drew 1968;

Robins et al. 1980; Schacter 1982); study of spontaneous recovery

is frequently advocated (Vaillant 1983; Smart 1976; Waldorf and

Biernacki 1979).

Substance substitution occurs with noteworthy frequency, especially between alcohol and opioids. Thirty-nine percent of Kolb's

(1924) opioid users were alcoholic before they began opioid use.

This pattern seems less common in the latter half of the 20th

century, yet a substantial minority (25% to 30%) of opioid users

continue to report alcohol abuse or dependence pre-dating onset of

opioid dependence (Green et al. 1978) or prior to treatment (Barr

and Cohen 1980). O'Donnell (1969) observed substitution of alcohol and barbiturates among his Kentucky addicts who had ceased

opioid use. Vaillant (1966b) found a substitute substance dependence, usually alcohol, among some of his abstinent former heroin

addicts. Among his abstinent alcoholics, he also found substance

substitution (Vaillant 1983). The substituted substances included

benzodiazepines, marijuana, and tobacco. Waldorf (1983) reported

"heavy drinking" among 41% of 201 recovered addicts, but suggested

that this phenomenon occurred early in the recovery process and

abated within a year. In our career study, we found that 43% of

54 subjects who achieved three years or longer of opioid abstinence had substituted alcohol for the opioid drug. Most exhibited

evidence of alcohol abuse or dependence for more than one year.

62
A large minority of patients maintained on methadone drink excessively (Joseph and Appel 1985). Apparently, many opioid users

cannot endure a steady pharmacological state, neither abstinence

nor smooth maintenance. Furthermore, from our clinical observation, it seems that most opioid addicts in treatment smoke one or

two packs of cigarettes every day. The alcohol and tobacco use by

methadone patients seems to be substance supplementation rather

than a substitution.

Several investigators have identified and described a number of

posttreatment conditions which were thought to facilitate prolonged abstinence or recovery. O'Donnell (1969) found that

abstinence from opioids was weakly associated with several variables: gender (women were more frequently abstinent than men),

less involvement in the drug subculture, and being employed

regularly. The associations were statistically significant, but

were not strong enough to be considered practical predictors of

abstinence. One environmental factor was of such overriding

importance that the other variables had little chance to show an

effect. That major factor was decreased availability of opioid

drugs. O'Donnell's subjects lived in a locale and an era in which

marked changes in medical prescribing practices, enforcement of

narcotics laws, and other social factors acted together to drastically reduce the amount of opioid drugs available.

Vaillant (1966b) reported the following factors associated with

opioid abstinence: compulsory supervision, a stable nonparental

personal relationship, and a change in residence away from the

drug-use area. He reported different but overlaping factors

associated with abstinence after alcoholism (Vaillant 1983):

behavior modification (broadly conceived to include compulsory

supervision), enhanced hope and self-esteem (often from religion

or AA), and social rehabilitation (including a new love relationship). He commented (p. 314) that "Staying sober is not a process

of simply becoming detoxified, but often becomes a work of several

years or . . . a lifetime."

Brill (1972) conceived a transition to addiction and the transition to abstinence as processes that evolved slowly with much

learning and adaptation. He called factors associated with

recovery "pushes" and "pulls." The pushes included: the bad

life, including arrests, prison, and hospitalization; negative

self-image; overdose; stress from constantly avoiding withdrawal;

and exhaustion of resources. The pulls included: legitimate

aspirations; treatment; personal relationships; and opportunity to

think while in jail or hospital.

Waldorf (1983) identified five processes (excluding development of

alcoholism or other psychiatric disorders) leading to recovery in

samples of 100 treated and 101 untreated ex-addicts: 1) developmental change; 2) conversion to religious, spiritual, or ideological groups; 3) change in behavior following environmental change;

4) "retirement" from drug use; and 5) "drift" from deviant into

conventional behavior.

63
Among our 54 former addicts who achieved three or more years of

abstinence, we identified the following factors (excluding alcohol

substitution) which probably facilitated the abstinence: treatment or correctional interaction during year before onset of

abstinence (present in 89% of the cases); relocation of residence

away from usual source of drugs; evangelical religious participation; employment with a drug abuse treatment agency; and probation

or parole for one year or longer (Maddux and Desmond 1981, pp.

99-105). Our later, more extensive analysis of residence relocation demonstrated this factor to be significantly associated with

abstinence (Maddux and Desmond 1982).

The following three vignettes illustrate factors associated with

recovery among our San Antonio subjects. The careers of the

three men are depicted in figure 1.

Subject 071. After approximately two years of heroin use, he

spent 18 months in involuntary treatment. After release from

treatment, he planned to resume heroin use, but, as he was preparing the heroin for injection, he realized that he had life

goals which were incompatible with heroin use. He wanted to take

care of his family and set a good example for his children, and he

wanted to accomplish something in life. He refused the injection

and remained abstinent for 15 years, through the age of 44 at last

interview.

Subject 111. After four years of occasional use of heroin he

ceased use because he married and his wife promptly threatened to

leave if he used heroin. Nine years later he resumed use in

response to marital conflict, used daily for two years, and then

voluntarily entered a hospital for treatment. After treatment he

became intensely involved in church work. Aged 47 when last

interviewed, he was no longer involved in his church work but had

been abstinent and steadily employed for 18 years.

Subject 162. From age 16, he used heroin daily for 20 years,

except for short periods in hospital or jail, Then, at age 37,

while participating in a prison therapeutic community, he felt a

change in himself. He decided to stop "playing games." After

discharge (not shown in figure 1), he remained abstinent under

compulsory supervision and obtained employment in a drug abuse

treatment program. When last interviewed, at age 52, he had been

abstinent for 14 years.

The following factors were cited in two or more of the studies

reviewed above: compulsory supervision, residence relocation, a

supportive social environment, religious activity, and treatment.

THE MAJOR THEMES

Similar findings by different investigators on several general

features of substance abuse careers in the United States,

especially those of alcohol and opioid users, have emerged in our

review of the literature. These can be summarized as major

themes, as follows:

64
1. Personal vulnerability. Only a small proportion of persons

who use psychoactive substances become substance abusers. Some

persons use alcohol throughout a lifetime without disability. A

special vulnerability, genetic or acquired, seems important in the

etiology of alcohol and opioids abuse and in relapse. The evidence for personal vulnerability seems less clear for tobacco

dependence.

2. High risk environment. Increased accessibility of substances

seems to be another important etiological factor. The much

greater prevalence of alcohol abuse over opioid abuse may be a

consequence of increased availability, the difference due to the

greater legal control of opioids. Furthermore, considerable

evidence points to factors in the family and social environment,

especially those promoting social learning of substance abuse.

3. Wide variation. Substance abuse careers vary widely in

duration and severity. Most alcohol and opioid abusers show

irregular periods of abuse, abstinence, ocasional use, daily

non-abusive use, hospitalization and outpatient treatment, and,

especially with opioid uses, incarceration. Less is known about

the tobacco user's career.

4. Substance substitution. Substitution of alcohol abuse for

opioid abuse and the reverse occurs with noteworthy frequency.

Concurrent, supplementary use of one while abusing the other also

occurs. Tobacco dependence is seen with high frequency among both

alcohol and opioid abusers.

5. High mortality. Death rates for alcohol and opioid abusers

are approximately three times higher than expected rates. Death

rates of smokers are 1.7 times higher than those of nonsmokers.

6. Frequent and rapid relapse. Alcohol dependence, opioid

dependence, and tobacco dependence often seem refractory to

treatment. Most treated persons relapse within one year after

treatment.

7. Increasing abstinence. With passage of years, increasing

abstinence is found in alcohol dependence and opioid dependence.

This also probably occurs in tobacco dependence, but long-term

career studies of this disorder have not yet been reported.

8. Maintaining recovery. The minority of alcohol and opioid

abusers who maintain a recovery process for three years or longer

seem to experience personal change with less emotional distress.

Environmental conditions such as treatment to initiate and

maintain the recovery, external coercion, and supportive social

relationships seem useful in maintaining the recovery.

ISSUES

Although general themes of agreement seem to exist about the

characteristics of relapse and recovery in substance abuse,

65
several problems handicap understanding of these phenomena. The

problems include:

1. Definitions and criteria. The absence of generally accepted

criteria for relapse and recovery handicap comparison of results

of outcome studies.

2. Clarification and measurement of etiological factors. While

a number of individual and environmental factors have been identified which seem to affect relapse and recovery, the conceptions

of these conditions vary among investigators. More research is

needed to clarify and measure these variables and to estimate

their effects.

3. Motivation for recovery. Most alcohol and opioid abusers

enter treatment under external coercion. Alcohol abusers often

deny that they have an alcohol problem. Motivation for recovery,

a subjective changing condition, seems a prominent determinant of

the recovery process. More precise analysis and measurement of

this condition is needed.

4. Social drinking. Return to "social" or "controlled" drinking

or drug use as a level of recovery needs further study and

evaluation.

5. Treatment effects. While treatment seems to have beneficial

short-term effects, especially partial or complete recovery from

acute withdrawal, its effects on the long-term career seem less

clear. More study is needed.

6. Validity of data. Most of the data of followup and career

studies consist of self-reports from subjects. While urine

analyses and reports from other sources generally tend to confirm

the self-reports, continued study on the validity of self-reported

recovery from substance abuse subjects is needed.

REFERENCES

American Medical Association Committee on Alcoholism and Drug

Dependence. Recovery from drug dependence. JAMA 214:579, 1970.

American Psychiatric Association. Diagnostic and Statistical

Manual of Mental Disorders. 3d. ed. Washington, D.C.; American 

Psychiatric Association, 1980.

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ACKNOWLEDGMENT

This work was supported in part by the U.S. Public Health Service

Service grant number DA 00083 from the National Institute on Drug

Abuse.

AUTHORS

James F. Maddux, M.D.

David P. Desmond, M.S.W.

Department of Psychiatry

The University of Texas Health Science Center

7703 Floyd Curl Drive

San Antonio, Texas 78284-7792

71
Multivariate Description

of Alcoholism Careers:

A 10-Year Followup

Colin Taylor, David Brown, Anni Duckitt, Griffith Edwards,

Edna Oppenheimer, and Margaret Sheehan

INTRODUCTION

This chapter presents data collected by a team of workers at the Addiction

Research Unit in one of its longest standing studies. By 1971, this team had

inducted 99 male, married alcoholics attending the Maudsley Out-Patient Clinic

into a treatment trial in which the standard treatment program was compared

with the efficacy of just giving simple advice (Edwards et al. 1977). Recently,

these alcoholics were contacted again, 10 years or more later, and it is this set of

data with which this chapter is concerned. A number of reports on this project

have already been published (Edwards et al. 1983, 1986; Duckitt et al. 1985;

Taylor et al. 1985.)

The data obtained for these patients does not detail their relapses and recoveries

throughout the period of the followup. It is intended to give an overview of the

processes of change that occurred over those 10 years and show the background

against which the careers of these alcoholics have unfolded. In so doing, the aim

of this primarily descriptive study is to supply the context within which the

individual movements between relapse and abstinence might be understood.

Caution must be taken on interpreting too much and generalizing too far from

these data, because of their inherent limitations: data limited in number to only

99 individuals; limited in time and place to London at the end of the 1960s; and

limited to self-selected subjects, all of them married men, predominantly in their

forties, seeking treatment as out-patients at the Maudsley Hospital clinic.

Nonetheless, we believe these data are important for what they can tell us: not

just for the factual information they provide about these 99 alcoholics, but also

because they raise issues of interest, both methodological and conceptual, that

have a more general application. The larger questions the analysis raises about

career and natural history of alcoholism are:

What is the multidimensional structure of the phenomena which are

subsumed under the simple term “outcome”?

Does a maturation process exist and, if so, how should we characterise

it?

Should career be viewed as following distinct and different pathways, or

is there a continuum of such patterns?

72
These questions are raised--but not answered--by this study. What has been

attempted is (i) to chart periods of time spent in heavy drinking; (ii) to explore

the relationship between the different dimensions of change; and (iii) to relate

these to the severity of the alcohol problem at intake into the study 10 years

previously.

THE BASIC SAMPLE DETAILS

The sample consists of 99 individuals who vary considerably in terms of career,

natural history, and maturation, and are linked only in that the period for which

we observed them began with an alcoholism clinic attendance at the beginning of

the 1970s. They are not a birth cohort, their ages ranging at intake from 20 to

60. Neither are they a cohort at a particular stage of the development of their

alcoholism: some had been previously treated for drinking problems but about 50

percent had not; and the extent of their drinking and dependence varied from

moderately dependent drinking, with an intake of perhaps 5 pints of beer

equivalent a day to more severely dependent individuals whose drinking was in

excess of 20 pints a day.

TABLE I

Selected Sample Characteristics at

Intake into the Study

Age at Intake

20-29 30-39 40-49 50-60 All

16 28 35 20 99

Mean years of problem drinking(1):

1.7 3.5 4.5 8.1 4.4

Mean daily alcohol consumption(2):

286 291 248 217 259

(1) Years since “drinking became problem”

(2) On “typical drinking day” (in ml.)

Some of this background information is shown in table 1. Of these 99 men, 68

were interviewed at followup: 18 had died during the followup period, and 13

were lost to followup (including 1 refusal), Numbers in the subsequent analysis

are reduced somewhat further by occasional missing items of data.

Table 2 shows in the broadest possible terms what happened to this group of

alcoholics in respect to their drinking over the 10-year followup period. It gives

year by year the average number of months the group as a whole spent in each

of three modes of behaviour. Again, a previous publication (Taylor et al. 1985)

displays these “life chart” data and reports more detailed information; but for our

present purposes it will be sufficient to note that there is the gentlest of trends

73
towards slightly more abstinence over time. This table, of course, pertains only

to the 68 individuals for whom a followup interview was obtained.

TABLE 2

Drinking Status Data (in Months) During 10 Years

of Followup of Interviewed Sample Members

'72 '73 '74 '75 '76 '77 '78 '79 '80 '81

Abstinent

4.0 4.1 4.0 4.4 4.2 4.7 4.9 5.4 5.3 5.1

Social

.2 .1 .4 .4 .5 .7 .7 .5 .8 1.1

Troubled

7.8 7.8 7.6 1.2 7.3 6.6 6.4 6.1 5.9 5.8

NOTE: Years are nominal and begin with first full calendar year of followup.

This report goes on to explore the separate patterns of behaviour and experiences

which are contained within this summary presentation of the entire group. Our

central theme is that the course of alcoholism requires a multivariate description.

It cannot be confined to a simple record of drinking and abstinence: mental and

social well-being are likely to vary from individual to individual, even when

their drinking is similar; and apparently successful abstainers may well substitute

for their drinking habits which are as bad or worse. Before proceeding,

therefore, it is necessary to describe the data that have been collected for these

individuals.

DERIVED MEASURES

The 68 individuals were interviewed using a semi-structured questionnaire with

probing, and the interviews were tape-recorded. The interviewees were asked to

give an account of their drinking history over the preceding 10 years. Only

three categories of types of drinking were operationally defined, and the one

with which we shall primarily be concerned here is that of “troubled drinking”--

drinking more than five pints of beer in any day during the month or

experiencing any dependence symptoms or experiencing other adverse

consequences. (For full details of the definitions, see Duckitt et al. 1985.)

Apart from the tape-recorded accounts mentioned above, the principal item of

information in this study which is coded on a year-by-year basis throughout the

followup period is that of the drinking histories; this is the information from

which the “life chart” data in table 2 was calculated. The remainder of the

information is in the form of variables which in some sense summarise the entire

10 years of life of each individual. For example, the analyses presented here

concern the total amount of time an individual spent in heavy drinking

throughout the followup period and is a simple total across the years for the

time-based drinking histories.

74
In addition to summarizing this 10-year interval, the study paid particular

attention to behaviour during the 12 months immediately prior to followup. The

information collected for this l-year slice is not usually identical in form to the

type of information collected for the entire followup. For example, the l-year

data on drinking is recorded as the total (estimated) consumption of alcohol over

the past 12 months; this is in contrast to the followup data, which concern the

amount of time spent in troubled drinking.

The data were collected in five designated areas of interest within which key

questions were asked covering the entire follow-up, the l-year period, or both,

and for which summary scores were constructed:

(1) TOTAL 10-YEAR FOLLOWUP DRINKING & LAST YEAR

CONSUMPTION

(2) TREATMENT - 10-YEAR FOLLOWUP & LAST YEAR

- Inpatient, Hostels, G.P.

- AA attendance

(3) PHYSICAL HEALTH - 10-YEAR FOLLOWUP

- Cirrhosis, Peptic ulcer,

AlC. brain damage, Chronic illness

(4) MENTAL HEALTH - 10-YEAR FOLLOWUP & LAST YEAR

- Depression, Suicide, Drug problems

(5) SOCIAL ADJUSTMENT - LAST YEAR

- Employment, Stable home

- Legal encounters, Marriage

Ideally, each area would have been covered by a large number of questions in

order to elicit detailed information for the whole field, but practical constraints

determined that only a few key items could be elicited. The information under

each heading is only outlined in this list; to give it in more detail here would be

impossible and a discussion of the difficulties and advantages of constructing

such scores would require a separate paper. (For some further details, see

Duckitt et al. 1985.)

A further set of measures were taken at the followup point which consisted of a

group of standard scales, usually in the form of self-completion questionnaires:

(1) The Eysenck Personality Inventory (“EPI”. Eysenck and Eysenck 1964) is

well known.

(2) The Severity of Alcohol Dependence Questionnaire (SADQ) (Stockwell et al.

1979) is a well-known measure of alcohol dependence. In this particular instance

the subject was asked to recall the most severe period of drinking that he had

ever experienced and to answer the SADQ as for that time. Thus, we have the

worst ever dependence for the subject.

(3) The Purpose in Life inventory (PIL) (Crumbaugh 1968) measures attitudes

such as “I believe man is absolutely free to make all choices / completely bound

by limitations of environment,” and “In achieving life’s goals I have made no

progress whatever / progressed to complete fulfillment.”

75
Two final scales, which are not particularly standard, are:

(4) The Troubles scale, which measures physically and socially troublesome

consequences of drinking, is inherited from the intake stage of the study, where

it was developed by Dr. J. Orford (Edwards et al. 1977). It covers basically the

areas of physical withdrawal (e.g., body shakes, blackouts) and social difficulties

such as debt and homelessness.

(5) The Attributions inventory is a 70-item questionnaire developed for this

particular followup to elicit from the alcoholic what influences and impacts have

had the most effect on his drinking problem, for better or for worse. This scale

will not be examined in this presentation, but is the subject of another paper

(Edwards et al., forthcoming).

At this point, it is worth noting that any sort of summary measures over a time

period are likely to weaken the measured relationship between the phenomena

concerned. Thus, a summary measure of depression and another of drinking will

probably not correlate as highly as they would if we had observed the year-byyear variation in each, assuming that they do indeed relate on a parallel basis

year by year. This attenuation phenomenon would be observed in the case of all

except the most slowly varying measures.

AIMS OF THE ANALYSIS

This long-term study was designed basically as a descriptive study and, although

there were a few key issues around which it was organized, there are few

specific hypotheses. The analysis should aim at presenting the wealth of

information in a parsimonious manner. The original intent of the study, the

comparison of a treatment with an advice group, is not a factor in the present

analysis. The difference between these two groups in followups conducted after

1 and 2 years were minimal and now, 8 years further on there is little possibility

that the groups differ in any significant respect. Rather than making simple

comparisons of pre- and post-treatment states, looking for the often puny effects

of treatment, the aim is instead to chart the larger, natural effects of 10 years of

life. The current analysis, therefore, treats the data as though they were a simple

10-year follow-up of a single cohort of alcoholics.

Although referred to as a cohort, it is important to remember that these men

were taken into the study simply by virtue of being consecutive attendees at the

Maudsley clinic. Viewed as a long-term followup, therefore, what we have is a

10-year slice taken out of each of their lives in a random fashion. Furthermore,

we must dispense with any idea of a “final outcome point” for the study since, in

any important sense of the word, “outcome” was well under way when the

individual entered the study. It is the whole 10-year slice that we wish to

describe.

Ten years out of an individual’s life provide a vast amount of detail, reflecting a

complex interplay of forces. The first object, therefore, of our analysis of these

data is to marshal the information from a particular viewpoint or around a

specific framework so as to provide some order to the description. Even the

crude information presented in the life chart showing the group’s drinking

history provides a challenge to the researcher in terms of its simple description.

A cursory glance through that information shows that although there are some

cases (4%) who were abstinent throughout the followup period and some (20%)

76
who remained in troubled drinking, over half the individuals displayed a

patchwork of drinking and abstinence in which no clear organizing principle is

easily discerned.

Part of the initial formulation of this study was the recognition of the obvious

fact that this sort of information cannot be contained in simply the coded

variables listed above. It is with this point in mind that we intend to analyse the

recorded accounts of our study members given at interview.

CHOICE OF ANALYSIS

Our overall aim, then, is to provide a framework upon which we may hang our

descriptions, particularly the descriptions of the drinking histories, partly with a

view to the future analysis of the free response material in the tape-recordings.

One approach we could have adopted, but did not, would have been to embrace

some particular theory of development or career and to see how far our

information allowed us to fit the individuals to this model. As an alternative, we

have tried to use the summary scores and scales to generate by means of

multivariate analysis some organising principle from the data themselves.

The most immediately appealing and the simplest way of doing this is to sort the

individuals in the study into groups or clusters with similar characteristics. These

characteristics would be those represented by the summary scores and scales,

which cover both the full followup period and also give further information on

the current l-year period. In looking for these clusters, we are not so much

seeking to form some typology of alcoholism, but rather to separate out distinct

life courses and pathways through these 10 years.

Such an approach uses no theoretical input, except implicitly in the selecting and

partitioning of the information to be used in the analysis. An alternative

method, which imposes a rather more abstract dimensional structure upon the

data. is principal component analysis. This method of characterising the changes

during the followup period is the subject of a further paper (Taylor et al.,

forthcoming), but it is the cluster analysis which is now to be described. Some

comparisons with the principal components analysis will be drawn later.

Cluster analysis is a notoriously unstable procedure, but there are techniques for

improving its performance. These include using stabilising “secondary”

transformations, selecting representative variables, and replicating analyses by

alternative cluster methods. All of these techniques have been employed in this

particular analysis.

DETAILS OF THE CLUSTER ANALYSIS

In order to maximize the chance of finding a clustering of the individuals, an

initial selection of key variables was made to construct a grouping. In this way,

“noise” or irrelevant differences between people on such a large number of

variables would be kept low. The choice was made from a priori considerations

of the eight most likely variables to show some clustering effect and of further

variables added to this set if they seemed to strengthen the separation between

groups in any way. Variables were deleted from the set if they failed to separate

the groups.

77
The method used was an average linkage hierarchical analysis (Lance and

Williams 1966). made on the Euclidean distances between individuals after a

secondary transformation (Sibson 1972). A second analysis of the data was

carried out by Ward’s method of clustering (Ward 1963) to check for sensitivity

to the particular analysis. The two methods agreed very closely in distinguishing

five groups of individuals, although in one analysis the two closest groups

probably would not have been deemed two clearly separate clusters. This point

is taken up briefly below.

IDENTIFYING THE SEPARATE GROUPS

The following hierarchical diagram (figure 1) shows the cluster structuring.

Beginning at the top of the tree, a very small group of six individuals form the

most clearly distinct grouping. This and the next most prominent group are both

comprised of individuals with high dependence levels--one fares very badly and

the other somewhat better. The remaining three groups are less clearly defined

and form a spectrum running from those faring very badly to those generally

doing very well. It is these last three groupings on the right-hand side of the

diagram that were shown as the least separate groups in the clustering. It will be

seen that the analysis suggests that these three might be fruitfully regarded as a

single continuum, which has been arbitrarily divided at numerically convenient

points.

Hi-dep/B Hi-dep/G Lo-dep/B Lo-dep/M Lo-dep/G

(6) (11) (15) (12) (12)

FIGURE 1

Cluster Structure of the Multivariate Data

(as described in the text)

We can look at these five groupings in detail by looking at their profiles across

all the data that we have for the men. The following table 3 shows this

information and gives the mean score for each of the groups on the variables

used in the cluster analysis.

First, before looking at the drinking behaviour of the groups, it shows the SADQ

scale means, to justify our calling the first two groups “high dependence”--

bearing this labeling in mind will help make the table a little clearer. Note that

the cutoff point on the SADQ suggested by Stockwell et al. (op. cit.) for labeling

“severe” as opposed to “moderate” dependence was a score of 30. In figure 1 and

78
table 3 the terms “Lo” versus “Hi” are intended only as a labeling and might more

properly be termed low-to-moderate versus severe. The first two groups’ means

are too close for us to be able to claim that one is any higher than the other, but

they both appear greater than the other three groups’ means. Within these righthand three groups, there is a gradient from moderately high to low dependence.

(It is not possible to test differences between these groups for statistical

significance, since they result from a cluster analysis of these data and are not

predetermined groupings.)

TABLE 3

Cluster Profiles on the Multivariate Data Set

SADQ 45 50 33 32 15

Alcohol 10yr 64 30 95 56 42

Alcohol 12m 75 7 133 53 48

Troubles 10yr 7.2 1.0 5.0 1.3 0.4

Social Adj. 12m 1.2 2.6 2.1 2.9 3.3

M.Health Adj. 12m 2.3 4.0 3.2 3.9 5.0

Purpose-in-Life 66 111 68 92 116

EPI - N 17 14 16 10 6

Arrests 10yr .83 .33 .45 .27 .08

Treatment 10yr 1.8 1.5 0.8 0.6 0.3

Treatment 12m .50 .08 .oo .oo .oo

AA 12m 1.3 3.1 0.1 .oo 0.0

AA 10yr 1.5 1.9 1.5 1.3 1.2

M.Health 10yr 1.7 1.7 1.8 2.0 2.5

Ph.Health 10yr

Prison 12m

Marriage Brk. 10yr

EPI - E

2.4 2.5 2.5 2.3 2.8

.33 .oo .oo .07 .oo

.50 .42 .45 .47 .33

12 13 1 1 11 12

Hi/B Hi/G Lo/B Lo/M Lo/G

The second section of table 3 shows the amount of drinking over the whole

followup period and over the current year in particular. The gradient across the

low dependence groups is clearly visible in both periods. Note that for the two

high dependence groups the levels of drinking are contained within this range,

except that the “Good” high dependence group has been almost abstinent over the

current year, though not in the past. Note too that the labels “Good” and “Bad”

are used in a relative sense only within each half of the table, in that the “Bad”

high dependence group has mean levels of drinking which are roughly the same

as the “Moderate” low dependence group.

The third section of the table lists some of the other l-year information. The

Troubles scale, which covers predominantly physical withdrawal symptoms in the

79
current year, as might be expected follows the same pattern as current drinking.

Note though that the means are much higher in the high dependence groups than

in the low dependence groups with the same level of drinking. In fact, the small

group of dependent people who have continued drinking show the most extreme

scores of all the groups. The remaining figures follow this same pattern, showing

that in current social adjustment and mental health these groupings are

consistent. The levels displayed in all these measures by even the better high

dependence group--that is, those who are currently nearly abstinent--do not

achieve the levels of the good low dependence individuals.

The fourth section of table 3 shows the continuation of the group profiles. The

first item in the top section shows that the general level of confrontation with

the law throughout the followup period has followed a pattern similar to the

social adjustment score. We can see that treatment experience has been more

intense in the high dependence groups, following the pattern of troubles and

drinking. Treatment in a shorter period of time--the last 12 months--however,

does not relate within the low dependence groups to this pattern; indeed it has

been generally nonexistent for the individuals in these three groups.

Involvement with Alcoholics Anonymous (AA) is interesting, in that we can see

it is predominantly confined to the two high dependence groups and it shows

that the current abstainers are currently heavily involved. In the past, all groups

have been involved with AA to some extent, again rather more amongst the

highly dependent people. General levels of mental health throughout the

followup show the same tendencies as the majority of other measures, but less

strongly.

The final section of the table lists the remaining variables, which did not appear

to relate to the clustering. It is worth recording that followup physical health in

general--as we have measured it--does not correlate at all with the other

variables. Our measure was limited to chronic or life-threatening disorders,

which were in fact rather rare.

The overall patterns here suggest a division between high and low dependence

individuals. The highly dependent people themselves are clearly divided into

those who are now more or less abstinent, and a handful who have continued

drinking. Within the low dependence groupings there is a gradient from bad to

good in almost all the measures we have used.

Whether these groups form distinctly separate processes through the 10 years of

observation or whether they merely divide a continuum of experience is not

central to our analysis here. These divisions, even if they only segregate one

extreme from another, serve to show the relationships between the variables; and

it is these relationships that form the multidimensional structure of the overall

phenomenon. A principal components analysis of these same data yields broadly

similar concepts: that is, the centrality of dependence, drinking, and treatment in

differentiating the overall patterns in the general indicators of well-being. It

would require a larger study to determine which of these two descriptive

methods is the more useful or the more accurate.

THE LIFE CHART DRINKING STATUS DATA

The drinking status data of the original “life chart” for the whole group (in table

2) can now be divided into five separate charts, one for each of these subgroups.

Table 4 shows the amount of time spent, year by year, in troubled drinking. The

80
extent of light, social drinking is not shown--since so little took place, it has

been included for the present with the time spent in abstinence.

TABLE 4

Life Chart Drinking Status Data for Each Cluster

'72 '73 '74 '75 '76 '77 '78 '79 '80 '81

Hi/B 8.3 9.3 9.3 8.5 9.0 8.5 6.5 6.8 5.5 7.0

Hi/G 7.1 5.0 3.8 3.1 5.0 3.9 4.3 1.9 1.9 0.1

Lo/B 10.4 9.8 11.3 11.9 10.8 11.6 11.5 11.7 11.9 10.1

Lo/M 6.7 7.5 6.6 7.1 6.6 6.2 5.7 5.9 5.9 6.1

Lo/G 5.8 6.3 6.8 5.3 5.0 4.5 4.3 4.1 4.0 4.4

Looking first at the three lower dependence groups, we can see that the general

levels of drinking not only differ between them, but that these different levels

have been maintained throughout the followup period, at least for the two worst

groups. The third group, the one that fared best overall, is possibly an exception

showing a very slight drift out of drinking. The worst group of the three has

consistently drunk for almost all of the 12 months in every year.

In the two high dependence groupings, we see a stronger differential. The better

of the two groups shows a marked drift out of drinking. The very small group

of currently drinking, highly dependent people has maintained a steady level of

drinking throughout the followup, and at a level approximately the same as the

middle group of lower dependence drinkers. This last point may seem to reflect

the earlier finding that, for the same amount of drinking, highly dependent

individuals show more serious troubles. Here, however, it should be remembered

that it is the percentage of time spent drinking that is being discussed.

What of the pattern of relapse and recovery within these groups? By examining

separately each individual history it becomes apparent that the improvements in

the high dependence group are made by individuals moving one by one into

abstinence and remaining there, except for one or two scattered slips. The small

group of currently drinking highly dependent men, by contrast, displays the most

variable patterns in and out of drinking, whereas there is only one such

individual amongst the better of the two (high dependence) groups.

Among the groups at the lower end of the dependence spectrum, the worst is

comprised of men who have consistently drunk throughout the period. A few

such individuals find their way into both of the better groups, presumably

because these few do not score so badly on dependence or on the other measures

of health. Why this is so, and whether they will in time move into worse

conditions, are open questions. The best group commonly shows a pattern of

complete abstinence soon after the beginning of the study. The middle grouping

displays a range which includes some highly variable drinking patterns, but also a

81
few individuals from each extreme of the drinking spectrum. This is in keeping

with its being the midrange of a continuum of behaviours.

It is difficult to quantify this information, but a crude index of year-by-year

consistency of behaviour--the average difference between percent of time spent

in one category and percent of time spent in the other--supports these statements

(55%. 88%, and 91%, 77%, 87%. respectively, for the five clusters).

PREDICTIVE FACTORS

The clusters obtained from these followup data can be related to information

from the intake data, in particular to measures of the severity of the drinking

problem as it then was. It must be remembered that these “life-charts” are all

comprised of people who, from the first year onwards, vary greatly in the extent

to which their alcoholism has developed. If there is any consistent relationship

between stages of development and subsequent behaviour, then we would hope to

find a measurable relationship between the measures of severity of problem at

intake and the summary scores by which we have characterised the 10 succeeding

years.

The final table (5) shows how these groups appeared at intake into the study.

This information has not been used in any way in the analysis so far, but we can

see that there is a tendency for the same pattern that existed throughout followup

to have been present at intake. Only the first two items in this table--the daily

alcohol intake (in milliliters) and the Troubles scale (0 to 10)--achieve statistical

significance (p < .05), but with such small numbers of people this is scarcely

surprising. Nonetheless, these two items suggest that both the groups

subsequently classified as high dependence groups had a worse problem to begin

with. This is supported by a crude intake dependence measure--a rating of

“severe” as opposed to “moderate,” made from case notes by an independent

clinician involved in developing the SADQ--being greatest for these two groups.

Similarly, some gradient was already present across the three low dependence

groups. In fact, the Troubles score at intake correlates .44 (p < .01) with the

subsequent SADQ score, the highest correlation that was found between intake

and followup measures.

TABLE 5

Cluster Profiles on Selected Variables

Measured at Intake into the Study

Hi/B Hi/B Lo/B Lo/M Lo/G

Daily Alc. 556 388 413 311 271

Troubles 6.8 6.1 5.5 4.1 3.1

Dependence .67 .67 .64 .36 .42

Previous Trtmt. .33 .50 .64 .40 .17

Yrs of Problem 5.8 4.9 6.1 3.9 2.2

Age at Intake 34 39 40 39 40

82
In the lower half of the table, the variables relating to the history of the

alcoholism problem prior to intake are shown. These show rather weak

patterning, but do suggest that the worst lower dependence group (Lo/B) might

have had a long-standing problem. It is interesting to note that this group, who

drank for almost 12 months in every year of the followup, were even previously

a long-standing problem group. As to how they have maintained this status and

an average SADQ score of 33, suggesting some of them would rate only

moderately dependent, we can only speculate. There is, of course, no reason

why everyone who drinks heavily should move from moderate into very severe

dependence in terms of the syndrome measured by the SADQ (see, for example,

Edwards et al. 1986). These individuals, who in general fare badly, are possibly

distinguished by not experiencing the high dependence levels of the Hi/B group

nor their resulting treatment and intermittent abstinence.

CONCLUSIONS

The patterns of drinking and abstinence which have been recorded vary

enormously. There is a set of “hardline” drinkers, who have drunk in a heavy or

troubled fashion more or less continuously throughout the 10 years. There are

some who have moved into abstinence at various points over the years, and who

are still abstinent; and there are others whose pattern has been to move to and

from abstinence in irregular fashion. These two latter patterns, in particular, are

more prominent in the groups showing higher levels of dependence.

Little relative change seems to have occurred amongst the majority of people in

the study, in the sense that at intake the group profiles on drinking and

associated troubles were similar to those at followup. It is not possible to say

whether they have generally improved or worsened in an absolute sense, because

of the different measuring procedures used at intake and follow-up. However,

one scale which is consistent is the “Troubles” scale, and the mean ratings are

much the same now as they were then.

The overriding and most important impression from these figures is that

behaviour throughout the followup period is at least a two-dimensional

phenomenon. Clearly, dependence is a powerful concept in separating out these

individual life courses in respect to their abstinence, drinking relapses, and

treatment, as well as their other indicator scores. Where there has been a shift

into abstinence, it has been the highly dependent people who have

disproportionately experienced it. Even so, for these abstaining, highly

dependent people, their general well-being in other areas of their life does not

match that of the best lower dependence group. It is clear that the categories

developed by the cluster analysis are not just characterised by drinking

behaviour. but also by the other measures used. Whether this categorisation will

be useful or not is a question that awaits an answer, and which we will attempt

to assess when we analyse the detailed tape recordings.

The group with the worst drinking record has not experienced (nor yet acquired)

the worst levels of dependence, even though they tended to have at intake a

long-standing problem. Rather, the worst dependence levels are associated with

some of the lowest levels of well-being as measured by our indicator scores,

possibly in conjunction with a pattern of treatment and relapse. The suggestion

in these figures that this group at intake was the youngest on average and had

the highest daily alcohol consumption comes from too small a sample to be

substantiated. It should be recalled, too, that individuals in this group appear

more erratic in their drinking record; and that both the highest dependence

83
groups have undertaken treatment more than any of the others. On a speculative

basis, therefore, it might be argued that the processes underlying relapse and

recovery might profitably be regarded differently amongst the highly dependent

groups than amongst moderate dependence drinking groups.

Part of the aim of this analysis, as previously stated, is to provide a framework

for our subsequent analyses of the tape-recorded material. We hope in those

analyses to be able to relate the present distinctions to the larger, unanswered

questions given at the outset. Have the right dimensions been used by which to

measure career, and has the measurement methodology been adequate? Will this

discrete, grouped structure prove more or less valuable than a continuum

approach; and what, if anything, will characterise the development processes

within these groups?

REFERENCES

Crumbaugh, J.C. Cross-validation of Purpose-in-Life test based on Frankl’s

concepts. J Individ Psychol 24:74-81, 1968.

Duckitt, A.; Brown, D.; Edwards, G.; Oppenheimer, E.; Sheehan, M.; and Taylor,

C. Alcoholism and the nature of outcome. Br J Addict 80:153-162, 1985.

Edwards, G.; Orford, J.; Egert, S.; Guthrie, S.; Hawker, A.; Hensman, C.;

Mitcheson, M.; Oppenheimer, E.; Taylor, C; and Cobley T. Alcoholism: A

controlled trial of “Treatment” and “Advice”. J Stud Alcohol 38:1004-1031,

1977.

Edwards, G.; Duckitt, A.; Oppenheimer, E.; Sheehan, M.; and Taylor, C. What

happens to alcoholics? Lancet July 30:269-271, 1983.

Edwards, G.; Brown, D.; Duckitt, A.; Oppenheimer, E.; Sheehan, M.; and Taylor,

C. Normal drinking in a recovered alcohol addict. Br J Addict 81:127-137,

1986.

Edwards, G.; Brown, D.; Duckitt, A.; Oppenheimer, E.; Sheehan, M; and Taylor,

C. Outcome of alcoholism: The structure of patient attributions as to what

causes change. Br J Addict (forthcoming).

Eysenck, H.H., and Eysenck, S.B.G. Manual of the Evsenck Personality

Inventory. London: Hodder and Stoughton, 1964.

Lance, G.N., and Williams, W.T. Computer programs for hierarchical polythetic

classification. Comp J 9:60-64, 1966.

Sibson, R. Order invariant methods for data analysis. J Royal Statist Soc (B)

34:311-349, 1972.

Stockwell, T.; Hodgson, R.; Edwards, G.; and Rankin, H. The development of a

questionnaire to measure the severity of alcohol dependence. Br J Addict

74:79-87, 1919.

Taylor, C.; Brown, D.; Duckitt, A.; Edwards, G.; Oppenheimer, E.; and Sheehan,

M. Patterns of outcome: Drinking histories over ten years among a group of

alcoholics. Br J Addict 80:45-50, 1985.

Taylor, C.; Brown, D.; Duckitt, A.; Edwards, G.; Oppenheimer, E.; and Sheehan,

M. Alcoholism and the patterning of outcome: A multi-variate analysis. Br

J Addict (forthcoming).

Ward, J.H. Hierarchical grouping to optimise an objective function. J Amer

Statist Ass 58:236-244, 1963.

ACKNOWLEDGMENTS

David Brown’s contribution to this work was supported by the Health Promotion

Research Trust, while other staff were funded by the Addiction Research Unit’s

Medical Research Council Programme Grant.

84
AUTHORS

Colin Taylor

David Brown

Anni Duckitt

Griffith Edwards

Edna Oppenheimer

Margaret Sheehan

Addiction Research Unit

Institute of Psychiatry

101 Denmark Hill

London SE5 8AF

85
Relapse and Recovery

Among Opioid Addicts 12 Years

After Treatment

D. Dwayne Simpson and Kerry L. Marsh

Conceptual formulations involving drug abuse and the addiction process include a

variety of physiological, psychological, social, and environmental factors. Many

of the drug abuse “theories” presented by Lettieri et al. (1980) focus attention on

separate and sometimes unique etiological factors, but more conceptual

integration is necessary to deal with the complex stages of addiction careers--

including initiation, maintenance, relapses, and termination. Longitudinal studies

of addiction designed to address these conceptual domains are an important part

of this theoretical development and refinement process.

Empirical evidence of relapse and recovery among opioid addicts over a period

of approximately 12 years after admission to community-based treatment

programs is presented in this chapter. The data include multiple episodes of

daily opioid use and abstinence over time. Several analytic strategies have been

used to explore the complex relationships involved in “relapse” and “recovery,”

terms which generally carry a medical connotation of “sick” or “well.” A broader

interpretation of these terms, however, is necessary when addiction outcomes are

studied. That is, instead of focusing only on whether or not there was a return

to drug use during a followup period, it may be more informative to examine

fluctuations in drug use over time as well as other related outcomes, such as

criminal involvement and employment. Operationally, the term relapse in the

analyses of opioid addicts presented here refers to the reoccurrence of daily

opioid use after a temporary period of abstinence from daily use. Reduction of

drug use, criminal involvement, and unemployment are considered to be general

indicators of recovery. These measures are also examined in relation to several

domains of theoretical influence as discussed in previous chapters.

The data used in this chapter--the Drug Abuse Reporting Program (DARP)--

were initiated in 1969 for the purpose of describing and assessing clients and

services in community-based drug abuse treatment programs. During 1969 to

1973, intake records were obtained on almost 44,000 admissions to 52 federally

funded agencies from across the United States. Since that time, data collection

and research have been conducted to evaluate during-treatment performance

(Sells 1974; Sells and Simpson 1976), posttreatment outcomes in the first few

years following DARP treatments (Sells and Simpson 1980; Simpson and Sells

1982), and long-term outcomes based on If-year followup studies of opioid

addicts (Simpson et al. 1986a, 1986b). This study focuses on relapse and

recovery of addicts over time. After describing the sample, the first section

86
summarizes outcomes at different points in time from the DARP preadmission

baseline period to the 12-year followup interview. Since many addicts

experienced repeated cycles of abstinence and addiction over time, the second

and third sections describe relapse and recovery episodes during Years 1-6 and

during Years 7-12, respectively. Finally, the fourth section examines social

adjustment indicators associated with relapse.

DESCRIPTION OF THE SAMPLE

6-Year Followup. The first two cohorts of admissions to drug abuse treatment

programs in the DARP (June 1969 through May 1972) totaled 27,214. Using this

population, the initial wave of the 6-year DARP followup studies (Simpson and

Joe 1977) included a stratified random sample of 4,107 opioid and nonopioid

drug users from 25 different treatment agencies in the United States. Of this

sample, 87% of the cases were located, and successful interviews were completed

with 3,131 respondents (i.e., 76%). The stratification factors for the sampling

procedure included DARP treatment classification, time in treatment, race-ethnic

group, sex, age, and treatment agency. Treatments included methadone

maintenance (MM) programs, therapeutic communities (TC), outpatient drug-free

treatments (DF), and outpatient detoxification (DT); an intake only (IO) group

was also selected, comprised of persons who completed intake and admission

procedures but who did not return for treatment in DARP. (The IO group in

this study was viewed as an important comparison group but not as a control

group since the DARP treatment groups were not formed through random

assignment.)

12-Year Followup. From the completed 6-year followup interviews described

above, a sample of 697 cases was subsequently selected for the 12-year followup

study. All were daily opioid users at the time of admission, and the sample

included black and white males from all five treatment groups, as well as black

and white females from methadone maintenance treatment programs. The sample

was drawn from 18 different DARP treatment agencies, as explained by Simpson

(1984a). The fieldwork, including locating and interviewing the sample, was

carried out under contract during 1982 and 1983 by the National Opinion

Research Center (NORC). Altogether, 80% of the cases were located: 490 (70%)

were interviewed after granting informed consent, 52 (8%) were deceased, and 13

(2%) refused to be interviewed. The remaining 142 (20%) were not located

before time and resources for the fieldwork ran out. Analysis of treatment

admission and 6-year followup data revealed no evidence of sampling bias

associated with the nonlocated cases in the 12-year followup study (Simpson

1984a).

The followup interviews were conducted face-to-face by trained interviewers

using strict procedures to protect the confidentiality of information. Average

duration of the interviews was approximately 2 hours, for which the respondent

was paid $15. The interview assessed behavioral changes and outcomes over

time, as well as psychological and social factors involved throughout the

addiction career. Major criterion behaviors included illicit drug use, drug abuse

treatment, alcohol use, employment, and criminality. Checks for internal

consistency and comparisons of self-reported information with results of

urinalyses and with criminal justice records of post-DARP incarcerations

indicated a high level of reliability and validity of the data (Simpson 1984b).

The sample of 490 former opioid addicts was comprised of 18% females and 82%

males (a difference due to sampling constraints in the treatment population),

87
included 51% blacks and 49% whites, and had a median age of 34 at the time of

the 12-year followup interview (with 19% over 40 years of age). However, the

findings presented in this chapter are based only on males (N = 405) since the

female sample was relatively small and several outcome measures presented below

are differentially associated with gender. For instance, a study by Marsh and

Simpson (1985) which focused on the female sample found that sex-related

differences exist on several behavioral measures (such as employment and

criminality) as well as psychological factors (such as motivations for treatment).

Sociodemographic and DARP treatment characteristics of the male sample are

described in table 1.

OUTCOMES OVER TIME

Behavioral outcomes over time, from the pre-DARP baseline throughout the 12-

year followup period. are summarized in table 2. The 6-year followup study

obtained information on a retrospective month-by-month basis for Years 1-6--

from termination of DARP treatment until the Year 6 followup interview. Thus,

it served as the basis for outcome tabulations in Years 1 to 3 immediately after

termination of DARP treatment and Year 6 subsequent to admission. The 12-

year followup study served as the basis for outcome tabulations in Year 12 after

admission. Tabulations for drug use and employment measures in each time

period were based only on “time at risk” (i.e., while persons were not confined in

jail or residential treatment facilities).

Individual measures of drug use are grouped into three different categories in

table 2, which include opioids (heroin, illegal methadone, and other opiates),

marijuana, and other nonopioids (cocaine, amphetamines/stimulants,

barbiturates/sedatives, and hallucinogens). Other individual measures include

time spent in jail or prison and 6 months or more each year of employment (i.e.,

at least 50% of the months at risk each year). Simpson et al. (1986a) examined

these data in detail and noted that the 12% increase in nonopioid use from Year

6 to Year 12 primarily represented cocaine use.

In order to examine different outcome measures simultaneously, the sample was

classified into six mutually exclusive categories, which are shown in table 2 and

illustrated in figure 1. These categories emphasize drug use and incarcerations

during each year. The first category includes persons who were institutionalized

for the entire year (usually in jail or prison, except for residential treatment in a

few cases). The second and third categories include daily opioid users (in 1 or

more months) in combination with and without jail. The fourth category

represents those who were in jail or prison (for 1 or more months) but who were

not daily opioid users. (This category was divided almost equally between

persons with no drug use and those who continued to use opioids less than daily

or who used other nonopioid drugs.) Finally, the last two categories had no jail

and low drug involvement; category five included less-than-daily opioid users

(defined as the use of opioid and/or nonopioid drugs in 1 or more months, but

no daily opioid use), and category six included those with no drug use (defined

as no use of any drugs during the year, with the exception of less-than-weekly

marijuana use).

These data indicate that, following substantial declines in daily opioid use and

incarcerations in the early years of the followup period, category size tended to

stabilize over time. It should be noted, however, that the pre-DARP measure for

jail and prison represented a lifetime rate since I-year preadmission baseline data

were not available. During Year 6 and Year 12, about one-fourth of the sample

88
TABLE 1

Description of the Sample

at Admission to DARP Treatment (N = 405)

Male

Black

White

Under 21 years old

21-25 years old

26-30 years old

Over 30 years old

Ever arrested

Ever jailed

Employed any time last year

DARP Treatment Assignment:

Methadone maintenance

Therapeutic community

Outpatient drug-free

Outpatient detoxification

Intake only

100%

53%

47%

25%

39%

20%

16%

87%

71%

67%

22%

24%

18%

21%

15%

89
TABLE 2

Outcomes Over Time for Male Addicts (N = 405)

Pre- Years During Followup

DARP 1 2 3 6 12

INDIVIDUAL MEASURES

% Daily Opioid Use

% Any Opioid Use

% Marijuana Use

% Any Nonopioid Use

% Any Jail/Prison

% Employed 6 Mos.

or More

100

100

51

55

71

36

OUTCOME CATEGORIES

(Mutually Exclusive)

% Institutionalized 3

% Daily Op + Jail 68

% Daily Op + No Jail 29

% Jail (No Daily Op) 0

% No Jail + <Daily Op 0

% No Jail + No Drug Use 0

FAVORABLE RECOVERY PROFILES

% No Drugs

+ No Jail

+ 100% Employment 0

% No Daily Drugs

+ No Jail

+ Any Employment 0

47 34 28 25 24

63 51 45 42 39

55 56 51 57 61

39 35 34 35 47

33 33 30 30 29

49 57 61 64 54

3 8 8 7 9

19 15 1 1 12 11

26 16 15 1 1 13

12 10 1 1 1 1 10

21 28 27 33 25

19 23 28 26 32

8 12 14 12 1 1

25 32 37 39 30

Note. For pre-DARP measures, drug use was based on the last 2 months

before admission to DARP, employment was based on the last 12 months, and

incarceration in jail or prison was a lifetime measure. Sample sizes were

adjusted in each time period so that tabulations were based only on persons who

were “at risk” (e.g., persons in jail during an entire year were omitted from drug

use and employment tabulations for that period).

90
FIGURE 1

OUTCOMES OVER TIME
continued daily opioid use, and almost half of these daily users also spent time in

jail. About one-fifth of the sample continued to be incarcerated for all or part

of each year in the followup period, even though they were not using opioids

daily. Thus, 57% of the sample appeared to be making reasonable adjustments

by Year 12 since they were not jailed and did not use opioid drugs daily.

Indeed, over half of the former addicts in these two categories in Year 12

reported no drug use at all (except less-than-weekly marijuana in some cases).

Judgments about favorable recovery from addiction are value-laden and must be

made in the context of expectations and standards formed by numerous factors.

Selection of appropriate criteria, performance levels for specified criteria, and

various environmental constraints and influences are but a few of the factors that

may be involved. Needless to say, judgment standards may vary, and outcomes

considered favorable by one evaluator are not necessarily acceptable to another.

To illustrate, two examples of “favorable recovery profiles” are presented at the

bottom of table 2. The first profile extends the logic of outcome category six

(i.e., No Jail + No Drug Use) described above by adding 100% employment as a

criterion (i.e., being employed during every month). Only 8% to 14% of the

sample met these highly restrictive and demanding recovery standards in any one

year of the followup period, a reduction to only one-third to one-half of the

previously defined No Jail + No Drug category. In view of the limited

employment opportunities frequently available as well as the problems inherent in

reducing daily opioid habits to absolute abstinence, less restrictive standards

could be considered acceptable and more realistic. For example, this might

include “No Daily Drugs + No Jail + Any Employment,” as shown at the bottom

of table 2. Using this standard, 25% to 39% of the sample would qualify as

recoveries in each year of the followup.

RELAPSES TO DAILY OPIOID USE BY YEAR 6

The 6-year followup interview included month-by-month behavioral outcomes

beginning at the point of DARP treatment termination. Due to the variability in

treatment length, however, the sample varied in the number of months of data in

the 6-year followup interval: 97% of the sample had 24 months or more, 84%

had 36 months or more, and 64% had 48 months or more. Therefore, these data

were well suited to the study of relapse using survival analysis methods, as

reported by Joe et al. (1985a).

Relapse data from the 6-year followup study are summarized in table 3. Of the

total sample of 405 male addicts, 44% quit daily opioid use during DARP

treatment and reported no relapses by the Year-6 interview. Another 35%

resumed (or in some cases just continued) daily opioid use in the first month

immediately after termination from treatment; a few (1%) continued without

interruption throughout the 6-year followup period, 19% quit sometime later and

had no more relapses through Year 6, and the remaining 15% quit and relapsed

one or more times. Finally, 21% were abstinent for 1 or more months following

treatment, but later relapsed at least once. In summary, over one-third (36%) of

the sample had one or more relapses during the 6-year followup interval, when

“relapse” is defined as a return to daily opioid use after 1 or more months of

abstinence.

How is length of abstinence from daily opioid use related to subsequent relapse?

In order to examine abstinence rates over time, the first period of abstinence

from daily opioid use for 1 month or longer was selected for each person. The

92
TABLE 3

Summary of Data for Relapse to Daily

Opioid Use by Year 6 Followup (N = 405)

I. Quit & No Relapse by Year 6 180

II. Immediate Daily Use After DARP 140

a. Continuous Use Thru Year 6 5 1%

b. Later Quit--No Relapse 77 19%

c. Later Quit--l Relapse 31 8%

d. Later Quit--2-3 Relapses 23 6%

e. Later Quit--Over 3 Relapses 4 1%

III. Delayed Relapse After DARP 85

a. 1 Relapse 53

b. 2-3 Relapses 27

c. Over 3 Relapses 5

Number

of Persons

Percentage

of Total

44%

35%

21%

13%

7%

1%

TABLE 4

Abstinence Rates During the First 42 Months’

After Initial Abstinence from Daily Opioids in Years 1-6

Minimum

Period of

Abstinence

3 Months

% Still Abstinent in Month Sample

6 9 12 15 18 21 24 27 30 36 42 Size

92 86’ 80 74 71 68 67 66 63 61 59 252

6 Months 93 87* 80 77 74 72 71 68 66 63 233

12 Months 92 89* 85 83 82 79 76 73 202

24 Months 99 95* 91 88 168

1Only those persons who had at least 42 months of data, beginning with first

month of the designated period of abstinence, were included in these analyses.

*Identifies abstinence rates 6 months after the period of minimum abstinence.

_(Underline) Identifies abstinence rates 12 months after the period of minimum

abstinence.

93
total length of this first abstinence period for each person was determined, and

abstinence rates over the following 42 months were calculated as shown in table

4. These data can be used to estimate the probability of maintaining abstinence

over time, given the initial duration of abstinence. For instance, table 4 shows

that 86% of those with a minimum abstinence period of 3 months were still

abstinent in Month 9 (i.e., 6 months later), while 95% of those with at least 24

months of abstinence were still abstinent 6 months later (in Month 30). For

abstinence at 12 months later, the rates for these two groups were 74% and 91%,

respectively. In other words, 74% of the former addicts able to maintain

abstinence from daily opioid use for at least 3 months were still abstinent a year

later, compared to 91% of those able to maintain abstinence for at least 24

months.

Although the DARP database is not comprehensive with regard to various

month-by-month events which immediately preceded and possibly influenced

relapse to daily use by Year 6, records were available on other drug use. These

data showed that about one-third (i.e., 31%) of the 143 persons in the sample

who relapsed by Year 6 used opioids less-than-daily within the last 3 months

immediately before relapse (and 27% used within the last month). The other

two-thirds therefore relapsed to daily use more abruptly and without extended

transitional use in the preceding months.

RELAPSES TO DAILY OPIOID USE BY YEAR 12

At the time of the 12-year followup, addiction careers in this sample ranged

from 1 to 35 years, with a median length of 9.5 years. Almost one-fourth of the

sample reported I or more months of daily opioid use in Year 12, down from

47% in the first year after DARP treatment.

Table 5 indicates that individuals who used opioids daily were not always the

same from one year to the next. Daily opioid use declined from 47% to 24%

between Years 1 and 12 (as indicated in column I), but the cumulative tally in

column II shows that 75% of the sample used opioid drugs daily sometime during

this followup. Finally, column III reveals that 15% had at least one relapse after

quitting during Year I, increasing to 65% those who relapsed one or more times

by Year 12. Thus, 35% of the sample never relapsed again after they eventually

quit.

Aside from describing daily opioid use trends through Year 12, the tabulations in

table 5 present several alternative drug use outcome measures using the same

database. Percentages of daily users for successive time intervals--shown in

column I--appear much more favorable than the cumulative tabulations in

columns II and III, but all are technically appropriate methods for describing

outcomes. Although not reported in table 5, another different and equally

appropriate procedure for describing daily opioid use outcomes is the length of

time since last addicted before the 12-year interview. For example, 76% of this

sample had not used opioids daily in the last year before followup, 68% in the

last 2 years, 63% in the last 3 years, 48% in the last 6 years, 35% in the last 8

years, and 29% in the last 10 years. Finally, 25% reported no daily opioid use at

all following DARP treatment.

Because of methodological and conceptual differences in the data-collection

procedures used for the 6-year and 12-year followup studies, the same relapse

analyses could not be extended directly to the 12-year data. In particular, the

12-year study did not obtain records on month-by-month drug use and other

94
TABLE 5

Comparisons of Measures for Daily

Opioid Use Over Time

I II III

Current Cumulative Cumulative

% of Daily % of Daily % Who Quit

Users Users and Relapsed

Year 1 Post-DARP 47 47 15

Year 2 Post-DARF 34 50 25

Year 3 Post-DARP 28 53 31

Year 6 Followup 25 56 35

Year 12 Followup 24 75 65

Note. Figures for Year 12 (representing the years between 6 and 12) were

calculated from the 12-year followup interview using data-collection methods

different from those in the 6-year followup interview, and this may have

affected the comparative precision of the Year 6 and Year 12 cumulative data in

columns II and III. Also, it is noted that Years I, 2, and 3 Post-DARP refer to

the time immediately following DARP treatment; the followup interviews were

conducted an average of about 6 and 12 years, respectively, after DARP

treatment began, and the data for Year 6 and Year 12 are based on the 12

months immediately before each interview.

95
behavioral outcomes; instead, the 12-year data focused more on interpretations

and perceptions of respondents regarding their addiction histories, the events and

reasons associated with various career phases, and their long-term outcomes on

the behavioral criteria studied in earlier DARP research. It was possible,

however, to link the 6-year and 12-year data in other ways to study relapse and

recovery. Of special interest was the comparison of periods of abstinence from

daily opioid use in Years l-6 (recorded in the 6-year followup) with outcomes in

Years 7-12 (obtained from the 12-year data). Based on the results presented

above from the 6-year data, it was expected that longer abstinence during Years

1-6 would be associated with better outcomes in Years 7-12.

To examine these relationships, the sample was first classified according to the

longest period of continuous abstinence from daily opioid use during the 6-year

followup interval. Five abstinence groups were defined--including 0-12 months

(11% of the sample), 13-24 months (18%), 25-36 months (23%), 37-48 months

(28%), and over 48 months (20%)--and then used to examine outcomes in Years

7-12.

Table 6 presents results for daily opioid use in Years 7-12, Years 10-12, and

Year 12; Year 12 data also includes Any Opioid Use, Any Jail or Arrests, and

50% Employed (i.e., employment during one-half or more of months at risk).

Daily opioid use information was obtained in the 12-year interview by asking

how long it had been since the respondent last used opioids daily, and this was

the source of data for the Years 7- 12 and Years 10- 12 analyses. More thorough

behavioral outcomes were obtained for the last year before interview, and these

data served as the basis for the Year 12 analyses.

Consistent with earlier findings, table 6 indicates that length of abstinence in

Years 1-6 was significantly related to outcomes in Years 7- 12. That is, persons

with longer abstinence had better long-range outcomes; 72% of the 0-12 month

abstainers in Years 1-6 returned to daily opioid use during Years 7-12, compared

to 33% of those who had over 48 months of abstinence. For the last 3 years of

the followup period (Years 10-12). these rates were 61% and 25%. respectively;

and for the last year (Year 12), they were 35% and 12%. These results for Year

12 also generalized to other behavioral measures, as observed at the bottom of

table 6. In particular, longer periods of abstinence were associated with better

outcomes on the criteria for Any Opioids, Any Jail or Arrests, and 50%

Employment.

FACTORS ASSOCIATED WITH RELAPSE AND RECOVERY

Several “reasons” were found to be almost universally reported as causes for

relapses--including the state of relaxation caused by opioids (91%). the rush

(85%), the need to avoid or eliminate withdrawal symptoms and drug craving

(81%), and the use of opioids to help forget troubles (80%). Similarly, the most

common reasons for quitting daily opioid use, as reported by those who were

abstinent a year or longer before the 12-year followup, included “being tired of

the hustle” (83%) and “needing to change after hitting bottom” (82%). Because

they were so common, these reasons are not very discriminating; in addition, they

appear to represent more of a background or contextual setting than explicit

causes which precipitate and sustain behavioral change.

Simpson et al. (1986a, 1986b) have described in detail the reasons given for

addiction stages, and Joe et al. (1984) have examined relationships among the

reasons associated with different stages. Using canonical correlation analysis,

96
TABLE 6

Outcomes in Years 7-12, by Longest

Abstinence from Daily Opioids in Years 1-6

Longest

Abstinence

in Years 1-6

% of Grouo Revortinn

Daily Any Any Jail 50% Sample

Ovioids Opioids or Arrests

Years 7-12 (Last 6 Years)

Employed Sizes

0-12 mos. 72 - - - - - - 46

13-24 mos. 58 - - - - - - 73

25-36 mos. 43 - - - - - - 94

37-48 mos. 38 - - - - - - 111

Over 48 mos. 33 - - - - - - 81

X

2

(df=4) 24.8*** - - - - - -

Years 10-12 (Last 3 Years)

0-12 mos. 61 - - - - - - 46

13-24 mos. 42 - - - - - - 73

25-36 mos. 38 - - - - - - 94

37-48 mos. 32 - - - - - - 111

Over 48 mos. 25 - - - - - - 81

X

2

(df=4) 18.9*** - - - - - -

Years 12 (Last Year)

0-12 mos. 35 55 57 37 46

13-24 mos. 30 43 58 41 73

25-36 mos. 27 44 40 51 94

37-48 mos. 21 30 41 63 111

Over 48 mos. 12 30 38 63 81

X

2

(df=4) 11.6* 11.2* 10.27* 15.1**

Note. Outcome data other than daily opioid use are not available for Years

7-12 and 10-12.

*p<.05

**p<.01

***p<.001

97
they found that reasons for changes across stages were related; for example, there

was a tendency for interpersonal relations at different stages to be more

consistently involved in influencing addiction processes for some individuals than

others. Further analyses of these and related factors associated with length of

addiction (Joe et al. 1985b) extended these results by finding evidence for

complex and multiple paths of addiction. For instance, one “lifestyle” associated

with length of time addicted was represented by a subgroup of employed addicts

who supported themselves during longer-than-average addiction careers (possibly

because they experienced fewer street risks than nonworking addicts). They also

found that longer addictions were reported by persons with lower educational and

socioeconomic background, higher social and criminal deviance throughout

careers, higher susceptibility to environmental and drug availability factors, and

higher responsiveness to family influences.

The most recent development in the study of these longitudinal predictors has

been to focus on relapse using event history analysis for modeling survival curves

(Joe et al. 1985a). The results have been consistent with other DARP research,

as well as with earlier literature reviewed by Platt and Labate (1976), in showing

that addicts with the lowest risk of relapse to daily opioid use typically included

those who were married, older, better educated, better employed, less (criminally)

deviant, and better adjusted psychologically than the others. In other words,

social adjustment emerges as a major predictive construct involved in relapse and

recovery. To explore this concept further, therefore, the sample was classified

with regard to social adjustment indicators based on (1) pre-DARP admission

data and (2) post-DARP followup data from Years 1-6. These groups were then

used to compare relapse and related criteria from the 12-year followup.

First, the sample was classified using intake information collected at the time of

DARP treatment admission; that is, the number of “positive” social adjustment

characteristics (i.e., married, over 27, over 12 years of education, no previous

incarcerations, and 6 months or more employment in the previous year) were

counted for each person, and the sample was divided into “high” and “low”

groups. Next, the sample was classified again (independently of the previous

classification) using post-DARP information from Years 1, 2, 3, and 6 of the 6-

year followup; for each separate year, the number of “positive” characteristics

(i.e., no jail, 6 months or more employment, and no more than 1 residential

move) were counted and then summed over the four l-year periods. Based on

these summed scores, the sample was divided into “high” and “low” groups. These

pre-DARP and post-DARP classifications were then used to form four groups

defined by social adjustment levels at DARP admission and during the 6-year

followup. These groups were labeled High-High (n = 117), High-Low (n = 110),

Low-High (n = 95), and Low-Low (n = 83).

Comparisons of 12-year outcomes for these four groups are summarized in table

7. In brief, the low-level social adjustment groups--especially those with low

adjustment during the 6-year followup period--had the poorest outcomes. Over

the entire period of Years l-12, relapse to daily opioid use was reported by 51%

to 81% of these groups, and it was highest for the two groups with low social

adjustment during the 6-year followup (i.e., Hi-Lo and Lo-Lo). Daily opioid

use during Years 7-12 was 41% for the Hi-Hi group, 38% for the Lo-Hi group,

48% for the Hi-Lo group, and 57% for the Lo-Lo group. Likewise, the same

basic pattern was observed for Years 10-12 (the last 3 years before the

interview), and they generalized to criminality and employment measures in Year

12. All were statistically significant except for daily opioid use in Year 12.

98
TABLE 7

12-Year Outcomes by Social

Adjustment indicators Over Time

Outcomes

Years 1- 12:

% Ever relapsed

to daily opioids

Social Adjustment Levels, Classified at

DARP Intake and for 6-Year Followup X

2

Hi-Hi Lo-Hi Hi-Lo Lo-Lo (df=3)

% % % %

58 51 75 81 24.7*

Years 7- 12:

% Used opioids daily

Years 10-12:

% Used opioids daily

41 38 48 57 7.6*

35 27 39 48 8.6*

Year 12:

% Used opioid daily

% Employment 50%

or more

23 19 25 29 30.2**

62 64 41 44 15.4**

*p=.05

**p<.01

99
Inspection of these data indicates that outcomes for the two groups with high

social adjustment levels during the 6-year followup (Hi-Hi and Lo-Hi) were

comparable, and they were more favorable than those for the two groups with

low levels of social adjustment in the 6-year followup (Lo-Lo and Hi-Lo).

Thus, indicators of social adjustment at treatment admission were less important

than those for the 6-year followup when predicting Years 7-12 outcomes. The

previous findings by Joe et al. (1985a) showing that admission data served as

significant predictors were based on survival curves, beginning immediately after

treatment (i.e., Year 1). Changes occurred in social adjustment levels over time

for some individuals, however, and the present data show that the most recent, or

proximate, indicators of adjustment appear to be the most pertinent for

predicting outcomes.

CONCLUSIONS

Compared to similar research based on smoking and alcohol, the study of users of

opioid and other illicit drugs in our society is complicated by several barriers to

observing and measuring these illegal behaviors. Changes over time in the legal

status and the availability (as well as quality) of drugs represent highly complex

influences on individual decisions about using drugs, That is, random

fluctuations in the quality and availability of drug supplies have moderating

effects on various social, psychological, and physiological factors involved in

illicit drug use by individuals. Environmental constraints, such as confinements

in jail or residential treatments, must also be recognized in identifying “time at

risk” for analyzing and interpreting drug use outcomes at any given time, and

especially before other factors are analyzed as influences in the relapse or

recovery process.

The longitudinal research findings presented here are helpful in establishing

“baseline” expectations for the long-term outcomes of opioid addicts. Among

male addicts admitted to the DARP in 1969-73, 53% had no daily opioid use in

the first year after treatment, and this rate increased to 66% in the second year

and to 72% in the third year. During the sixth year after admission to treatment,

75% of the sample reported no daily opioid use. This percentage remained

virtually unchanged 6 years later (at Year 12).

Significantly, 19% of the sample who used opioid drugs daily at some time

during Years 7-12 after admission to treatment did not use them daily in the

previous Years 1-6. This illustrates the long-term threat of relapse over time.

One-fourth (25%) of the sample never used opioids daily during the 12-year

followup period, but 65% quit for a month or longer and then relapsed to daily

use one or more times. By the end of Year 12, however, 63% of the sample had

not used opioid drugs daily for a period of at least 3 years.

These data show that relapse to daily opioid use is prevalent among addicts.

However, relapse is neither a random nor a certain occurrence. Multiple episodes

of the abstinence-relapse cycle occurred for many addicts, but resistance to

relapse increased as the period of abstinence became longer; and these behavioral

improvements also generalized to lower rates of arrests and incarcerations, as well

as more employment. Unfortunately, there was no apparent threshold for length

of abstinence which insured permanent recovery. Instead, there was a

probabilistic decrease in the subsequent occurrence of relapse as abstinence

became longer.

100
Indicators of social adjustment or adaptation during Years l-6 (i.e., higher

employment, less legal involvement, and fewer residential moves) likewise

predicted abstinence from daily opioid use in Years 7-12. Although similar

social adjustment criteria measured at treatment admission--including marital

status, age, educational achievement, and employment history--predict relapse

rates beginning in the first year following treatment (Joe et al. 1985a), these

particular measures are generally unrelated to long-term outcomes recorded years

later. As Lehman and Simpson (1984) and Lehman et al. (1985) have reported,

the statistical significance of most predictor variables diminishes as outcome

measures become more temporally distant.

The DARP followup studies give support to several major theoretical domains--

sociological, psychological, physiological, and environmental--as being influential

factors in the stages of opioid addiction, relapse, and recovery. For example,

major reasons cited for starting opioid use include the psychological euphoria and

sensation, easy availability, and social pressures. Psychological escapism and

euphoria were major reasons for sustaining opioid use over time, while the

relative significance of social influences during this stage diminished. “Drug

craving” emerged later as a factor in the maintenance and relapse of drug use.

Reasons for quitting addiction primarily involved personal psychological crises,

along with family and social pressures, and such environmental factors as legal

threats and drug availability (Joe et al. 1984). In addition, the role of drug abuse

treatment over time was regarded by most addicts as significant in the process of

recovery (Joe et al. 1982-83; Marsh et al. 1985; Simpson 1984c).

For treatment programs, these results emphasize the importance of aiming to

change short-term behaviors and identifying appropriate support mechanisms and

social networks to maintain improvements over time. Fortunately, from a

therapeutic point of view, client characteristics and background at intake do not

predetermine long-range outcomes. Criminal involvement and other indicators of

social adjustment are predictive of short-term outcomes, but long-term

therapeutic change is not limited by these or other factors studied in the DARP.

However, some long-term addiction careers are related to stabilized lifestyle

patterns involving family relations, criminality, or employment (Joe et al. 1985a)

which appear to enable and help sustain addiction. On the other hand, virtually

all recovering addicts in this sample reported experiencing a personal

psychological crisis as part of the motivation and decision-making process to

quit.

Successful intervention may therefore begin with a crisis which has significant

personal implications for an addict, and the most appropriate role for treatment

or other intervention agents is to understand and use the crisis to guide and

affirm positive change. There also appears to be a tendency for one’s motives in

starting and stopping addiction to be similar over time. For instance, social

pressures and friends are particularly influential for some addicts. This finding

may have therapeutic utility in identifying the most effective approaches for

intervention by determining motivational forces in starting and maintaining daily

use. However, more work is needed which focuses on the systematic assessment

of these motivational factors and the “readiness to change” by addicts.

REFERENCES

Joe, G.W.; Lloyd, M.R.; Simpson, D.D.; and Singh, B.K. Recidivism among

opioid addicts after drug treatment: An analysis by race and tenure in

treatment. Am J Drug Alcohol Abuse 9:371-382, 1982-83.

101
Joe, G.W.; Chastain, R.L.; and Simpson, D.D. Reasons for Initiatina. Continuing,

and Quitting Opioid Addiction. College Station, TX: Texas A&M

University, Behavioral Research Program, 1984.

Joe, G.W.; Chastain, R.L.; Marsh, K.L.; and Simpson, D.D. Opioid Recidivism

Factors: 12-Year Followup of 1969-1972 Admissions to DARP Drug Abuse

Treatments. College Station, TX: Texas A&M University, Behavioral

Research Program, 1985a.

Joe, G.W.; Chastain, R.L.; and Simpson, D.D. Major Domains of Influence

Associated with Addiction Career Length: 12-Year Followup of 1969-1972

Admission to DARP Drug Abuse Treatments. College Station, TX: Texas

A&M University, Behavioral Research Program, 1985b.

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Year Followup of 1969-1972 Admissions to DARP Drug Abuse Treatments.

College Station, TX: Texas A&M University, Behavioral Research Program,

1984.

Lehman, W.E.K.; Joe, G.W.; and Simpson, D.D. Development of Drug Integrative

Model for predicting- Long-Term Addiction Careers: 12-Year Followup of

1969-1972 Admissions to DARP Drug Abuse Treatments. College Satistics,

TX: Texas A&M University, Behavioral Research Program, 1985.

Lettieri, D.J.; Sayers, M.; and Pearson, H.W., eds. Theories on Drug Abuse;

Selected Contemporary Perspectives. National Institute on Drug Abuse

Research Monograph 30. DHEW Pub. No. (ADM) 80-967. Washington, D.C.:

Supt. of Docs., U.S. Govt. Print. Off., 1980. 488 pp.

Marsh, K.L., and Simpson, D.D. Sex Differences in Opioid Addiction Careers.

College Station, TX: Texas A&M University, Behavioral Research Program,

1985.

Marsh, K.L.; Joe, G.W.; Lehman, W.E.K.; and Simpson, D.D. Treatment History

of Opioid Addicts: 12-Year FOllOWUp of 1969-1972 Admissions to DARP

Drug Abuse Treatments. College Station, TX: Texas A&M University,

Behavioral Research Program, 1985.

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New York: John Wiley and Sons, 1976.

Sells, S.B., ed. The Effectiveness of Drug Abuse Treatment. Vols. I and II.

Cambridge, Mass: Ballinger, 1974.

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Vols. III, IV, and V. Cambridge, Mass: Ballinger, 1976.

Sells, S.B., and Simpson, D.D. The case for drug abuse treatment effectiveness,

based on the DARP research program. Br J Addict 75: 117- 131, 1980.

Simpson, D.D. Research Design and Methods; 12-Year Followup of 1969-1972

Admissions to DARP Drug Abuse Treatments. College Station, TX Texas

A&M University, Behavioral Program, 1984a.

Simpson, D.D. Reliability and Validitv of Data 12-Year Followup of 1969-1972

Admissions to DARP Drug Abuse Treatments

A&M University, Behavioral Research Program, 1984b.

Simpson, D.D. National treatment system evaluation based on the Drug Abuse

Reporting Program (DARP) followup research. In: Tims, Frank M., ed.

Drug Abuse Treatment Evaluation; Strategies. Progress and Prospects.

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(ADM) 84-1329. Washington, DC.: Supt. of Docs., U.S. Govt. Print. Off.,

1984c. pp. 29-41.

Simpson, D.D., and Joe, G.W. Sample Design and Data Collection; National

Followup Study of Admissions to Drug Abuse Treatment in the DARP

During 1969-1972. College Station, TX: Texas A&M University, Behavioral

Research Program, 1977.

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Simpson, D.D., and Sells, S.B. Effectiveness of treatment for drug abuse: An

overview of the DARP research program. Adv Alcohol Subst Abuse 2(1):7-

29, 1982.

Simpson, D.D.; Joe, G.W.; and Lehman, W.E.K. Addiction Careers; Summary of

Studies Based on the DARP 12-Year Followup. National Institute on Drug

Abuse Treatment Research Report. DHHS Pub. No. (ADM) 86-1420.

Washington, D.C.: Supt. of Docs., U.S. Govt. Print. Off., 1986a.

Simpson, D.D.; Joe, G.W.; Lehman, W.E.K.; and Sells, S.B. Addiction careers:

Etiology, treatment, and l2-year followup outcomes. J Drug Issues

16(1):107-121, 1986b.

ACKNOWLEDGMENTS

This paper is part of a series of interrelated studies on addict careers and 12-year

followup outcomes based on the Drug Abuse Reporting Program (DARP). It was

supported by the National Institute on Drug Abuse grant R01 DA-03419 as part

of a longitudinal drug abuse research project which began in 1968. The

interpretations and conclusions, however, do not necessarily represent the position

of NIDA or the Department of Health and Human Services.

The authors also acknowledge the contributions of many individuals over several

years. Drs. S.B. Sells, George W. Joe, and Wayne E.K. Lehman serve as senior

members of the research team, and the data collection for the followup

interviews was conducted by the National Opinion Research Center.

AUTHORS

D. Dwayne Simpson, Ph.D

Kerry L. Marsh, M.S.

Behavioral Research Program

Department of Psychology

Texas A&M University

College Station, Texas 77843

103
The Process of Smoking Relapse

Thomas H. Brandon, Stephen T. Tiffany, and Timothy B.

Baker

Smoking cessation treatments now regularly produce cigarette abstinence in 90 to

100 percent of clients (e.g., Erickson et al. 1983; Hall et al. 1984; Tiffany et al.

1985). Despite nearly universal cessation, the most successful smoking

interventions tend to produce year-long abstinence in only about half of all

treated subjects (Hall et al. 1984; Lando 1977; Tiffany 1985). Such statistics

underscore the frequent urgings that smoking researchers shift their focus from

cessation treatments to treatments aimed at extending, rather than producing,

abstinence (e.g., Marlatt 1982). An initial step in the effort to extend abstinence

(prevent relapse) is the analysis and characterization of relapse as a naturally

occurring process. Such information could be beneficial to efforts to design

effective abstinence extension treatments. For instance, information on common

relapse situations might allow therapists to target their maintenance procedures at

a circumscribed set of situations. In addition, subjects may spontaneously use

strategies to deal with relapse and relapse crises (where the smoker is tempted to

smoke but does not necessarily do so) that may suggest treatments of general

benefit.

While relatively few studies have been conducted that are targeted at

characterizing the smoking relapse process, the few studies extant yield general

patterns of findings that are reassuringly consistent. Available data suggest that a

great deal of variance in relapse incidence can be associated with a limited set of

affective, behavioral, and contextual variables. For instance, smoking relapse

and relapse crises tend to occur when individuals are: experiencing a negative

affect such as anxiety. depression, anger (e.g., Cummings et al. 1980; Shiffman

1982) in the presence of other smokers smoking (Shiffman 1982); experiencing

interpersonal stress (Marlatt and Gordon 1980; Shiffman 1982); or consuming

food or beverage--especially alcohol (e.g., Shiffman 1982).

In addition to data on smoking relapse, there now exists a well-articulated theory

of the relapse process (Marlatt and George 1984; Marlatt and Gordon 1984).

Marlatt’s theory constitutes an interesting and important departure from other

approaches to the analysis of relapse. Instead of focusing on pre-existing

personal characteristics that predict relapse (e.g., level of physical dependence,

personality factors), Marlatt has focused on events surrounding initial uses of a

drug during the postcessation period. According to Marlatt’s theory, a person’s

cognitive/affective reaction to initial postcessation drug use is a potent

determinant of subsequent drug use.

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One possible response to postcessation drug use is what Marlatt has labeled the

“abstinence violation effect” (AVE), a cognitive/affective reaction comprising two

principal components: an attribution made with respect to the causes of drug use

(the “lapse”) and an affective reaction to the lapse. The attribution process is that

the individual attributes the cause of the lapse to internal, stable and global selffeatures that are assumed, by the individual, to be uncontrollable, e.g., “lack of

willpower,” or addictive personality (Abramson et al. 1978; Weiner 1974). This

attributional process elicits an affective reaction characterized by conflict and

guilt. In theory, the stronger the AVE (the closer attributions are to the

prototype and the greater the negative affective reaction), the more likely a

“lapse” is to lead to relapse (regular drug use). The magnitude of the AVE is

posited to be a positive function of: the individual’s commitment to remaining

abstinent, the amount of effort previously expended to remain abstinent, and the

duration of the abstinence period.

Marlatt recognizes that relapse is affected by factors other than the AVE. For

example, he states that coping response execution will reduce the risk of relapse

(Shiffman 1982). In Marlatt’s model, coping likelihood appears to be a function

of both a subject’s confidence in his ability to cope with the relapse crisis

(Shiffman 1982) and the magnitude of any AVE effect. In addition, he believes

that relapse likelihood is also influenced by an individual’s expectations regarding

drug use, and by the initial effect of the drug once it is ingested in the

postcessation period.

Data are available that provide support for Marlatt’s model (although cf.

Shiffman 1984a). For example, Marlatt’s research has recently shown that,

among smokers who lapse, those who report responding with global, internal, and

stable attributions are more likely to relapse completely than other subjects

(Goldstein et al. 1984). In this same research there was also evidence that those

subjects who experienced a complete relapse reacted to their initial drug contact

with greater guilt feelings than did other subjects. This provides some support

for the notion that problematic lapses are associated with an affective reaction as

hypothesized by Marlatt. Goldstein et al. presented no data linking the

attributional style characteristic of the AVE with the magnitude of affective

reaction.

Most data gathered on relapse phenomena are vulnerable to diverse challenges

and conflictual interpretations. One reason for this is that relapse data typically

involve retrospective self-report, sometimes of target events distant in time from

data collection. This renders these data prey to biases such as memory errors and

self-presentation distortions. Due to the retrospective nature of much of the data

reporting, one bias may be particularly problematic; viz., reports of reactions to

relapse crises or initial drug use may be colored by the subject’s awareness of his

or her subsequent drug use. For example, Goldstein et al. found that lapsers and

relapsers were discriminated on the basis of guilt reactions to initial drug use.

One could interpret this to mean either that subjects experiencing the greatest

guilt went on to relapse, or that subjects who went on to relapse merely reported

experiencing the greatest guilt; i.e., knowledge that they had relapsed completely

distorted subjects’ recall of their affective reaction to initial drug use.

Another problem with research on relapse is that most studies involve selfselection; i.e., the subject population is composed of individuals who voluntarily

come forward to provide data.

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In the present research we attempted to avoid some of the problems of previous

relapse studies by investigating relapse in an identified population of individuals

who had gone through a formal cessation program. This permitted us to survey

an entire population, thus eliminating one type of self-selection bias. Subjects in

our research were self-selected in the sense that they all volunteered for a formal

cessation program. Thus, our subjects may not be representative of smokers as a

whole.

We attempted to make frequent contact with subjects in order to gather

information on initial cigarette use prior to the potentially distorting effects of a

successful or unsuccessful resolution of the relapse crisis. Of course, our

procedure did not eliminate potential bias; it merely made us susceptible to a

different set of biases. Restricting the sample to smokers treated by a single

program constrains sample size. Also, data may reflect the effects of the

particular treatment used, and subjects’ reports to followup interviewers may

have been influenced by the subjects’ attitudes or feelings about the treatment

program.

With the above caveats in mind, this research was intended to characterize the

process of relapse with respect to temporal features and cognitive, affective, and

physical correlates. Specific questions addressed in this research were: (1) If

smoking occurs, what is the latency to sampling a second cigarette, or to

returning to regular smoking? That is, what is the time frame in which the overt

manifestations of relapse occur? (2) What is the likelihood that a subject will

relapse completely if he or she smokes a cigarette? (3) Once a subject relapses

completely, what is the likelihood that he or she will achieve a subsequent period

of abstinence? (4) What are the cognitive, affective, and physical precursors, and

consequences, of an initial post-cessation cigarette? (5) What are the contextual

features and activities associated with initial cigarette use? (6) What is the

incidence of coping response use after smoking an initial cigarette? (7) What was

the frequency and severity of urges prior to the initial lapse? and (8) Is there any

relationship between a smoker’s precessation characteristics and the timecourse of

the relapse process? In addition to characterizing the context of subjects* lapses

to cigarette use, we also explored whether any of our dependent measures

predicted latency to sample a second cigarette or return to regular smoking.

METHODS

Subjects

The subject pool consisted of 82 persons (47 women and 35 men) recruited from

the community to participate in a 2-week smoking cessation program (see

Tiffany 1985). All subjects were between the ages of 18 and 40, and had

smoked at least one pack of cigarettes per day for at least I year. Subjects’ mean

age was 31.1, mean years smoking was 12.9, and mean number of cigarettes per

day pretreatment was 24.4.

Of these 82 subjects, 72 reached complete abstinence by the second week of the

cessation treatment. During the 2-year posttreatment followup period, 54 of the

subjects reported smoking. Data from their first relapse episodes are reported

here.

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Procedure

Cessation Treatment. All subjects met in groups of two to six smokers for 6

evenings over a 2-week period. Each meeting consisted of approximately 60

minutes of behavioral counseling and 30 to 60 minutes of aversive smoking. The

exact nature of the counseling and the aversive smoking varied across four

treatment conditions.

Followup. Following treatment, all subjects were contacted by phone by a

research assistant blind to the particulars of the study. An attempt was made to

interview subjects at 2-week intervals through 3 months posttreatment, and then

monthly, through 12 months. Subjects also were contacted at 18 and 24 months

posttreatment. Collaterals, who could provide information about the subjects’

smoking, were contacted every 3 months. Structured interviews were used to

gather data about subjects’ smoking status and problematic situations that they

encountered and expected to encounter. If they had smoked at all, extensive

information was gathered concerning the relapse episode. Information was also

gathered concerning the frequency, severity, and nature of urges to smoke. A

relapse interview was completed each time a subject had smoked, after having

gone at least 2 weeks without smoking. This report, however, focusses on the

first relapse episode only. The interviewers recorded the subjects’ free responses

to the open-ended questions of the structured interview.

Content Analysis. After 2 years of followup on all subjects, two research

assistants were trained to perform a content analysis of subjects’ responses to the

relapse interviews. Response categories were derived by the authors after

reviewing a sample of the interviews. Each research assistant scored

approximately 70 interviews. Reliability data were gathered by having both

research assistants score 39 of the interviews, and calculating Kappa coefficients

for 7 of the interview questions that required the greatest degree of judgment by

the scorers. Kappas ranged from .587 for subjects’ thoughts following smoking,

to .859 for food or beverages consumed prior to relapsing, with a mean of .782.

RESULTS AND DISCUSSION

For the 54 subjects who smoked, the mean number of days between treatment

termination and the first relapse episode was 58.44. A second cigarette was

smoked by 94.4 percent of these subjects, an average of 13.17 (S.D. = 55.6 days)

days after the first cigarette. Approximately half of all subjects (n = 26) had a

second cigarette on the same day as their first, and many of these (n = 14) within

an hour of their first cigarette. We operationally defined return to daily smoking

as three consecutive days of smoking. During the 2-year followup period, 90.7

percent of subjects who smoked a single cigarette eventually returned to daily

smoking. The mean number of days between the first cigarette and daily

smoking was 41.83.

Of the 49 subjects who returned to daily smoking after their initial posttreatment

abstinence, 30.6 percent reported a subsequent, second, distinct period of

abstinence during the 2-year followup period. (Only one subject reported a third

abstinence period.) There was much variability in terms of the temporal

characteristics of the second abstinence period. The beginning of this period

ranged from 5 to 288 days after the return to daily smoking, with a mean of

87.53 days and a median of 39 days. The length of the abstinence period ranged

from 7 to 652 days (including 4 subjects who remained abstinent through the end

of the followup period), with a mean of 178.53 days and a median of 66 days.

107
At 2 years posttreatment, only 16.6 percent of subjects who had smoked at least

one cigarette were abstinent. Of those who eventually returned to daily smoking,

8.2 percent were abstinent, while the 5 subjects who smoked but did not return

to daily smoking were all abstinent. The mean 2-year posttreatment smoking

rate for all 54 subjects was 19.31 cigarettes per day.

The number of days to first relapse was not correlated with days between the

first relapse and the onset of daily smoking, r(47) = .02. When the five subjects

who never returned to daily smoking were included in the calculations, a modest

correlation was found, r(52) = .35, p <. 05.

Characteristics of the Relapse Episodes

Table 1 shows that of the 89 percent of the relapsers who reported the location

of their first relapse, a majority of their relapses occurred either at home or at a

social event such as a party, or in a bar or restaurant. Other people were present

during 56.6 percent of the relapses. In 58.5 percent of all cases, subjects

reported that they had noticed others smoking prior to their relapse.

TABLE 1

Location of Relapse

Location (89% Response) % of Responders

Home 26.4

Work 11.3

Another’s Home 11.3

Bar/Party/Restaurant/Entertainment 26.4

In Transit (car, bus, plane, walking) 18.9

Other 5.7

Table 2 displays the self-report of consumption of subjects immediately

preceding relapse. Alcohol was associated with nearly one-half of all relapse

episodes. This figure is considerably higher than that reported by Shiffman

(1982). It is possible that this was caused by either fortuitous sample

characteristics or the fact that smokers who consumed alcohol were less likely to

call Shiffman’s hotline.

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TABLE 2

Consumption Preceding Relapse

Consumption (98.1% Response) % of Responders

None 30.2

Food 11.3

Alcohol 45.3

Caffeinated Coffee/Tea 24.5

Caffeinated Soft Drink 1.9

Recreational Drug 5.6

NOTE: Multiple coding results in totals over 100%.

In nearly all cases, subjects acquired their relapse cigarette through deliberate

action. Table 3 demonstrates that only 1.9 percent of the subjects were offered

the first cigarette smoked. Social pressure has been reported to be an important

determinant of relapse in previous studies (e.g., Marlatt 1982). If the data from

our research are representative, this suggests that there is little reason to train

subjects in cigarette-refusal skills as has been done with other substance abuse

populations. On the average, subjects smoked approximately two-thirds of their

first cigarette. Smokers rarely smoked all of the first cigarette they sampled.

TABLE 3

Origin of Cigarette

Origin (96.3% Response) % of Responders

Bought It 26.9

Asked For It 54.8

Found It 9.6

Was Offered It 1.9

Stole It 5.8

Relapses were distributed throughout the day (Table 4) with most occurring in

the afternoon and evening. This pattern of relapse mimics the diurnal pattern of

urge/craving self-report volunteered by individuals undergoing smoking

withdrawal (e.g., Gilbert and Pope 1982; Glassman et al. 1984).

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TABLE 4

Time of Relapse

Time (100% Response) % of Responders

Morning (02:00 - 10:59) 7.4

Noon (11:00 - 12:59) 11.1

Afternoon (13:00 - 16:59) 27.8

Evening (17:00 - 19:59) 33.3

Night (20:00 - 01:59) 20.4

Subjects were asked to recall their mood and physical feelings prior to smoking.

Table 5 displays their responses. In keeping with previous studies (Marlatt 1982;

Shiffman 1982). most subjects reported that negative affect preceded smoking.

Anxiety or tension was reported by 35.3 percent of subjects who answered, while

depression/hopelessness, anger/irritation, or boredom/fatigue were reported by

most of the remaining subjects. Less than one in five subjects reported any

positive affect. Only 77.8 percent of subjects could recall their physical feelings

prior to relapse. Of these, as with affect, negative states predominated. In

addition, 9.5 percent volunteered that they felt under the influence of alcohol or

other drugs.

TABLE 5

Affect and Physical Feelings Preceding Relapse

A. Affect (94.4% Response) % of Responders

Negative Affect

Depression/Hopelessness

Anxiety/Tension

Anger/Irritation

Boredom/Fatigue

Happy/Celebratory/Confident

Relaxed

Other (e.g., neutral, nostalgic)

56.9

17.6

35.3

15.7

11.8

17.6

2.0

11.8

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TABLE 5 (Con't)

B. Physical Feelings (77.8% Response) % of Responders

Negative/Ill Feelings 31.0

Fatigue 26.2

Headache 2.4

Other Negative Feelings 4.8

Aroused/Agitated 40.5

Under the Influence 9.5

Relaxed 4.9

Neutral 16.7

Other 2.4

NOTE: Multiple coding results in totals over 100% and sums that exceed

subtotals.

Responses to Relapse

One-third of all subjects reported using coping responses after relapsing to lessen

their chances of further smoking. Overall, subjects used an average of 0.15

cognitive coping responses, and 0.28 behavioral coping responses. The

predominant behavioral coping response was to throw out all cigarettes to which

the subject had access. Common cognitive coping responses were to think of

reasons not to smoke or for the subject to remind himself or herself of how

much progress each had made.

When asked about the taste of their first cigarette, 45.3 percent described it in

negative terms, 22.6 percent described it as positive, and 32.1 percent said it

tasted neutral.

Table 6 lists the cognitive, affective, and physical responses to relapse that were

reported by subjects. Over one-third of the subjects did not report or recall any

cognitions, and nearly one-half did not report any affective response. The

majority of subjects responding reported self-blaming or self-deprecatory

cognitions (61.8 percent). Only 2.9 percent said that they admitted defeat or

gave up trying to abstain after smoking the first cigarette. Positive thoughts,

such as relief that the struggle to abstain had finally ended, were reported by

11.8 percent.

Depression was the most common affective response to smoking reported by

subjects (42.9 percent). Only 7.1 percent of subjects described their mood as

happy, celebratory, or confident, and only 10.7 percent said they felt relaxed

after smoking.

Most of the physical responses to smoking the first cigarette (table 6) appeared to

be agonist effects of nicotine (reported by 73.1 percent of the subjects). The

most common of these was a feeling of dizzyness or lightheadedness which was

reported by about 58 percent of our sample. This figure is congruent with data

collected by Gilbert and Pope, who found that slightly over half of the subjects

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in their laboratory study reported these symptoms upon having an initial

postwithdrawal cigarette. The fact that an initial cigarette is likely not to taste

good, and is likely to have unpleasant effects, may be useful information to

convey in counseling programs with smokers. Other negative physical feelings

were reported by 19.2 percent. Only 3.8 percent said that they felt physically

relaxed after smoking.

TABLE 6

Cognitive, Affective, and Physical Response to Relapse

A. Cognitions (63% Response) % of Responders

Self-Blame/Self-Deprecation 61.8

Vowed “Never Again” 5.9

Admitted Defeat/Gave Up 2.9

Neutral/Indifference 8.8

Relief/Positive Thoughts 11.8

Other Cognitions 17.6

B. Affect (51.9% Response) % of Responders

Depression/Hopelessness 42.9

Anxious/Tense 10.7

Anger/Irritation 10.7

Aroused/Excited 7.1

Boredom/Agitated 3.6

Relaxed 10.7

Happy/Celebratory/Confident 7.1

Other 14.3

C. Physical Feelings

(96.3% Response)

% of Responders

Nicotine Agonist 73.1

Dizzy/Light Headed 57.7

Nausea 17.3

“High” 13.5

Tachycardia 7.7

Shaky 1.9

Headache 1.9

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TABLE 6 (Con't)

Other Negative Feelings

Oral Cavity Irritation

Fatigue

Other

Other Physical Feelings

Aroused/Agitated

Relaxed

Neutral

Other

19.2

7.7

1.9

9.6

25.0

3.8

3.8

7.7

9.6

NOTE: Multiple coding results in totals over 100% and sums that exceed

subtotals.

Prior Urges

Subjects were questioned about the frequency, severity, and effects of urges that

they experienced prior to relapsing. Table 7 shows that nearly 80 percent of the

subjects reported experiencing one or more urges to smoke per day prior to their

relapse. When asked to rate urge severity on a five-point Likert scale where five

represented extreme severity, the mean rating was 3.29, between moderate and

severe.

Table 8 lists the subjects' responses when asked if and how urges to smoke

affected their lives. Only 44 percent of responding subjects reported any effect,

and the majority of those stated that urges disrupted their thinking or

functioning.

TABLE 7

Frequency, Severity, and Description

of Urges Prior to Relapse

Urge Frequency (96.3% Response) % of Responders

Almost Constant 9.6

Hourly 5.8

Daily 63.5

More Than 2 Per Day 38.5

1-2 Per Day 25.0

Every Other Day 7.7

Every Several Days 3.8

Less Often 9.6

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TABLE 8

Effect of Urges on Life

Effect of Urges (92.6% Response) % of Responders

Urges Didn’t Affect Life 56.0

Urges Affected Life 44.0

Annoyance/Irritation 2.1

Negative Mood 16.8

Disruption of Thinking or Functioning 31.4

NOTE: Multiple coding results in subtotal over 44.0%.

Regression Analyses

To reveal associations between characteristics of relapse and outcome measures,

exploratory regression analyses were performed. The categorical responses of

subjects on the various items were dummy coded and entered as predictor

variables in separate regression analyses. Response categories were entered in the

regression only if they were endorsed by at least 10 percent of the responding

subjects, and if they were among the four most frequently endorsed categories

for a given item. Dependent variables were length of time between treatment end

and first relapse, length of time to second cigarette, and length of time to

resumption of daily smoking. For the latter two analyses, length of time until

first cigarette was forced into the regression first as a covariate.

No item significantly predicted days until second cigarette with days until first

cigarette partialled out. Only one variable was significantly associated with

number of days between treatment end and smoking a first cigarette. The longer

a subject maintained abstinence before a lapse, the more likely it was that he or

she reported experiencing negative physical feelings (e.g., fatigue, headache)

before relapsing (pr = .34, F( 1,38) = 5.08, p <.05). Only one variable was

associated with the number of days between treatment end and return to daily

smoking; viz., subjects who reported that urges affected their life tended to

return to daily smoking more rapidly than other subjects; r = -.31, F(l,41) =

4.32.

Three variables were associated with the length of the interval between smoking

a first cigarette and a return to regular smoking. Negative physical feelings

preceding first relapse were associated with a shorter time period until the

resumption of daily smoking (pr = -.35, F(1,32) = 4.41, p<.05) as was having the

first cigarette in the presence of other smokers (pr = -.37, F(l,43) = 6.95, p

<.05). Finally, the origin of the subjects’ first cigarette significantly predicted

time to daily smoking (sR2 = .06, F(2,41) = 3.38, p <05). Subjects who bought

their cigarettes tended to return to daily smoking sooner (pr = -.30, F(l.41) =

4.15, p <.05).

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The relationships between a number of pretreatment variables and outcome were

also examined. The pretreatment smoking rate was found to be negatively

correlated with days from treatment end to daily smoking; r = -.42, F(1,44) =

9.38, p <.01. This relationship persisted when days to first cigarette were

partialled out (pr = -.46, F(1,43) = 11.62, p <.01), indicating that a higher

pretreatment smoking rate was associated with a quicker return to daily smoking

after an initial lapse.

Pretreatment confidence was measured on a five-point scale. Subjects were

asked to estimate the likelihood that they would be abstinent 1 year following

treatment. This measure was positively correlated only with days until first

relapse; r = .35, F(1,51) = 7.02, p <.05. This same measure, taken posttreatment,

was similarly predictive of days to relapse; r = .36, F(1,51) = 7.52, p <.01.

Other pretreatment smoking characteristics examined--age, sex, years smoking,

number of previous quit attempts, and smoking satisfaction--were not related to

any of the outcome measures.

CONCLUSIONS AND IMPLICATIONS

One reason for doing this research was to discover information that might be

helpful in developing relapse prevention or intervention treatments; i.e.,

treatments that are designed to reduce the likelihood of further smoking should a

“lapse” occur (see Marlatt 1982). Some data in this study may be helpful in that

regard. First, in the majority of cases, relapse to regular smoking does not occur

precipitously. In fact, over half of all subjects waited more than 24 hours before

having a second cigarette. This suggests that smokers do not rapidly lose control

once they sample a cigarette, and it also suggests that there is a substantial

temporal window during which to intervene if a lapse occurs. On the other

hand, the nearly universal return to regular smoking (91 percent) once a cigarette

was tasted suggests that there are powerful forces operative that a relapse

intervention program must overcome. It is encouraging that nearly one-third of

these relapsers achieved a subsequent period of abstinence. However, their longterm abstinence rate of only 8.2 percent--compared to the 100 percent abstinence

rate for relapsers who did not return to regular smoking--lends support to

Marlatt’s (1982) recommendation that focused intervention occurs after a smoking

lapse but before full relapse. Moreover, the negligible correlation between days

to a first cigarette and days to full relapse suggests that different factors may

influence the maintenance of absolute abstinence versus the prevention of full

relapse following initial smoking. For example, maintenance of abstinence might

be a function of factors such as confidence/effectance estimates, coping skills, or

attributional styles (Hall et al., 1984; Marlatt 1982; Shiffman 1984a). However,

once a drug is actually sampled, readdiction may largely reflect the influence of

pharmacological motivational systems. Consistent with this is the fact that the

best predictor of the latency between a first cigarette and regular smoking was

the pretreatment smoking level.

While there are data indicating that coping response execution in the face of an

urge to smoke reduces the likelihood of smoking in the relapse crisis situation

(e.g., Shiffman 1982), we were concerned with whether coping responses, made

after a lapse had occurred, would reduce the likelihood or rate of subsequent

relapse on a long-term basis. Our results show that only a small percentage of

our subjects used coping responses after a lapse, and that coping response

execution was not associated with an increased relapsed latency. It may be that

coping responses are more effective if they are executed prior to a lapse. Also,

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our subjects used fairly primitive coping responses. It may be that more complex

or combinatorial coping responses would be more effective (Shiffman 1984b).

There was some evidence (p <.10) in our results that putting out a cigarette

quickly (having smoked little of it) was associated with an increased interval

from a first cigarette until a return to regular smoking. If putting out a cigarette

were considered a coping response, it would constitute the only evidence that

coping response execution was associated with delayed relapse.

One disappointing aspect of this research is that we were unable to obtain data

that strongly supported Marlatt’s relapse model. For example, there was no

evidence that reacting to a lapse with depression or hopelessness resulted in a

worse prognosis than did a different affective reaction. There was a tendency

for subjects who were depressed before their relapse to return to regular smoking

more rapidly than other subjects (F(1,39) = 2.88). However, this finding is

difficult to interpret. Prelapse depression might be associated with faster relapse

for a variety of reasons: e.g., it might reflect an enduring withdrawal or

heightened life stress. Moreover, we found no evidence that particular cognitive

responses to relapse (e.g., self-deprecation) were related to relapse rate. Nor was

there any evidence that relapse progressed more quickly the longer an individual

had been abstinent.

One characteristic of a lapse that is related to the progression to full relapse, is

the presence of negative physical feelings prior to the lapse. This is related to a

faster relapse progression, and is associated with the relapse of individuals who

had been abstinent the longest. The explanation for this pattern is unknown, but

it may be that individuals who are tired or ill are simply less able to cope

effectively with urges.

One final observation merits comment. Shiffman (1982) questioned the extent to

which relapse can be attributed to temporally and situationally discrete incidents,

and a person’s response to such incidents, versus the tonic factors that render the

individual susceptible to relapse. The present research reveals two tonic factors

that appear to have been relatively important in determining the rate of relapse:

i.e., the presence of chronic urges, and the precessation level of smoking. These

factors, in fact, seemed relatively more important in determining relapse rate in

our sample than did factors specific to the relapse context e.g., affective,

physical, or cognitive reactions to smoking. Of course, this conclusion, as well as

others, must be considered tentative given the constraints of this study--the small

sample size, the open-ended interview format, the different reliabilities of

response categories, etc. We are now analyzing data yielded by a systematic

replication of this research.

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addictive behaviors. In: Stuart, R.B., ed. Adherence. Compliance and

Generalization in Behavioral Medicine. New York: Brunner/Mazel, 1982.

Marlatt, G.A., and George, W.H. Relapse prevention: Introduction and overview

of the model. Brit J Addict 79:261-273, 1984.

Marlatt, G.A., and Gordon, J.R. Determinants of relapse: Implications for the

maintenance of behavior change. In: Davidson, P., and Davidson, S., ed.

Behavioral Medicine; Chaning Health Lifestyles. New York:

Brunner/Mazel, 1980.

Marlatt, G.A., and Gordon, J.R. Relapse Prevention: Maintenance Strategies in

Addictive Behavior Change, New York: Guilford, 1984.

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Consult Clin Psychol 50:71-86, 1982.

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Applied Soc Psychol 14:296-309, 1984a.

Shiffman, S.M. Coping with temptations to smoke. J Consult Clin Psychol

52:261-267, 1984b.

Tiffany, S.T. Treatments for cigarette smoking: An evaluation of the

contributions of aversion and counseling procedures. Doctoral Dissertation

submitted to the University of Wisconsin-Madison, 1985.

Weiner, B. Achievement Motivation and Attribution Theory. New

Jersey: General Learning Press, 1974.

ACKNOWLEDGMENTS

Karen Obremski conducted followup interviews. This research was supported, in

part, by the National Heart Lung and Blood Disease Grant #ROI HL28519.

AUTHORS

Thomas H. Brandon, MS

Timothy B. Baker, Ph.D.

Department of Psychology

University of Wisconsin

Madison, Wisconsin 53706

Stephen T. Tiffany, Ph.D.

Department of Psychology

Purdue University,

West Lafayette, Indiana 49705

117
Commitment to Abstinence and

Relapse to Tobacco, Alcohol,

and Opiates

Sharon M. Hall and Barbara E. Havassy

Interest in cross-drug generalities has existed for several years, but there are few

data that address such generalities. This is so even though there is a growing

body of indirect evidence suggesting that significant commonalities exist. For

example, Carroll and Meisch (1984) have demonstrated that food deprivation

increases the reinforcing efficacy of diverse drugs in laboratory animals. Falk, et

al. (1983) describe environmental features that have similar effects across drugs.

Examples are schedules of reinforcement that maintain persistent drug selfadministration and drug use as an adjunctive behavior. Kandel and Maloff

(1983) note sociocultural similarities in factors influencing use of many drugs--

for example, peer group pressure in the initiation of use--and termination of use

as a function of changes in demographic status. Similar examples can be drawn

from sociological, epidemiological, and psychological perspectives (Levison et al.

1983).

There are two investigations of cross-drug similarities in relapse, both of which

have considerable heuristic value. In the first investigation, Hunt and colleagues

(1971) compared relapse rates for graduates of treatment programs for alcohol,

opiate, and tobacco abuse. The investigators suggested that relapse curves are

similar across opiates, alcohol, and tobacco, both in the shape of the curve and in

the poor abstinence rates seen at long-term followup. This work has been

criticized on several grounds. Sutton (1979) noted that these are typical survival

curves that describe many phenomena. The phenomena can be as diverse and

unrelated as the death rates of neonates over time in some countries or the time

to burn out for individual light bulbs in large batches of bulbs. However, to

those in the field who have not seen them before, these data are compelling.

They reflect the experience of clinicians in the rapidity of relapse, and the

inevitability of it, for users of all three drugs.

A second landmark investigation was that of Marlatt and Gordon (1980), who

interviewed 137 subjects about the situations in which they relapsed after

treatment for tobacco, alcohol, or opiate dependence. These investigators noted

consistency across all three drugs. About one-half the relapse determinants for

the three drug categories fell into one of two categories: negative emotional

states and social pressure. Negative emotional states were described as relapse

determinants for 38% of the alcoholics, 43% of the smokers, and 28% of the

heroin addicts. Social pressure was a precipitant for 18% of the alcoholics, 25%

of the smokers, and 34% of the heroin addicts. These data raise several critical

118
questions. The first is the extent to which the retrospective nature of the data

colored the perception of the event, Second, the extent to which these are

illusory correlations is not known. Particular events may have been labelled as

determinants of relapse because they were the most salient factors in the

situation. The causative factors may have been subtle and less easily verbalized.

An example of such a subtle factor is chronic mild withdrawal symptoms. The

last question is one of base rates. The categorical scheme used by Marlatt and

Gordon (1980) spans the range of human experience. The frequency of such

events in the lives of the subjects, independent of relapse, is not known. It is

possible that coding of events other than relapse to drugs would show similar

distributions of situations.

The goal of the present study was to determine factors related to relapse to three

abused drugs: tobacco, alcohol, and heroin. It differed from earlier studies by

its prospective nature, by the range of variables investigated, and by attempts to

control variables left uncontrolled in previous studies. It was based on a model

of relapse that emphasizes commitment, withdrawal symptoms (including negative

affect), and environmental support, as determinants of abstinence or relapse (Hall

1980).

This model, the emerging literature on relapse processes, and clinical lore suggest

factors which appear to be important in relapse to all three drugs.

Social Support

The first factor is social support, which can be defined as resources provided by

other persons (Cohen and Syme 1985). Social support is often conceptualized in

two ways. The first is “structural” support. The structural aspect of social

support refers to the existence and pattern of relationships with others, for

example, marital status, number of relationships, or number of contacts per time

period. The second aspect of social support is functional support. This is the

degree to which interpersonal relationships provide emotional, intellectual, or

material resources. When considering health outcomes, such as maintaining

abstinence, both structural and functional aspects of support may facilitate

abstinence or, conversely, encourage drug use (Cohen and Wills, in press).

Variables used to measure support differ depending on which aspect of support is

being measured. They also differ widely within investigations of specific drugs,

as well as across drugs. Most investigations of drugs assess the functional, rather

than structural, components of support. These have been shown to predict

outcome. Behaviors perceived as supportive by the quitter are consistent

predictors of abstinence in ex-smokers (e.g., Graham and Gibson 1971;

Mermelstein et al., in press). Positive family environment has been a consistent

predictor of outcome in alcoholics (Foster et al. 1972; Finney et al 1980; Moos et

al. 1979; Orford et al. 1976).

Evidence for the role of social support in relapse to heroin use is indirect.

Marlatt and Gordon (1980) found that social pressure, including direct pressure

to use the drug, and being in the presence of others using drugs, was the most

frequently reported determinant of relapse to heroin use.

Systems approaches to psychotherapy (e.g., Haley 1971; Bosormenyi-Nagy and

Sparks 1973) recognize that subtle forms of social support for drug use may come

from families. Therapies developed from these theories have been successfully

applied to reduction of drug use during treatment (Stanton et a1. 1978), but they

119
have not been specifically applied to relapse. Also, family factors are considered

of importance by drug treatment programs, in that provision of family services

has been seen to be essential (Coleman 1977; Reed 1985).

Drug users may receive satisfactory general social support, but it may not include

specific support for quitting drug use or maintaining abstinence. If network

members also have problems with the drug, the support offered may reinforce

continued use. Or, if network members are unaware of the user’s problem, the

support they provide may not be a resource to help them cope with abstinencerelated difficulties. The relationship of drug-specific social support to relapse

has not received significant attention. Mermelstein et al. (1983) attempted to

differentiate global social support from support specific to quitting smoking.

Subjects were asked how many of their friends and how many of their coworkers

were smokers. The subjects also completed a global social support questionnaire.

No clear results emerged when the proportions of smokers among friends and

coworkers were compared to smoking status during treatment, at end of

treatment, and posttreatment, although differences at end-of-treatment were

suggested. Cohen and colleagues (1985) report data that suggest support from

intimates for quitting smoking is a determinant of abstinence.

Negative Life Events

A second variable is the occurrence of negative life events, and other global

variables, that have been included under the construct of “stress.” Stress is

frequently operationalized as major life events or changes, both positive and

negative. Most research has looked at the effects of stress on global health

outcomes. When stress is correlated with health outcomes, negative life events

predict poor outcome. Positive events, or scores combining both, usually do not

(Mueller et al. 1977; Vinokur and Selzer 1975). Data specific to the addictions

has also been reported. Ogbru (1976), Finney et al. (1980), and Cronkite and

Moos (1980) all found that negative life changes predicted relapse for alcoholics.

Benfari and Eaker (1984) reported similar findings for smokers. Krueger (1981)

found events such as recent loss of a relationship or job, depression,

interpersonal conflict, or disappointments were associated with occurrence of

heroin use by methadone maintenance clients who had been heroin-free for at

least 6 months.

The ongoing “stresses” of daily living, repeated or chronic minor events known as

“Hassles,” appear to be another useful way to characterize stress. Again, most

interest has been in the relationship between general health outcome and Hassles.

It was suggested that the strain of these daily events cumulatively affects health.

Delongis et al. (1982) investigated the relationship of both Hassles and major life

events to health outcomes. Hassles scores were more strongly associated with

health than were life events. While Hassles predicted significant proportions of

variance when the effect of life events was removed, the reverse was not true.

When the effect of life events was controlled, Hassles and health remained

significantly related. Although no studies relating Hassles to relapse to drug use

have appeared in the literature, the study of such relationships may be fruitful.

Marlatt and Gordon (1980) also noted that 13%-18% of relapse situations for all

three drugs could be classified as including interpersonal conflict, a common

“stressful” event. In their study, negative emotions were among the most common

relapse precipitants. Whether this reflects characterological factors or the

occurrence of negative life events is not known. Negative affect is known to be

a consistent factor in smoking relapse (e.g., Hall et al. 1983; Pomerleau et al.

120
1977; Tunstall et al. 1985). Again, whether this affect reflects life events or is

characterological is not known.

Sex Differences

There is indication that women smokers and alcoholics relapse more rapidly than

men. The U.S. Public Health Service (1980) noted this trend in a comprehensive

review of the smoking literature that reported sex differences among treated

smokers. Similarly, poorer outcome has been reported for alcoholic women

(Davidson 1976), although others dispute the accuracy of this position (Vanicelli

1984). Those few studies that examined sex differences in heroin addicts have

not found differences in illicit drug use or treatment outcome variables (Cushman

1978; Savage and Simpson 1980).

An emerging literature suggests that the variables controlling drug use,

determinants of relapse, and optimal treatment may be different for women than

for men. Women smokers report they are more likely to smoke in response to

negative affect than men. The predominance of negative affect smoking among

women could be a factor in the higher relapse rates reported for them, since

negative affect smokers have been found to be more likely to relapse than

smokers who do not label negative affect as a primary determinant of smoking

(Pomerleau et al. 1977). The greater role of negative affect in use of alcohol and

heroin for women has also been noted (e.g., Beckman 1976; Braiker 1982; Reed

1985; Rhoads 1983; Westie et al. 1984). Others have suggested that the

treatments offered, rather than women’s characteristics, explain possible

differences in outcome. Several writers have suggested that chemical dependency

treatment services are not designed for alcoholic or addicted women and may fail

to recognize women’s key difficulties. If they do recognize these difficulties,

they perceive them as outside the scope of services they are willing or able to

provide (Reed and Beschner 1981; Carmen et al 1981; Reed 1985). The issue of

treatment suitability for women smokers has been little discussed. However,

self-quit rates for men smokers are better than for women, suggesting that

factors other than treatment structure may be involved in producing differences

observed (Pehacek et al. 1982).

Skills to Prevent Relapse

There are other intriguing factors that have been little studied. One is the

presence of skills to prevent relapse. Clinicians have long recognized that the

ability of patients to eloquently describe their responses to relapse situations is

often matched by a lack of coping behavior in actual relapse situations.

Interventions teaching such skills to alcoholics, smokers, and heroin addicts have

been evaluated. Most evaluations assessed the effects of training on behavioral

performance tests, rather than on relapse prevention (Eisler et al 1973; Foy et aI.

1974; Van Hasselt et al. 1978). However, some studies have looked directly at

relapse prevention as a function of skill training. Chaney and colleagues (1978)

found that providing skill training to alcoholics decreased the duration and

severity of relapse episodes at year follow- up. Hall and coworkers (1984) found

that smokers given relapse prevention skill training were less likely to relapse

than those participating in a discussion control condition. However, the stability

of this finding is not clear (Hall et al 1985). Negative results have been reported

by Cooney et al. (1982). These treatment studies cannot partial out the unique

contribution of skills, because they were part of multicomponent treatment

programs.

121
Commitment to Abstinence

A final variable is commitment to abstinence. Both clinical lore and common

sense about the determinants of success suggest that a commitment to abstinence

is central to maintenance of abstinence. Commitment to abstinence is one

dimension of the broader term, “motivation.” We conceptualized it as an

indicator of motivation to cease drug use and remain abstinent. Janis (1983)

suggests that commitment is central in facilitating adherence to difficult

decisions. The decision to remain abstinent may be especially difficult for the

chronic drug user.

Studies of smokers who quit smoking without treatment indicate this may be a

promising variable, but that it may interact with other variables (Best 1975,

1980). Several dimensions of commitment must be considered. Among the most

predictive have been desire for abstinence (Goldstein et al 1983; Rosen and

Shipley 1983) and perceived probability of success (Best 1975; Rosen and Shipley

1983; Goldstein et al. 1983). Level of commitment may be directly linked to

other variables, such as the perceived costs and benefits of change (Hall 1980)

and the client’s self-efficacy about maintaining abstinence (Condiotte and

Lichtenstein 1981).

Many of these models can be easily adapted to alcohol and opiate abuse.

However, data relevant to such adaptations are lacking.

Our Approach

Several consistencies emerge. Despite a need, and despite some theorizing, few

data on cross-drug generalities exists. There is evidence for the importance of

social support in preventing relapse. Negative life events may increase the

probability that relapse will occur. However, it is unclear whether they are

causative or whether they are implicated by virtue of selected recall of a relapse

situation. There is indication that women relapse at higher rates across drugs.

Knowledge about processes underlying sex differences in the relapse process is

poor. Coping skills and commitment to abstinence, two variables considered to

be central in preventing relapse, have been little studied.

Hypotheses

This paper reports the results of a preliminary study which tested two hypotheses

about commitment to abstinence:

(1) Regardless of drug, the greater the commitment to abstinence, the

longer the time to relapse; and

(2) Negative mood, withdrawal symptoms, and negative life events would

interact with level of commitment to abstinence over time to relapse. We

predicted that at high levels of commitment these variables would not affect

outcome. At lower levels, the higher the level of these negative subjective

events, the shorter the time to relapse.

Differences in time to relapse between drug treatment classes were not expected.

In this preliminary study, relapse was defined as 1 week of daily use of the

problem drug.

122
METHOD

Treatment Facilities

Subjects were drawn from three drug groups: opiate addicts completing 21-day

methadone-assisted detoxification or 28-day residential treatment, alcoholics

completing 28-day residential treatment, and smokers completing 28-day

cessation treatment.

The treatment facilities from which we recruited subjects were selected for four

reasons. The first was treatment goal. All the treatment programs chosen were

abstinence oriented. The similarity of goal allowed us to better assess the

common effects of central variables. The second was the nature of the treatment

episode, which lasted about 1 month, and had a well-defined ending date. This

similarity eliminated length of treatment as a confounding variable. Third, we

selected treatment modality groups in which there were enough clients to obtain

an adequate sample. The fourth was that the facilities treated subjects who were

representative enough of the populations within drug group so that the data

obtained would be meaningful, while allowing us to roughly equate drug

treatment classes on demographic characteristics.

Our research group offered a smoking treatment program at San Francisco

General Hospital, a large public hospital which serves a multiethnic, lower and

working class population. The program was offered at this location because both

a drug treatment and an alcohol program included in the study were at the

hospital, facilitating the acquisition of subjects with similar demographic

characteristics. Treatment included aversive smoking and group discussion and

support. Groups were led by one of two therapists. Although the treatment was

uniform across the groups, the therapists had different orientations, providing for

some variability in treatment delivery.

Alcoholics were recruited mostly from two residential programs. Both used

Alcoholics Anonymous extensively in treatment. Clients were primarily lowermiddle and working class and were from a variety of ethnic groups.

We recruited opiate addicts from four sources: three 21-day detoxification

clinics, and one 28-day residential facility. The outpatient clinics provided

methadone detoxification and supportive counseling. The inpatient program was

based on an adaptation of the abstinence-oriented Alcoholics Anonymous model.

Again, the programs treated lower-middle and working class clients of diverse

ethnic groups.

Subjects

Subjects were blacks and whites between 21 and 50 years of age, who had been

employed within the 6 months before the beginning of treatment and who gave

adequate data for followup contact. Subjects were of low to middle

socioeconomic status (SES) and were not upper-middle or upper SES, destitute,

or homeless. The primary source of income for all subjects was legal.

Here, we report data on the first 77 subjects to enter the study. Data have been

collected on 230 subjects, about equally distributed among the three drug groups.

Descriptive statistics for the first group of 77 are shown in table 1.

.

.

123
TABLE 1

Descriptive Statistics

TOBACCO ALCOHOL OPIATES

M 18 25 11

SEX

F 12 4 7

WHITE 27 22 14

ETHNICITY

BALCK 3 7 4

NEVER MARRIED 18 8 5

MARRIED 6 9 6

MARITAL

STATUS

SEPARATED 1 4 2

DIVORCED 5 8 5

EMPLOYED 26 13 5

EMPLOYMENT

STATUS

ON LEAVE 1 2 0

UNEMFLOYED 2 11 8

STUDENT, NOT IN

JOB MARKET,OTHER 1 3 5

AGE = 35.43 38.34 34.78

SD = 7.60 5.53 7.31

AGE AT = 14.23 14.69 19.l7

FIRST USE

SD = 4.35 2.87 5.76

AGE AT = 16.50 20.79 21.94

REGULAR USE

SD = 3.83 7.15 5.73

124
Method

Study Induction. Subjects were recruited at their treatment site when in the last

third of treatment. Only clients who had acceptable attendance and were

abstinent were recruited. Abstinence was verified by two biochemically

validated self-reports at least 72 hours apart. Clients agreeing to participate

underwent a screening procedure and completed an informed consent. A study

intake assessment, which was administered just before the client completed

treatment, included an interview assessing demographic characteristics, health

status, and treatment history; and instruments measuring drug and alcohol use,

mood, withdrawal symptoms, life events, and motivation about drug use.

Followup. Followup assessments were completed once a week for 12 weeks

(beginning with the first week following treatment end) or until the subject

relapsed. Subjects’ drug and alcohol use, moods, and withdrawal symptoms were

monitored during followup. Social support data were also collected at the

followup assessment. We recognized this procedure could confound perceived

social support with early progress. That is, support by others may vary as a

function of cues from the subject about probability of continued abstinence

during treatment or very soon afterwards. However, all alcohol and some opiate

clients were recruited from inpatient facilities. They could not estimate social

support from their environment until they returned to it.

Measures. The following instruments were used in the present study:

(1) A preceded intake interview, measuring demographic variables, addiction and

treatment history, treatment goals, and physical health.

(2) A scale measuring Commitment to Abstinence was adapted from that used by

Marlatt (unpublished). The scale asked subjects to rate a) desire to be abstinent,

b) perceived chances of success, and c) perceived difficulty of abstinence, on a

1-10 point scale. Subjects were also asked to endorse one of five abstinence

goals, which are shown as goals 2 through 6 in table 2.

TABLE 2

Abstinence Goals

1. No clear goal.

2. Controlled use.

3. Total abstinence for a time, then decide about use.

4. Use occasionally, but not a habit.

5. Give up once-and for all, but realize I may slip.

6. Give up once and for all, be totally abstinent, never use again.

125
(3) A scale measuring chronic withdrawal symptoms (Symptoms Questionnaire)

was adapted from existing scales measuring alcohol, tobacco, and opiate

withdrawal symptoms.

(4) The Mood Questionnaire (Ryman et al. 1974) was shortened and adapted for

our population.

(5) The “Hassles” scale (Kanner et al. 1981) was shortened for use with our

population.

For smokers, self-report of abstinence was verified by expired air carbon

monoxide readings of 9 ppm or less. Self-report of abstinence for alcoholics was

absence of alcohol in urine specimens. Report of abstinence by opiate addicts

was verified through absence of morphine in urine specimens. Urinary alcohol

and morphine were assayed by a commercial laboratory. The accuracy of the

morphine assay has been judged acceptable by the State of California as part of

its laboratory monitoring program for drug treatment programs. There was no

independent verification of the accuracy of the alcohol assays available to us.

Results

Overview. The small and incomplete sample suggests that a generous probability

level, for example, p < .10. would be appropriate. On the other hand, because of

the small sample size, conservative statistics, including hierarchical regression

analyses by sets, could not be used. Data analysis therefore required more tests

than ideal. As a compromise, we retained the p < .05 significance level.

Interpretation of the results should be considered tentative given the incomplete

sample size, and the less-than-optimal data analysis strategy required.

Commitment to Abstinence and Time to Relapse. Each of the four commitment

to abstinence ratings was entered as an independent variable in a series of

hierarchical regressions with drug group as the covariate. Time to relapse was

the dependent variable in each.

The first hypothesis was supported. Of the four dimensions of commitment to

abstinence, two of these, goal and perceived difficulty, were significant

predictors of time to relapse in this small sample.

A goal of total abstinence versus partial abstinence was a significant predictor of

time to relapse (F[1,69] = 4.16. p < .05, r

2

 = .0453), independent of treatment

class. As is shown in figure I, subjects who endorsed the most restrictive goal, “I

want to quit (drinking) once and for all, to be totally abstinent, and never (drink

another drink) again for the rest of my life,” had longer times to relapse than did

subjects committed to the other alternatives combined. The selection of “total

abstinence” as a goal also predicted relapse versus continued abstinence. At 12

weeks, 63% of those selecting this goal were abstinent. Less than 30% of those

choosing other goals were abstinent (Fisher’s Exact p < .008). The interaction

between treatment class and commitment to total abstinence was not significant.

126
FIGURE 1

Weeks to Relapse as a Function of Choosing a Goal of Total

Abstinence Versus Choosing Other Goals

The interaction between perceived difficulty of abstinence and treatment class

was significant (F[2,65] = p < .01, r

2

 = .12). For smokers, perceived difficulty

and time to relapse were negatively correlated (r = .515, p < .01). For alcoholics,

there was no correlation (r = .062). For opiate addicts, greater perceived

difficulty predicted longer time to relapse (r = .570, p < .01). Regression lines of

time to relapse as a function of perceived difficulty for each treatment class are

shown in figure 2.

Desire to quit and likelihood of success were not significantly related to weeks to

relapse.

127
FIGURE 2

Regression Lines for Drug Treatment Classes: Weeks to Relapse

as a Function of Perceived Difficulty of Abstinence

Sex Differences, Hassles, Withdrawal, Moods, and Abstinence. The hypothesized

interactions were not found. A series of hierarchical regressions were completed

with treatment condition, abstinence ratings, sex differences, Hassles scores, and

mood scores entered as independent variables. Interaction terms were entered last.

There were no significant interactions of abstinence scale values with sex of

subject, Hassles, withdrawal symptoms, or moods.

Drug Treatment Class, Time to Relapse, and Relationships among Independent

and Moderating Variables. Contrary to expectation, there were differences in

treatment class in time to relapse (F[2,74] = 5.91, p < .01, r

2

 = .13). For opiate

addicts, mean = 6.11 weeks, a = 4.14; for alcoholics mean = 8.66 weeks,

SD = 5.04. For cigarette smokers mean = 10.37 weeks, SD = 3.59. Only

differences between smokers and opiate addicts were significant (t[46] = 3.75,

p < .01).

To better understand factors that might mediate differences in time to relapse

across the three drug groups, we compared the groups on mean negative mood

128
states following treatment, Hassles scores, withdrawal symptoms following

treatment, and commitment to abstinence in a series of exploratory analyses.

Significant differences were found between the three drug groups on expectation

of successful abstinence (F[2,74] = 4.71, p < .01, R

2

 = .11), predicted difficulty

in maintaining abstinence (F[2,74) = 3.06, p < .05, R

2

 = .076), goal of total

abstinence versus other goals (F[2.74] = 3.43, p < .04, r

2

 = .084), and withdrawal

symptoms (F[2,74] = 6.30, p < .01, R

2

 = .145). Differences between total Hassles

score, negative mood states, and desire to maintain abstinence were not

significant.

Most significant, F-values reflected differences between smokers and the other

two drug groups in thoughts about abstinence. Smokers were most likely to

predict they would be successful in maintaining abstinence. The difference

between smokers and opiate addicts was significant (t[25 for unequal

variances] = 2.52, p < .01, figure 3a). The paired comparisons between smokers

and alcoholics, and alcoholics and opiate addicts, were not significant. Smokers

saw maintaining abstinence as more difficult than the other two drug groups.

The difference between smokers and alcoholics was significant (t[57] = 2.59,

p < .01, figure 3b), but the other two paired comparisons were not significant.

FIGURE 3a

Probability of Successful Abstinence as Predicted by the Three

Drug Treatment Classes

129
FIGURE 3b

Perceived Difficulty of Abstinence as a Function of Drug

Treatment Class

FIGURE 3c

Percent of Subjects Selecting Total Abstinence as a Goal for Each

Drug Treatment Class

130
Smokers were more likely to select total abstinence as a goal than the other two

treatment classes. The difference between smokers and opiate addicts was

significant (t[46] = 2.59, p < .01, figure 3c). The remaining two paired

comparisons were not significant.

Opiate addicts reported significantly higher levels of withdrawal symptoms

(mean = 43.66, SD = 21.91) than both smokers (mean = 28.67, SD = 16.61;

t[46] = 2.69, p < .01) and alcoholics (mean = 25.36, SD = 16.06; t[45] = 3.30,

p < .01). Because time to relapse differed, the length of time over which

symptoms were measured differed among the three groups. Therefore, an

analysis of covariance was completed with time to relapse removed from the

equation. Differences in withdrawal symptoms remained significant.

DISCUSSION

The results confirm the first hypothesis. Independent of drug group, if subjects

endorsed a statement indicating that they intended to be abstinent and never use

the problem drug again, they were slower to return to daily drug use. They also

were more likely to be abstinent at the end of 3 months. On the one hand, this

is not surprising, since individuals’ prediction of their own behavior is often

good (Condiotte and Lichtenstein 1981). On the other hand, some might consider

an intention never to use a drug again to be an unrealistic one. Marlatt and

Gordon (1980) suggest such attitudes might facilitate relapse. Under their

concept of the “Abstinence Violation Effect” (AVE), if a single slip is considered

a failure, as it would be by those endorsing the most restrictive statement, it may

be the first step in the completion of a self-fulfilling prophecy. These

preliminary data do not support this model.

This result was not due to grouping the more moderate- abstinence goal with the

nonabstinence goals. In a secondary analysis, goals were divided into three

categories: (1) Those indicating either no goal or a nonabstinent goal (statements

1-4); (2) “Realistic” Abstinence (Statement 5); or (3) “Total” Abstinence

(Statement 6). Subjects endorsing Statement 5 relapsed the most rapidly, but the

differences between them and the subjects endorsing the first four categories

were small and not significant.

The pattern of these data suggest that smokers think differently about abstinence

than the other two drug groups. Smokers were more committed to complete

abstinence and more optimistic about their chances of abstinence. However, they

also saw abstinence as more difficult. The differences in time to relapse--i.e.,

the longer time to relapse for smokers--support their optimism. The source of

these differences is not clear.

It is possible that smokers’ combined optimism and realism reflect global attitudes

toward treatment. Smokers who enter treatment may have more faith in it than

do members of the other two drug treatment classes. It may be that a “smokers

subculture” is not one which devalues some forms of treatment, as may be the

case for some alcoholics and heroin addicts (Brown et al. 1972, 1975; Sutker et al.

1978). Also, the data show the smokers have tried to quit fewer times and

therefore have had fewer failure experiences. Failure may breed more failure as

confidence in one’s ability to quit is decreased by negative experiences.

The data indicate few differences between drug groups on subjective experience

during the post-treatment followup period. The classes do not differ

significantly on negative moods or on day-to-day life stresses (Hassles). Opiate

131
addicts do report more withdrawal symptoms than do members of the other two

groups.

The interactions we expected to find between negative subjective experience

during the posttreatment period and level of commitment to abstinence are not

yet detectable. A larger sample size may be needed to detect such differences, if

they are present.

These are preliminary data. As such, interpretations of them must be regarded

with considerable caution. They do seem to indicate that commitment to

abstinence, a little studied factor, may be a fruitful variable to address. While

other variables--such as stress, affect, and life events--are perhaps more

fashionable, their potential as predictors has not yet been realized in this study.

It is of theoretical interest to know that certain ways of thinking about

abstinence may increase the probability of maintaining it. This knowledge is of

little clinical utility unless it can be translated into behaviors that prevent relapse

in risky situations or those that prevent the client from ever entering such

situations. Such specific knowledge may ultimately lead to useful therapeutic

techniques. Similarly, factors leading to the development of this way of thinking

and the therapeutic and environmental events that control it should be explored.

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ACKNOWLEDGMENTS

Research reported was funded by National Institute on Drug Abuse Research

Grant Number R01-DA-03082 and ADAMHA Research Scientist Development

Award K01-DA-00065.

AUTHORS

Sharon M. Hall, Ph.D.

Center for Social and Behavioral Sciences

1350 7th Avenue (CSBS 204 Box 0844)

University of California, San Francisco

San Francisco, California 94143

Barbara E. Havassy, Ph.D.

University of California, San Francisco

Department of Psychiatry

San Francisco General Hospital

1001 Potrero Avenue (7M)

San Francisco, California 94 110

135
Explaining Relapse to Opiate

Addiction Following Successful

Completion of Treatment

William E. McAuliffe, Barry Feldman, Rob Friedman, Elaine

Launer, Elizabeth Magnuson, Carl Mahoney,

Susan Santangelo, William Ward, and Roger Weiss

INTRODUCTION

Relapse is a central aspect of the concept of opiate addiction (Lindesmith 1968;

Catalano and Hawkins 1985). The inability to stop opiate use is what most

people have in mind when they say that someone is “addicted” to opiates. During

their careers, most opiate addicts in fact seek primary drug-user treatment to

help them stop opiate use (McAuliffe 1975). Many achieve abstinence on their

own or by successfully completing some form of primary treatment, be it simple

detoxification, counseling, therapeutic community, or methadone maintenance.

Unfortunately, followup studies have found relapse rates to be around 50 percent

for methadone maintenance graduates (Brown et al. 1975; Cushman 1974;

Lowinson and Langrod 1973; Riordan et al. 1976; Stimmel and Rabin 1974),

about 66 percent for those who completed outpatient methadone detoxification

(Maddux et al. 1980), 10 percent for therapeutic community graduates (Smart

1976), and between 50 percent and 90 percent for dischargees from the Public

Health Service Hospital in Lexington, Kentucky (O’Donnell 1965; Stephens and

Cottrell 1972). Most opiate addicts relapse repeatedly over their disease course,

even after substantial periods of abstinence (McAuliffe 1975; Waldorf 1973).

Consequently, many theorists (e.g., Lindesmith 1968; Wikler 1965) now regard the

tendency to relapse as one of the defining characteristics of addiction.

Despite the conceptual importance of relapse and the great economic and human

cost of cycles of repeated treatment and re-addiction, relatively few researchers

have studied the causes of relapse as distinct from the causes of treatment

failure. Most field studies of relapse to date have focused on measuring the

frequency of relapse or its timing (e.g., O’Donnell 1965; Hunt and Bespalec

1974). A much smaller number of empirical studies have sought to discover the

predictors and causes of relapse (e.g., Alksne 1955; Ball and Snarr 1969; Brill et

al. 1972; Brown et al. 1971; Joe and Simpson 1983; Jorques 1983; Maddux and

Desmond 1981; McAuliffe 1982; Simpson et al. 1979; Stephens and Cottrell 1972;

Vaillant 1969; Waldorf 1973. 1979, 1983; Wikler and Pescor 1967; Willie 1983;

Winick 1962, 1964).

Most of these pioneering studies have been retrospective or cross-sectional in

design. Some researchers (e.g., Alksne et al. 1955; Brill et al. 1972; McAuliffe

1982; Waldorf 1973) simply asked long-term addicts why they had relapsed, and

then summarized the responses statistically or in a theory of relapse. Other

136
researchers (e.g.. Winick 1962) correlated demographic variables with patient

outcomes and then speculated about the meaning of the results, e.g., interpreting

the relationship between age and relapse as a matter of maturation or burnout.

Although valuable first steps for generating hypotheses, retrospective studies are

vulnerable to after-the-fact rationalization by the subjects themselves, as well as

biases in the sampling frame (Robins 1966), and demographic correlations with

relapse are open to varying interpretations.

The studies to date have produced promising hypotheses and causal models (e.g.,

Marlatt and Gordon 1979; Catalano and Hawkins 1985; Milkman et al.

1983/1984), but few have attempted to explore these models systematically.

Many of the statistical studies have examined the relationship of one measure at

a time with relapse (e.g., Winick 1964). Other statistical studies of relapse have

used multivariate methods but have often employed exploratory or predictionoriented model specification methods, such as step-wise regression, that select

variables solely on statistical rather than theoretical for testing theoretical models.

The recent study by Jose and Simpson (1983) represents an important early

attempt to investigate relapse using multivariate statistical models specified

theoretically, although the authors apparently had to rely on existing measures as

indicators rather than on measures specifically designed for this purpose.

The present study sought to build upon the previous studies. Prospective in

design, it measured concepts from several leading theories of relapse at the point

of the subjects’ satisfactory completion of treatment. and then re-interviewed the

subjects at 6 months and 12 months to determine the extent of relapse to opiate

use. Since the study is not yet completed, this report describes the study’s

implementation to date and presents preliminary findings regarding conditioning

models of relapse from the baseline (at discharge from treatment) and the 6-

month followup data obtained thus far.

METHODS

Recruitment Plan and Followup

The 184 subjects for this study included four types: 1) “imminent completers”

(67 percent) or 2) recent completers (14 percent) of treatment programs for

opiate addiction; 3) completers of after care programs (12 percent); and 4) longterm clients of open-ended drug counseling (7 percent). For the purpose of this

study, “completers” are persons discharged from treatment on recommendation of

treatment staff. Interviews were conducted within an average of 1 week before

or after discharge. Since outpatient drug-free counseling tends to be openended, the research design assumed that clients who had been doing well in

counseling for 6 months or more were equivalent to other treatment completers;

clients from open-ended aftercare programs were treated similarly. Addicts in

corrections facilities were eligible only if they were completing a prison-based

drug treatment program.

Recruitment began in the spring of 1981 and included a large number of

treatment programs in the Boston and surrounding areas (47 programs in all).

Staff contacted each program frequently to determine when an opiate-addicted

client would be completing treatment. In order to insure a wide variation in the

hypothesized causes of relapses, the recruiters tried to obtain approximately equal

numbers in the eight-cell design presented in table 1. The design assumes a

rough correspondence between levels of three broad factors that are thought to

be related to recovery: time since last period of physiological dependence,

137
psychological adjustment (motivation, attitude), and social adjustment (resources

and stability). Since the factors were measured only after a subject was

recruited, we assumed that the clients from particular modalities would

approximate the characteristics of particular cells. As table 1 shows, while some

cells were clearly harder to fill than others, we have obtained a sample of

subjects who have a wide range of treatment experience and therefore should

have ample variation in relapse experiences and their causes. All subjects

provided baseline data on hypothesized causes of relapse and background

characteristics during a 2-hour interview.

We have thus far achieved good results in obtaining 6-month followup data on

these 184 subjects. All of the subjects have reached their 6-month

anniversaries: 94 percent have provided followup data, 2 percent refused or

could not be located, and 4 percent are overdue but still being pursued. To

obtain this response rate, the research staff employed the same persistence and

field techniques developed and used successfully by previous addict researchers

(Nurco et al. 1977; Robins 1966; Robins et al. 1974; Maddux and Desmond 1981;

Bale et al. 1984).

RESULTS

Demographic Characteristics

As one would expect for a sample of treatment graduates, including ones from

pain clinics and aftercare programs, this sample is somewhat older; better

educated; and more often employed, non-minority, and married than the typical

opiate addict sample. Of the 184 subject, 71 percent were males. The samples’

median age was 32 years old, with a range from 21 to 63. The subjects had

attended a median of 12.3 years of school, with one having attended as few as 3

years while another had attended as many as 4 years of graduate school. At the

time of the interview, 59 percent of the subjects were working, but 77 percent

had worked some of the immediately preceding year (a median of 6.6 months).

Of those 75 subjects who were unemployed, one-third were either disabled

(n=11), receiving welfare (n=1) or workmen’s compensation (n=3), in school full

time (n=6), supported by spouses (n=2), receiving prolonged severance pay (n=1),

or had a job waiting for them on discharge (n=1). The sample’s median

occupational prestige score for the current or last job held was 32.8, which is

approximately the score for a truck driver (Featherman et al. 1975). Whites

comprised 79 percent of the sample, blacks 18 percent, and Hispanics 3 percent.

Forty-nine percent of the sample were single, 22 percent married, 28 percent

separated or divorced, and 1 percent widowed.

Drug Addiction History

The sample members were all primary opiate addicts. They had first been

opiate-addicted a median of 9.3 years prior to the baseline interview (range = 0.3

to 25.3 years). Of course, many had intervening periods of abstinence--

voluntary or involuntary--and periods of intermittent drug use. When these

periods are excluded, the average “net” length of addiction was 4.5 years, with a

range from 2 months to 16 years. During the year prior to the baseline

interview, the subjects used illicit opiates a median of 98 days. Seventy-five

percent of the subjects began opiate drug use for the reasons usually cited for

recreational addiction (to get high, curiosity, to go along with others); the rest

cited medical reasons.

138
TABLE 1

Recruitment Design: Programs, Sample Size,

and Percent of Entire Sample

Time Since Dependence

Short

(less than 3 months)

Long

(3 months or more)

Psychological

Adjustment

Social Adjustment Social Adjustment TOTAL

Low High Low High

HIGH

Methadone Pain Therapeutic

Maintenance Clinic Community

12 (6%) 24 (13%) 42 (23%)

Low

Pubilc Inpatient

Detox [30]/

Out-patient

Short-term

Methadone

Detox [3]

33 (18%)

Private, Corrections

Inpatient Drug CounDetox in seling

Psychiatric

Hospital

31 (17%) 5 (3%)

Aftercare

27 (15%) 105

outpatient

Drug Free

10 (5%) 79

TOTAL 45 55 47 37 184

Note: Cell entries are 1) the modality of treatment, 2) the number of subjects

recruited from that modality, and 3) the percentage of the entire sample

recruited from that modality.

139
Extent of Relapse at 6 Months

As reflected by differences in definitions across studies in this volume, the

precise meaning of “relapse” may vary widely. This chapter assumes that,

theoretically, relapse during the followup period is a continuous variable ranging

from complete abstinence to daily use. Although abstinence and relapse are

categorical concepts in layman’s terms and in some of the early scientific

literature (e.g., Ray 1961), recent research (e.g., Zinberg and Jacobson 1976;

Kurland et al. 1969; McAuliffe et al. 1985a) has shown that drug use by addicts

following treatment may assume a variety of patterns covering the entire

continuum of use. Moreover, the operant and respondent conditioning model of

opiate use that guides this research (McAuliffe and Gordon 1980; McAuliffe and

Ch’ien 1986) views addiction as a quantitative variable reflecting the strength of

the drug-taking response. A continuous concept of relapse has the advantage of

including the entire range of opiate use outcomes. The present authors hold that

it makes little sense to consider any recurrence of a chronic disease as a complete

failure to treatment: a more realistic approach is to view amelioration rather

than cure as the goal of drug treatment. If so, extent of opiate use during

followup reflects the degree of relapse.

Consistent with this theoretical view, this chapter employs two operational

definitions of relapse: 1) the number of days of opiate use during 6 months

following completion of a treatment program, and 2) a series of ordered

categories summarizing the amount of opiate use during the 6 months as shown

in table 2. While both measures are based on the same data, the first measure

describes the central tendency of the responses, whereas the second describes

their overall distribution. The validity of these “behavioral” measures was

demonstrated in our previous research (McAuliffe et al. 1985a), and in

methodological research by others (Amsel et al. 1976; Bale 1979; Maddux and

Desmond 1975; Pompi and Shreiner 1979; Stephens 1972). In the present study,

however, we tested the measures further by correlating them with seven-point

semantic differential items indicating the extent of being “addicted” versus “nonaddicted” and the extend “on opiates” and “off opiates” at followup. (For baseline

versions of these measures, see items 3 and 4 in table 3 below.) The correlations

were .56 and .71 respectively, indicating a statistically significant degree of

convergent validity (Campbell and Fiske 1959) between the behavioral measures

and the semantic differential measures of relapse at followup.

Inspection of table 2 reveals a wide range of relapse experience over the

modalities of treatment. At one end of the continuum, a majority of the clients

completing publicly funded short-term detoxification program (PDX) had periods

of daily opiate use, whereas at the other end almost all of the clients in aftercare

(AFT) and outpatient drug-free programs (OPDF) were entirely abstinent or had

only rare slips during the 6-month followup period. The mean days of opiate

use was 31 for the entire sample, and ranged from 4 to 83 across modalities,

reflecting statistically significant variation in opiate use during followup over

modalities of treatment. It is also notable that the relapse experiences of the

clients treated in particular modalities coincided reasonably well with our

sampling design based on the time since detoxification and our judgment about

the social and psychological characteristics of clients the different programs

graduated.

140
TABLE 2

Outcome of Followup at 6 Months by Modality

Time Since Dependence

Short Long

(less thatn 3 months) (3 months or more)

Outcome

Abstinant or

Pam Slips

% % % % % % % %

(less than

6 days 26 50 46 70 80 82 90 89

Occasional

Use (6 to

25 days

Regular Use

(26 to 104

days)

3 9 7

7 6 18

4 0 3 0 3

17 0 0 0 4

Daily or Near

Daily (105 to

182 days or min.

2 wks daily), 62 33 29 9 20 1 5 10 4

Refused.

100 100 100 100 100 100 100 100

Mean Days of

Opiate Use 83 57 47 23 37 21 6 4*

n 29 12 28 23 5 39 10 27

In process 4 0 3 1 0 3 0 0

33 1 2 3 1 4 5 42 10 2 7

* Differences across all modalities is significant at the .001 level

141
TABLE 3

Correlations Among Measures of

Psychological Addiction at Baseline

Correlations

Measure (coding) 1 2 3 4

1.

2.

3 .

4 .

5 .

How often do you feel

a craving or need for

opiates? (5 = several

times a day; 0 = never) 

Are you currenetly psychologically addicted

to or dependent on

opiates? (l = yes, 0 = no) .64

Myself as I am today:

(7 = addicted, 1 = nonaddicted) .49 .56

Myself as I am today:

(1 = off opiates; 7 = on

opiates) .45 .47 .44

Number of days of

illlicit opiate use

during the year prior

to interview .45 .32 .35 .27

Note: n = 143 for all correlations, due to individual item non-response. All

of the correlations are significant at the .001 level.

142
Conditioning Theories of Relapse

Conditioning theories provide a common background for several major models of

relapse (Lindesmith 1968; McAuliffe and Gordon 1980; Vaillant 1969; Wikler

1965), but these models differ in the emphasis they place on particular

reinforcing stimuli. This chapter will examine data that are relevant to this issue.

Craving at Discharge

Before considering the question of which reinforcing and conditioned stimuli are

most important in the relapse process, the analysis will first estimate the common

causal assumption of these models--that the extent of relapse is a function of the

degree of addiction. Addiction in these analyses is assumed to be reflected by

the extent of craving, which the questionnaire measured by asking, “Right now,

how often do you feel a craving or need for opiates.” The questionnaire format

allowed answers ranging from “never” (scored 0) to “more than once a day”

(scored 5). The mean craving response at baseline (discharge) was 2.2, which

represents slightly more than once per week. However, 31 percent of the

subjects said they never craved, while another 31 percent said they craved

opiates more than once a day.

The validity of the craving measure was tested by correlating it with several

other questionnaire items measuring addition at baseline (table 3). A variety of

items measuring the same concept was included in the questionnaire to insure

reliability and to measure the extent to which the scores vary depending on

differing response formats. As table 3 shows, the craving measures, two of

which (2 and 3) ask about addiction directly and two of which (4 and 5) ask

about the cause of addiction (opiate use). The overall consistency between the

different measures indicates that they appear to focus on the same underlying

concept.

A goal of any treatment for opiate addiction, regardless of its theoretical

underpinning, is to reduce craving. (“Addiction” in this chapter is defined as a

psychological rather than a physiological state.) Table 4 reveals that modalities

differ significantly in the extent to which they have eliminated their clients’

craving and psychological addiction by discharge (see item 2 in table 3 for

description of psychological addiction). Those discharged from short-term

programs, including public and private inpatient detoxification programs and

pain clinics, had high craving rates. The relatively low percentage of pain

patients admitting to psychological “addiction” may be a reflection of pain clinics’

ideology, which denies that their patients are “addicts” while allowing that the

patients are “drug dependent.” Despite long periods in treatment, subject from

methadone maintenance programs were usually detoxified immediately before the

baseline interview and consequently were experiencing craving as often as the

short-term patients. By contract, clients from the long-term drug free programs

(OPDF, AFT, TC), even programs located in prisons (CORR), reported much

lower levels of craving and psychological addition than did clients from shortterm programs. It is noteworthy that all long-term clients were either

outpatients, halfway house, or re-entry facility residents. By contract, all the

recently detoxified clients, except methadone maintenance graduates, were

inpatients. Thus, the recently detoxified clients reported more craving than did

the long-term clients, even though at the same time of the interview the recently

detoxified group was much less exposed to environmental cues that might cause

craving than was the long-term group.

143
TABLE 4

Craving by Type of Program

Mean Frequency % PsychologiType of Program of Cravinga ca1ly Addicted n

Public Detoxification 3.4 66 29

Methadone Maintenance 3.3 73 12

Private Pychiatric 3.2 6 1 28

Pain Clinic 2.3 29 2 4

Corrections 2.0 60 4

Outpatient Drug Free 1.7 44 10

Aftercare 1.0 26 27

Therapeutic Community 1.0 13 39

TOTAL 2.2 41 173

Significant p<.01 p<.01

aCraving scale: 0 = never, 1 = less than once a week , 2 = once per week,

3 = several times a day, 4 = once a day, 5 = more than

once per day.

144
The obvious correspondence between the rates of craving in table 4 and relapse

rates across modalities in table 2 suggested the need to examine the relationship

between craving and relapse directly. Bivariate regression analysis found that the

extent of craving explained a significant amount of the variation in relapse (the

standardized regression coefficient was .30, p < .001), and the relationship

remained significant when the effects of the individual modalities of treatment

were controlled statistically (standardized b = .16, p < .05).

The Causes of Craving

Since craving at discharge and the extent of relapse at followup appear to be

related, as conditioning theories suggest that they would be, one naturally turns

to consideration of what the precise cause of craving is. Conditioning theory

itself is neutral on this point, since a response such as drug taking may be

reinforced in a variety of ways (Carr 1984; McAuliffe and Gordon 1980;

McAuliffe et al. 1985b). Consequently, a variety of conditioned cues may

stimulate craving, and theorists differ on which cues are most important. On the

one hand, some authors (Lindesmith 1968; Wikler 1965; O’Brien et al. 1981) view

relief and avoidance of withdrawal sickness as the most important source of

reinforcement for chronic opiate use. They have emphasized conditioned

withdrawal and cues similar to withdrawal as factors in causing relapse.

Lindesmith (1968), for example, speculated that avoidance of withdrawal distress

by opiates generalizes to avoidance of any distress, and that long after

detoxification, addicts may return to opiate use in response to distress of various

kinds.

On the other hand, McAuliffe (1982) and McAuliffe and Gordon (1980) place

greater emphasis on a wide range of conditioned stimuli, such as those associated

with euphoria seeking, pain relief, and anxiety reduction. These stimuli are

present in the addict’s environment, independent of withdrawal and the level of

physiological dependence, and are not systematically extinguished during the

course of most primary drug treatment (McAuliffe and Ch’ien 1986).

The present study took two approaches to the question of which cues are most

important. The first was to ask subjects what was currently causing them to

crave; and describing to them certain verbal pictures associated with different

reinforcers, in order to determine how much the cues would cause them to crave

during the interview. Tables 5 and 6 present the results of these efforts. The

second approach employed causal modeling and is described below.

For table 5, subjects who had reported some current craving were told, “I want

to know what are the things that cause you to crave (desire or need to use)

opiates. I'll read the reason, and you tell me how important it is for you.” The

response categories were “very,” “somewhat,” slightly,” and “not at all important.” "

Table 5 shows that the reasons with the highest overall ratings reflect craving

caused by anxiety, depression, and euphoric effects. Least important in the

addicts’ own judgment were both unconditioned and conditioned withdrawal

sickness, socializing, and need for sexual facilitation.

However, the importance of some of these causes varied significantly from

modality to modality, primarily reflecting differences in the time since the last

detoxification. As a group, clients from short-term detoxification programs and

methadone maintenance gave highest importance to unconditioned withdrawal

sickness and euphoria seeking. By contrast, clients from long-term drug-free

programs hardly mentioned withdrawal but did emphasize the negative effective

145
TABLE 5

Mean Importance of Reasons for Current Craving

Time Since Physiological Dependence

Short Long

(less than 3 months (3 months or more)

Reasons for PDX MM Psy Pain COFR TC OPDF AFT

Craving (n= (n= (n= (n= (n= (n= (n= (n=

26) 10) 22) 16) 3) 20) 17) 121)

You are anxious and know

that the drug will give

you relief 2.5 2.6

You just want to take it

because it feels good 2.1 2.0

You're feeling depressed 2.1 1.9

You are urder pressure

and you want to relax 2.0 1.7

You are having trouble

handling thing and you

know that you would funtion better if you took

an opiate drug 1.7 1.9

You're angry with someone or about something 1.4 1.0

You don't feel quite

right" off drugs 1.6 2.1

You remember going

through withdrawal and

the memory makes you

feel uncomfortable or

drug sick 1.5 1.9

You feel sick from the

lack of drugs (withdrawal) 1.8 2.3

You're getting ready to

socialize with friends 1.0 1.4

You want to enjoy sex

or find a sex partnew 0.6 0.6

2.4 1.3

1.9 0.9

1.6 0.6

1.2 0.9

1.4 0.6

1.1 0.6

1.8 0.8

1.2 0.6

2.1 0.4

1.1 0.6

0.5 0.5

2.7 1.4 2.7 1.7*

3.0 1.6 1.9 1.4*

1.7 2.0 2.0 1.7*

2.5 1.6 2.0 1.8*

1.7 1.2 1.6 1.4

1.5 1.6 1.3 0.9

2.0 0.9 1.1 0.7'

1.0 0.8 1.1 1.1

0.0 0.3 0.7 0.2*

0.7 1.1 0.6 1.2

1.5 0.6 0.3 0.5

2.0

1.7

1.7

1.6

1.4

1.2

1.3

1.2

1.2

1.0

0.6

* Statistically significant differences across modalities

Note: Importance ratings: 3 = very, 2 = samewhat, 1 = slightly, 0 = not at all

146
TABLE 6

Craving Cures: Response to Hypothetical Situations

Presented as Stimuli During Interview

Cues PDX MM PhysPAIN COPR TC OPDF AFT TOTAL

(n=26) (n=10) (n=22) (n=16) (n=3) (n=20) (n=17) (n=121)

You are in a situation in which

you otfen used

opiates before 2.3 2.1 2.3

You remember

really enjoying

how good the feeling of being under

the influence of

opiates was 2.3 2.1 2.3

You open the medicine cabinet at a

friend's house end

there is a bottle

of opiates on the

shelf 1.6 2.1 2.2

Your dentist offers

to give you a prescription of opiates

for a toothache 1.9

You hurt your back

and the pain is

keeping you awake 1.6

2.4 2.5

2.3 2.5

You see someone

else taking a drug 2.1

You win on the

state lottery and

suddenly you have

some extra cash

to spend 2.4

You're really bored

with nothing to do 1.9

You are going out

with a close friend

and really want to

celebrate 1.5

1.9

1.8

1.2

1.7

2.0

1.9

1.5

1.5

1.1

0.6

0.7

1.1

1.5

0.5

0.2

0.4

0.4

2.6 1.9 2.1 1.9* 2.0

2.6 1.7 1.7 1.9

2.2 2.0 2.0 1.6

2.2 1.4 1.9 1.6

2.4 1.3

2.4 1.6

2.4 1.6

1.6

0.6

1.3

0.9

1.4

1.7

1.9

1.3

0.7

2.1*

1.8*

1.8*

1.5*

2.0*

1.1*

1.3*

0.8*

1.7

1.7

1.6

1.3

1.1

* Statistically significant differences accross modalities

Ratings: 3 = a lot, 2 = some, 1 = a little, 0 = not at all

147
TABLE 6 (Continued)

Cues PDX MM Psy PAIN CORR TC OPDF AFT TOTAL

(n=26) (n=10) (n=22) (n=16) (n=3) (n=20) (n=7) (n=17) (n=121)

You are watching a

movie or a TV show

depicting the story

of a person who is

about to use opiates after being

in a cold sweat

and yawning 1.0

There is an empty

bottle of druqs on

the table and you

start to think that

you'll soon be

feeling drug sick 1.2

You catch a cold.

you're nose is running and you're

feeling really bad 1.2

Talking about drugs

in an interivew

like this one 0.8

You need a book or

magazine article

about someone goinq

through severe

witdrawal 0.6

1.0

1.4

1.5

0.8

0.9

1.3

1.4

1.3

1.0

0.2

0.2

0.3

0.3

0.4

0.1

2.2

2.0

1.4

1.6

0.4

0.9

0.8

0.7

0.7

0.2

1.2 1.2* 1.0

1.1 0.9* 1.0

0.7 0.8* 0.9

1.3 0.9 0.6

0.5 0.4* 0.4

* Statistically significant differences across modalitities

Ratings: 3 = a lot, 2 = some, 1 = a little, 0 = not at all

148
state of being under pressure. Even though they were recently detoxified, pain

patients did not rate withdrawal items as important, most likely because they

typically took opiates in small regular doses and therefore key discriminative

stimuli for them were the clock and pain rather than withdrawal distress

(McAuliffe et al. 1985b). The reasonableness of these findings suggests that the

addicts may well have insight into the causes of their craving.

Table 6 presents the results of a slightly different question, one that attempts to

elicit craving during the interview by presenting verbal stimuli (vignettes) to the

respondents. All subjects, including those not currently bothered by craving,

were told, "I’m going to describe situations that could happen to you. Take a

minute or two to picture each situation in your mind. Then, tell me how much

it makes you feel an urge for opiates, even if you would NOT give in to the

urge.” The situations were specifically designed to distinguish conditioned

withdrawal from euphoria seeking and other motives.

The results in table 6 indicate that situations previously associated with drug use

(item l), euphoric effects (2), having ample supplies of opiates available (3 and

4). and pain (4 and 5) caused the most craving, whereas situations associated with

withdrawal sickness and relief of withdrawal (items 10, 11, 12 and 14) caused the

least. As in the previous set of items, pain patients responded differently from

most of the other clients: they experienced urges only in response to pain--back

and dental. Only subjects in corrections programs responded to the withdrawalassociated stimuli. With occasional exceptions, clients from the remaining

modalities responded similarly to each other over the various stimuli. Thus, the

combined results of these two sets of items suggest that stimuli associated with

euphoric effects and high availability (which often translates into euphoria) and

with relief of negative feeling states (anxiety and depression) were most likely to

cause craving in persons graduating from drug treatment.

Causal Model of Relapse

To test these same hypotheses using statistical causal modeling, we estimated a

preliminary model of the relapse process at 6 months following discharge (figure

1). The model included a composite index of anxiety and depression items from

the Hopkins Symptom Checklist (DeRogatis et al. 1974); euphoria seeking (item 2

from table 6 plus the subject’s response to a question on his/her willingness to

take a constant, lifelong euphoria pill); a measure of current physical pain,

degree of current physiological dependence (one item); responsiveness to

conditioned withdrawal stimuli (items 10 and 11 from table 6); time since

detoxification; amount of opiate use during the year prior to the baseline

interview; number of “extinction trials” (times when drugs were available but not

used since detoxification); and opiate availability at baseline. The zero-order

correlations of the independent variables with relapse at 6 months are presented

in table 7. They show that relapse had a number of significant predictors, pain

being the weakest in this set of variables and availability at baseline having a

small negative zero-order correlation with opiate use during followup.

The results of the causal modeling in figure 1 showed that the effects on relapse

of most variables, except physical dependence, were felt through craving. When

craving and physiological dependence were included in a regressing analysis of

relapse, none of the other factors had significant direct path coefficients to

relapse. Craving itself was a significant function of the amount of opiate use in

the past year (which may be thought of as roughly reflecting the number of

reinforced trials) and several stimuli, including anxiety and depression,

149
FIGURE 1

Conditioning Model of Relapse
TABLE 7

Zero-order Correlations of Independent Variables with

Days of Opiate Use During the 6-Month Followup Period

Independent correlation with

Variable Days of Opiate Use P value

During Followup

Months since detoxification

at baseline

Craving

Physical Dependence

Number or Extinction

Trials

Euphoria Seeking

Depression and Anxiety

Conditioned Withdrawal

Availability

Pain

-.31 .01

.30 .01

.25 .01

-.25 .01

.20 .01

.16 .02

.14 .08

-.10 .09

-.01 .47

151
unconditioned and conditioned withdrawal sickness, and euphoria-seeking. The

sizes of these latter path coefficients were all roughly equivalent to each other.

One surprising result was the lack of a significant effect of availability on

craving. This effect was previously demonstrated experimentally by Meyer and

Mirin (1978) and, therefore, was left in the present model despite its lack of

statistical significance. Since the availability at baseline also did not affect

relapse directly, in our subsequent work on these data we will have to examine

this measure more closely. The most likely explanation of this result is that

availability may change rapidly soon after discharge; therefore, availability just

before discharge may not be a good long-term predictor of relapse. Also, the

pain measure had a negative effect on craving, a result which will require closer

investigation. The most likely explanation is that pain clinic patients had the

highest scores on the pain measure, but only moderate scores on craving.

Overall, however, the fit of the data to theoretical expectations is good.

DISCUSSION

We must emphasize first of all that these are preliminary results from a study

still in the field collecting and processing data. As the project proceeds, the

results will almost certainly change to some degree, although the conclusions

should remain basically the same.

The results of our field effort are encouraging. The research team has recruited

subjects in similar situations from a wide range of modalities, despite the fact

that treatment graduates for modalities, such as methadone maintenance, are a

comparatively rare species. Interviewers have succeeded in obtaining 6-month

followup interviews with 94 percent of the sample. Almost as many 12-month

followup interviews have been completed. Moreover, a validity check of key

variables indicates that the data are clean.

Several substantive findings stand out. As expected, the modalities varied widely

in outcomes during the first 6 months. We were also able to predict these

outcomes rather well with a sampling design based on the time since

detoxification and the kinds of clients who were admitted. The findings also

confirm the theoretical importance of craving at discharge as a factor in

understanding relapse, even after the type of drug treatment program a subject

graduated from is controlled. Except for physical dependence, other major

hypothesized causes of relapse appeared to affect relapse primarily through their

ability to cause craving. The most important factors in this regard were the

amount of recent drug use, physiological dependence, anxiety and depression,

conditioned withdrawal sickness, and euphoria seeking. Again, we must

emphasize the preliminary nature of these analyses.

Although a part of the evidence suggested that some of these factors may be

slightly more important than others, the safest conclusion at this point in the

study is that the evidence as a whole favors an important role for each. The

differences in importance of withdrawal from one analysis to the next probably

reflect differences in what is being addressed in each analysis. The data in table

6 and figure I reflect the ability of stimuli to elicit craving when those stimuli

do occur in the vignette. However, since powerful stimuli may actually occur

infrequently during followup, they may play a relatively insignificant role in

predicting relapse during followup (table 7). In a previous study, McAuliffe

(1982) found that conditioned withdrawal symptoms occurred in many subjects,

but only in a few of those cases did those symptoms cause relapse.

152
Clinical Implications

Research on relapse should have important clinical implications. Clients in

treatment and aftercare programs should be educated regarding the course of

their disease and the prospects for recovery when certain events, such as a “slip”

or “lapse” occur. Recovering addicts benefit from knowing what the major

causes of craving and relapse are and how they can be avoided (McAuliffe and

Ch’ien 1986). Studies of addict careers--as well as studies of the causes of

relapse--can, therefore, be quite useful in treatment if the findings are

communicated effectively to drug counselors and their clients, and systematically

incorporated into relapse prevention programs (e.g., Zackon et al. 1985; Marlatt

and Gordon 1979).

Evidence in the present study on relapse rates and craving across modality

suggests a change in clinical emphasis. Completers of long-term drug-free

programs and aftercare report less craving and were less likely to relapse. Highly

motivated clients from short-term programs and methadone maintenance should

be channeled into these drug-free modalities in order to reduce craving, with the

promise that satisfactory completion of the program offers the best chance of

recovery.

Finally, the discussion of the meaning and measurement of relapse has

implications for treatment policy. The present research and the author’s previous

work (McAuliffe et al. 1985a) indicates that a single episode of opiate use does

not necessarily imply a high degree of relapse long-term. studies which define

relapse as any use of the drug of abuse produce the highest possible relapse rates,

and thereby can create an atmosphere of therapeutic pessimism for clinicians and

policymakers. Research presented in this volume clearly demonstrates that

addiction is a chronic disease. A chronic disease model of addiction would take

amelioration rather than absolute cure as a realistic treatment goal; the

measurement of relapse should ideally be consistent with this goal.

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ACKNOWLEDGMENT

National Institute on Drug Abuse Grant Number DA-02798 supported this

research.

AUTHORS

William E. McAuliffe. Ph.D.

Barry Feldman, B.A.

Rob Friedman, M.A.

Elaine Launer, B.A.

Elizabeth Magnuson, B.A.

Carl Mahoney, B.A.

Susan Santangelo, B.A.

William Ward, B.A.

Robert Weiss, M.D.

Harvard Medical School

Department of Psychiatry

MC Lean Hospital

Belmont, Massachusetts

Harvard School of Public Health

Department of Behavioral Sciences

677 Huntington Avenue

Boston, Massachusetts 02115

156
Relapse to Use of Heroin, Cocaine,

and Other Drugs in the First Year

After Treatment

Robert L. Hubbard and Mary Ellen Marsden

INTRODUCTION

Previous research documents that the major drug abuse treatment modalities

substantially reduce drug use during and after treatment from pretreatment levels

(Craddock et al. 1985; Hubbard et al. 1984; Tims 1981; Simpson et al. 1978;

Simpson and Lloyd 1978). Many clients, however, relapse to drug use after

treatment. Little is known about the process and timing of relapse, particularly

when multiple drugs are used before and after treatment. Better understanding

of the nature and causes of relapse should contribute to the design of more

effective treatment and aftercare approaches. Modified treatment approaches

could reduce relapse rates for particular types of drugs, extend the time until

relapse, and lessen the severity of posttreatment drug use. This brief paper

describes the complex nature of relapse and examines the timing of relapse to use

of specific drugs and the change from pretreatment periods in overall drug use

patterns for a sample of 2,280 drug abuse treatment clients participating in the

Treatment Outcome Prospective Study (TOPS).

MULTIDIMENSIONAL NATURE OF RELAPSE

Abuse or dependence is usually characterized in terms of the use of a single

substance such as heroin, alcohol, or tobacco. The understanding of relapse to

drug abuse, however, is complicated by current drug abuse patterns that involve

multiple use of a wide range of types of licit and illicit drugs (Craddock et al.

1985) and many patterns of abuse. A common pattern is the weekly or more

frequent use of marijuana, cocaine, alcohol, and heroin (Hubbard et al. 1985).

Heroin abusers commonly substitute other drugs for heroin. Descriptions of drug

abuse and relapse that consider only single drugs are inadequate. Definitions of

relapse must take into account the patterns of use of multiple drugs and alcohol.

A multidimensional definition of relapse should also include consideration of the

type, extent, and timing of relapse.

A basic type of relapse is the posttreatment return to use of a specific drug (e.g.,

cocaine) that was used before treatment. A second type of relapse is the

nonmedical use of a drug to substitute for a principal pretreatment drug (e.g.,

other narcotics as a substitute for heroin). A more comprehensive definition of

relapse is the posttreatment resumption of the pretreatment pattern of drug use

(e.g., multiple use of heroin, cocaine, marijuana, and alcohol) or the development

157
of new patterns of use. Relapse, then, may be use after treatment of a specific

pretreatment drug, nonmedical use of its substitute, or it may refer to an overall

use pattern.

The likelihood of relapse after a particular mode of treatment can be measured in

various ways. The four methods of measurement below consider two key

dimensions: frequency of use and pretreatment drug use patterns.

Any Posttreatment

Use Among All Clients

Any Posttreatment Use

Among Pretreatment

Weekly Users

Any Posttreatment Use

Among Pretreatment

Monthly Users or

Nonusers

- Percentage of all clients reporting any use

in the year after treatment.

- Percentage of clients who used weekly or

more frequently before treatment and

reported any use in the year after treatment.

- Percentage of clients who used in the year

after treatment among clients who did not

not use weekly in the year before treatment.

Posttreatment Users Who

Report Daily Use

- Percentage of clients who reported using

their posttreatment primary drug daily for

at least 30 days in the year after treatment

among all clients who used that drug in the

year after treatment.

Each measure is useful but only partially describes relapse. The first definition

does not consider posttreatment or pretreatment use levels. The second and third

definitions consider pretreatment use levels but not posttreatment use levels. The

fourth definition focuses on the most severe relapse. A complete exploration of

posttreatment use should include relapse to weekly use as well as relapse to the

pretreatment frequency. Relapse measures should be developed that consider

resumption of any use as well as use that is less severe or frequent than

pretreatment patterns of use.

Within each of these types of relapse, indicators of the extent of relapse, such as

frequency and severity, add an important dimension to the description of drug

use patterns and use of specific drugs. The timing dimension considers the

latency, duration, and episodic nature of relapse (Mann et al. 1984). Drug abuse

treatment clients may continue drug use throughout treatment or may cease use

during treatment, only to resume use before leaving treatment or at various times

after treatment. The first posttreatment use may be brief and have little clinical

significance, or use may continue for weeks, months, or years, The lengths of

periods of use and abstinence after treatment are variable and the periods are

cyclical (see Maddux and Desmond 1974).

To appropriately study relapse, the pretreatment pattern of drug use and the

overall posttreatment pattern should be considered. Posttreatment marijuana use

by a client who used heroin daily before treatment and by another who used only

marijuana are not equivalent. Shifts to less serious drug use patterns can be

viewed as indicators of improvement rather than relapse.

A brief episode of infrequent use may not indicate serious relapse. On the other

hand, brief episodes of heavy use, even those separated by long intervals of

abstention, may be predictive of serious relapse in the future. Relapse needs to

158
be defined by level and severity and within the context of overall use patterns.

Indices of multiple drug use patterns have been developed and used in major

national studies (Bray et al. 1982; Savage and Simpson 1976).

METHODS

The Treatment Outcome Prospective Study (TOPS) used personal interviews to

obtain detailed drug use histories of 11,750 clients entering 41 detoxification,

outpatient methadone, residential, and outpatient drug-free (OPDF) treatment

programs in 10 cities from 1979 to 1981 (Hubbard et al. 1984). Three different

samples totaling 5,000 of these clients were reinterviewed at 3 months, 12

months, 2 years, and 4 years after treatment.

Most of the analyses reported in this paper are based on the pretreatment and

posttreatment drug-use patterns of 2,280 clients from the 1979 and 1980

admission cohorts who were interviewed at intake and approximately 1 year after

they left treatment in one of the four modalities.

The drug-use measures developed for this paper are based on the comprehensive

assessments of nonmedical use of 12 different drug types. These assessments

were obtained in interviews covering the year before admission and the first year

after termination. Quantity and frequency of alcohol use and frequency of use

of all types of drugs for nonmedical purposes during the 12-month periods

before and after treatment were obtained. Clients were asked to report their

frequency of use on a 9-point scale from nonuse to use four or more times per

day. At the followup, clients were asked how much time elapsed before use of

specific drugs was resumed after leaving treatment. For heroin and for the

clients’ primary drug of abuse at the time of followup, questions were asked

about the time until daily use was resumed.

NATURE AND EXTENT OF RELAPSE FOR FOUR SPECIFIC DRUGS

Drug use in the first year after treatment was common. About one in five

reported weekly or more frequent heroin use, and about one in four reported

weekly or more frequent use of other nonnarcotics (amphetamines, sedatives,

barbiturates, minor tranquilizers) (Hubbard et al. 1986.) While such simple

frequency data on posttreatment use are informative, relapse can be described

more appropriately in the context of pretreatment use. Marijuana use, while of

interest, was not considered in the present analysis, and is excluded from the

“other nonnarcotics” category.

Types of Relapse

The magnitude of the relapse rates for each of the four types of drugs shown in

table 1 differs by drug and definition of relapse. The relapse rates among

pretreatment weekly users were similar for all drugs. Posttreatment use rates for

cocaine and other nonnarcotics for pretreatment nonusers and those who used

monthly or less frequently before treatment were twice the rates for heroin and

other narcotics. This posttreatment use by pretreatment nonusers or low-level

users may mean that cocaine and other nonnarcotics were being used in lieu of

heroin and/or other narcotics used before treatment. The probability of relapse

to daily use of a primary drug among all posttreatment users was highest for

heroin (54 percent). Twenty-five percent or fewer users of other narcotics,

cocaine, and other nonnarcotics relapsed to daily use of these drugs.

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TABLE 1

Types of Relapse Rates in the Year After

Treatment for Four Drug Types

Types of

Relapse Heroin

Drug Used Posttreatment

Other Other

Narcotics Cocaine Nonnarcotics

% % % %

Any Posttreatment Use

Among All Clients

31.9 28.3 44.0 45.3

Any Posttreatment Use

Among Pretreatment

Weekly Users

58.6 57.0 65.0 60.2

Any Posttreatment Use

Among Pretreatment

Monthly Users or

Nonusers

16.8 19.7 36.2 35.3

Posttreatment Daily

Use Among Posttreatment Users

53.6 25.1 20.1 16.7

Time Until Relapse

Former clients were asked when they first used each drug after treatment.

Clients also identified their primary problem drug and reported when they first

used that drug daily for at least 1 week.

In table 2, the distributions of the periods between termination from treatment

and first use of four types of drugs are presented for all former clients who

reported any use in the first year after treatment. About 15 percent of clients

who used drugs other than marijuana in the year after treatment were using the

drug at treatment termination, and another 25 percent resumed use within the

first week after discharge. A month after leaving treatment, about 60 percent of

those who would relapse in the year after treatment had resumed use. About

half the remaining 40 percent relapsed 1 to 3 months after termination. The

timing of relapse appears to be similar for the four types of drugs. The length

of time until relapse may be critical for long-term rehabilitation outcomes.

160
TABLE 2

Time Until First Use in the First Year After Treatment

Among Clients Who Reported Posttreatment Use

of Each of Four Drug Types

Drug Used Posttreatment

Weeks After

Termination Heroin

Other Other

Narcotics Cocaine Nonnarcotics

% % % %

Used at termination 15.3 14.4 10.7 15.2

Within I week 28.9 22.8 21.6 24.3

2-4 weeks 21.4 24.1 24.6 24.5

5-13 weeks 15.8 13.9 17.6 16.0

14 or more weeks 18.6 24.8 25.5 20.0

Total

Number of Posttreatment Users

100.0 100.0 100.0 100.0

720 626 984 1,026

Mean Days to Relapse

Among Those Who

Used Posttreatment

55.0 68.3 71.9 58.8

Table 3 shows the time until first relapse to daily use for the four types of drugs.

One-third of posttreatment daily heroin, cocaine, and other nonnarcotics users

and half of the other narcotics users who were to become daily users in the year

after treatment were using daily at treatment termination. On the other extreme,

about one in five had been out of treatment at least 3 months before beginning

daily use. Extending the period between treatment termination and daily use

would seem to be important to establishing long-lasting abstinence. The

variations in the timing of the relapse to daily use for narcotics other than heroin

compared to the other three types of drugs suggest that the course of relapse to

daily use may differ by drug.

The timing of relapse to daily use appears to be different from the timing of

relapse to first use. Those who were to become daily users were most likely to

relapse immediately following termination. First daily use for those who did not

immediately start using heroin daily after treatment was more evenly spread over

the 3-month time span than was first use of the same drug.

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TABLE 3

Time Until Daily Use in the Year After Treatment

Among Clients Who Reported Posttreatment Use

of Each of Four Drugs Types

Drug Used Daily Posttreatment

Weeks After

Termination

Other Other

Heroin Narcotics Cocaine Nonnarcotics

% % % %

Used at termination 32.1 49.0 34.9 37.4

Within 1 week 13.5 9.6 7.1 11.7

2-4 weeks 20.7 15.9 19.1 16.4

5-13 weeks 15.5 14.0 19.8 15.8

14 or more weeks 18.1 11.5 19.1 18.7

Total

Number of Posttreatment

Daily Users

100.0 100.0 100.0 100.0

386 157 126 171

CHANGE IN PATTERNS BETWEEN PRETREATMENT AND POSTTREATMENT YEARS

Describing posttreatment use of a specific type of drug does not provide a

complete picture of relapse. Here the concept of relapse to drug use is

broadened to consider differences between pretreatment patterns and

posttreatment patterns.

Multiple drug use by TOPS respondents before treatment was common.

Comparisons of the use patterns of clients in the TOPS and Drug Abuse

Reporting Program (DARP) research provides evidence of the increasing

prevalence of multiple drug use over the past decade (Hubbard et al. 1985). The

focus on daily use of heroin and other narcotics alone in many studies of

treatment clients in the 1970s (Savage and Simpson 1977) may no longer be fully

descriptive of the extent of drug use or be appropriate indicators of relapse.

Several approaches were used in TOPS analyses (Bray et al. 1982; Hubbard et al.

1985) to examine patterns of multiple drug use including a set of drug use

patterns adapted from the DARP classification scheme (Simpson 1974). The

extensive variety of combinations of weekly use of eight drug types used by

TOPS clients suggested that broad rather than specific categories were required to

describe clinically useful patterns.

162
Patterns were defined by hierarchical rules that required weekly or greater use of

key drugs or drug types. First, two types of heroin users were defined: heroin

users who used other narcotics and heroin users who did not use other narcotics.

Next, among the remaining clients, users of narcotics other than heroin and users

of nonnarcotics (excluding marijuana and alcohol) were then identified. Finally,

alcohol/marijuana users and minimal users (clients who did not report weekly use

of any drug or alcohol) were the residual group. The resulting five categories

are hierarchical; clients were included in the less serious patterns only if they did

not meet the criteria for the more serious patterns. The defining characteristics

of the patterns do not identify all drugs used by the clients. Rather, they

indicate the key drugs and their use levels. In table 4, the five hierarchical

patterns are shown. The alcohol and marijuana patterns were included with

nonweekly users of any drug. This analysis does not consider any level of use of

alcohol, marijuana, or infrequent drug use as relapse.

From table 4 it is clear that the patterns shift between pretreatment and

posttreatment periods, particularly to the cells to the right of the diagonal,

indicating a movement to less serious use patterns after treatment. More than 40

percent of each of the three types of narcotic users move to the

alcohol/marijuana/minimal pattern. However, 20 percent of heroin-othernarcotic users, 39 percent of heroin users, and 24 percent of other narcotic users

resume their pretreatment use pattern. Between 10 percent and 20 percent of the

users of heroin and/or narcotics reduced their use to nonnarcotics in the year

after treatment. About 16 percent of heroin-other-narcotic users eliminated

heroin use but resumed other narcotics use.

Because drug abuse is a multidimensional phenomenon best described by multiple

drug patterns rather than single drugs, additional analyses should be conducted to

examine in more detail the transitions among drug abuse patterns from

pretreatment to posttreatment periods. The patterns in table 4 provide a

structure for more detailed analyses of relapse.

163
TABLE 4

Relapse Rates to Different Drug Use Patterns

in the Year After Treatment for Clients

with Five Pretreatment Use Patterns

Posttreatment Drug Use Pattern

Pretreatment HeroinDrug Use Other

Pattern Narcotics Heroin

Other Non- NonNarcotics narcotics relapsers*

% % % % %

Heroin-Other

Narcotics

(n = 225)

20.4 7.6 16.4 12.7 44.9

Heroin

(n = 643)

Other Narcotics

(n = 295)

Nonnarcotics

(n = 508)

Alcohol/Marijuana

Minimal

(n = 609)

5.1 38.7 2.8

8.1 2.0

4.7

3.8

24.4

2.4 6.1

10.6 42.8

18.3 47.1

27.8 59.0

2.8 4.9 12.8 75.7

*Includes all clients not classified as relapsing during the year of postreatment.

Some of these may have had alcohol, marijuana, or infrequent other drug use.

SUMMARY AND RECOMMENDATIONS

This paper briefly assessed the multidimensional nature of relapse to drug use,

the length of posttreatment abstinence periods for four types of drugs, and

resumption of drug use patterns.

Rates of relapse defined in various ways showed important differences among the

drugs. Relapse to daily heroin use, for example, was very high compared to the

relapse to use of the other three types of drugs. The timing of relapse was quite

similar for all 4 drugs. Approximately two-thirds of clients who relapsed did so

within the first 3 months after leaving treatment. Between 10 percent and 15

percent were using at treatment termination. More emphasis on aftercare and

postdischarge counseling that focuses on prevention of relapse might help reduce

relapse rates and increase periods of remission for relapsing clients.

164
Consideration of the complementary concept of reduction in overall use patterns

(in addition to reduction in use of individual drugs) could help researchers and

clinicians better understand posttreatment use. Because of the complexity of

drug abuse, different conceptualizations of relapse and reduction in drug use

need to be examined. The drug abuse pattern measure used here is one way to

describe the shift among patterns.

The preliminary analyses presented in this paper indicate the complex nature of

relapse among former drug abuse treatment program clients. Survival analysis or

failure rate analysis could also be used to examine the timing of relapse in more

detail. In order to learn how treatment can minimize the risk of relapse and

lengthen abstention periods, studies are needed to:

describe the multidimensional nature of relapse (type, extent, timing, and

the overall drug use pattern) and the relapse to use of specific drugs

within the context of multiple drug use patterns;

identify the correlates of relapse, particularly behavior, during treatment

and in the first 3 months after leaving treatment; and

assess the effects of relapse prevention efforts such as discharge

evaluations and aftercare services in the first months following

termination.

Relapse is a complex. dynamic process that must be examined more carefully by

researchers and clinicians. The extensive treatment histories of many clients

entering and re-entering programs suggest that recovery from drug use is long

term, and episodic relapses are experienced. The process of recovery occurs

throughout the drug use and treatment career. A better understanding of this

process should lead to improved treatment and aftercare services that will reduce

verall relapse rates, extend remission periods, and reduce the duration of relapse

episodes.

REFERENCES

Bray, R.M.; Schlenger, W.E.; Craddock, S.G.; Hubbard, R.L.; and Rachal, J.V.

Approaches to the Assessment of Drug Use in the Treatment Outcome

Prospective Study. Prepared for the National Institute on Drug Abuse.

Research Triangle Institute Report No. RTI/1901/01-05S, 1982.

Craddock, S.G.; Bray, R.M.; and Hubbard, R.L. Drug Use Before and During

Drug Abuse Treatment: 1979-1981 TOPS Admission Cohorts. DHHS

Publication No. (ADM) 85-1387. Rockville, MD: National Institute on Drug

Abuse, 1985.

Hubbard, R.L.; Rachal, J.V.; Craddock, S.G.; and Cavanaugh, E.R. Treatment

Outcome Prospective Study (TOPS): Client characteristics and behaviors

before, during, and after treatment. In: Tims, F.M., and Ludford, J.P., eds.,

Drug Abuse Treatment Evaluation; Strategies, Progress and Prospects.

National Institute on Drug Abuse Research Monograph 51. DHHS

Publication No. (ADM) 84-1329. Washington, DC: Supt. of Docs.. 1984.

Hubbard, R.L.; Bray, R.M.; and Craddock, S.G. Issues in the assessment of

multiple drug use among drug treatment clients. In: Braude, M., and

Ginzburg, H.M., eds., Strategies for Research on the Interactions of Drugs of

Abuse. National Institute on Drug Abuse Research Monograph 68. DHHS

Pub. No. (ADM) 86-1453. Washington, D.C.: Supt. of Docs., U.S. Govt.

Print. Off., in press.

165
Hubbard, R.L.; Marsden, M.E.; Cavanaugh, E.R.; and Rachal, J.V. Drug Use

After Drug Abuse Treatment, Followup of 1979-1980 TOPS Admission

Cohorts. Treatment Research Monograph Series. Rockville, MD: National

Institute on Drug Abuse, forthcoming.

Maddux, J.F., and Desmond, D.P. Obtaining life history information about

opioid users. Am J Drug and Alcohol Abuse 1:181-198, 1974.

Mann, N.R.; Charuvastra, V.C.; and Murthy, V.K. A diagnostic tool with

important implications for treatment of addiction: Identification of factors

underlying relapse and remission time distributions. Int J Addict 19(1):25-44,

1984.

Savage, L.J., and Simpson, D.D. Measures of Illicit Drug Use: National

FOIIOWUp Study of Admissions to Drug Abuse Treatments in the DARP

During 1969-1971. Institute of Behavioral Research Report, 76-14. Fort

Worth: Texas Christian University, 1976.

Savage, L.J., and Simpson, D.D. Illicit Drug Use and Return t o

Treatment: National Followup Study of Admissions to Drug Abuse

Treatments in the DARP During 1969-1971. Institute of Behavioral Research

Report, Report 77-3. Fort Worth: Texas Christian University, 1977.

Simpson, D.D. Patterns of multiple drug abuse. In: Sells, S.B., ed., The

Effectiveness of Drug Abuse Treatment (Vol. 1). Cambridge, MA: Ballinger

Publishing Company, 1974.

Simpson, D.D., and Lloyd, M.R. Alcohol and illicit drug use: National followup

study of admissions to drug abuse treatments in the DARP during 1969-1971.

Am J Drug Alcohol Abuse 5(1):1-22, 1978.

Simpson, D.D.; Savage, L.J.; and Sells, S.B. Data Book on Drug Treatment

Outcomes--Followup Study of 1969-1972. Admissions to the Drug Abuse

Reporting Program (DARP). Institute of Behavior Research, Report 78-10.

Fort Worth: Texas Christian University, 1978.

Tims. F.M. Effectiveness of Drug Abuse Treatment Programs. National Institute

on Drug Abuse. Treatment Research Report. Washington: D.C., Supt. of

Docs., U.S. Govt. Print. Off., 1981.

AUTHORS

Robert L. Hubbard, Ph.D.

Mary Ellen Marsden, Ph.D.

Center for Social Research and Policy Analysis

Research Triangle Institute

P.O. Box 12194

Research Triangle Park, North Carolina 27709

166
Smoking Cessation and Relapse

Among Cardiac Patients

George E. Bigelow, Cynthia S. Rand, Janet Gross,

Thomas A. Burling, and Sheldon H. Gottlieb

Most clinical research concerning smoking cessation has been conducted with

participants in organized smoking cessation treatment programs. Such

individuals, and their experiences with smoking cessation, may not be

representative of the larger population of smokers. Participants in organized

cessation programs certainly represent a self-selected subsample of smokers, and

little is known about the dimensions in which this self-selected group might

differ from other smokers. However, since the vast majority of smoking

cessation occurs outside of such structured treatment contexts, we can see that, at

least in a statistical sense, these treatment participants are an “unusual” subsample.

Perhaps further useful information concerning smoking cessation and relapse

might be gained by studying these processes in situations in which they

spontaneously occur, rather than in organized treatment settings.

Among the populations most likely to spontaneously discontinue their smoking

habits are individuals who have recently experienced an adverse cardiac health

event. In particular, it is estimated that approximately one-third to one-half of

smokers who suffer a myocardial infarction (MI) either discontinue or

dramatically reduce their smoking habit immediately following the event

(Burlington et al. 1984). In this chapter, we will summarize recent work we have

been conducting, examining cigarette smoking cessation, and relapse among

myocardial infarction patients.

POPULATION

Participants in these studies were hospitalized surviving myocardial infarction

patients who reported being cigarette smokers at the time of their heart attack.

SETTING

This work was undertaken because the naturally occurring epidemiology of

smoking in this population--with smokers rapidly dichotomizing themselves into

long-term quitters versus resumers of smoking--appeared to offer a convenient

context within which to examine factors associated with these differential

smoking outcomes. Other features of the cardiac care setting also made it

attractive as a context for studies of smoking behavior. The fact that surviving

myocardial infarction patients routinely received several days of intensive care in

the Coronary Care Unit where smoking was not possible, meant that all patients

167
would be beginning their ambulatory recovery period in a tobacco-abstinent

status. The fact that patients routinely remained in the hospital for several days

of ambulatory recovery following intensive care made it convenient to collect

data from patients and made it possible to assess their smoking during this

ambulatory period when smoking relapse became possible. In addition, medical

charts provided valuable supplemental sources of data, and routine medical

aftercare provided a convenient opportunity for assessing smoking status

outcomes post-hospitalization.

IN-HOSPITAL RELAPSE

When we first proposed to study smoking relapse in myocardial infarction

patients, the hospital’s cardiologists indicated that this was not practical since

these patients were not permitted to smoke. However, in our initial study we

found that these medical rules did not reliably control patient behavior.

In this first study (Baile et al. 1982) we conducted single predischarge interviews

with 66 patients concerning their smoking. These interviews covered smoking

history, health beliefs, and craving and smoking experiences during

hospitalization; these results were considered in relation to one another, in

relation to demographics, and in relation to medical chart information concerning

the severity of disease.

The most dramatic finding was the rapidity and prevalence of in-hospital

smoking relapse among these myocardial infarction patients. Patients had been

on the ambulatory recovery unit on average for less than 5 days, but during this

time fully 38 percent of the patients had resumed smoking. Among relapsers, the

mean latency to smoke following transfer from intensive care was 2.25 days.

Smoking relapse did not typically occur in full-blown intensity during

hospitalization; patients reported smoking an average of 5.14 cigarettes per day

when they smoked. Despite the relatively moderate level of this smoking, it was

considered a likely precursor of more intensive smoking upon hospital discharge.

Examination of the data to identify factors associated with, or predictive of,

smoking relapse revealed that the only significant relationships were with

indicators of myocardial infarction severity. Peak blood levels of the enzyme

creatine kinase (CK) were used as the primary objective biological index of

infarction severity. CK is released when tissue is damaged, and peak CK levels

can be used both diagnostically and prognostically in evaluating myocardial

infarctions. Higher CK levels are generally reflective of greater tissue damage.

Patients who relapsed to smoking during their hospitalization had average peak

CK levels that were significantly lower than those of patients who abstained

from smoking throughout their hospitalization. Thus, smoking abstinence

appeared most likely among patients who had suffered more severe infarctions,

and smoking relapse appeared most likely among patients with the least cardiac

damage.

The likelihood of smoking relapse bore a graded negative relationship to the peak

CK level, as illustrated in figure 1. This graded relationship was statistically

significant, with p < 0.005, according to Bartholomew’s chi-square test for

ordered samples.

168
FIGURE 1

From Burling et al. 1984. Copyright 1984, Lawrence Erlbaum Associates, Inc.

There were no significant differences between patients relapsing and abstaining

during their hospitalization on demographic characteristics, smoking histories,

health beliefs, or reported craving for cigarettes. Thus, severity of smokingrelated adverse health effects was a more powerful predictor of early smoking

abstinence versus relapse than were these psychosocial variables.

POST-HOSPITALIZATION SMOKING OUTCOMES

A major limitation of the previous study was that it examined smoking only

during the brief period of hospitalization immediately following myocardial

infarction. In a subsequent second study we followed patients’ posthospitalization to assess long-term smoking outcomes, and we used expired breath

carbon monoxide assessment to provide an objective biological index of smoking

status (Bigelow et al. 1984). Patients were contacted approximately 5 times per

week during their hospitalization, and were followed post-hospitalization for an

average of 12 months.

During the in-hospital period, some of the relationships observed in the previous

study were replicated. Again, a high rate of in-hospital smoking relapse was

observed--36 percent. Also, again, peak CK level was significantly lower in

those patients who resumed smoking during hospitalization.

In examining long-term smoking outcomes, peak CK was no longer a significant

predictor. However, another index of MI severity did indicate the same

relationship of smoking outcome to severity as was noted during the in-hospital

phase. Assessment of left ventricular ejection fraction by radionuclide

ventriculography was introduced into the cardiology service as a new diagnostic

and prognostic procedure part way through our study, so these data were

available only for 68 patients. Ejection fraction is a dynamic measure of cardiac

pump performance, providing a measure of the proportion of left ventricular

169
blood volume that is ejected when the heart contracts; it is generally accepted as

the best overall measure of cardiac performance and one of the best prognostic

indices of cardiac health. We found these biological measures of cardiac

function, collected in-hospital at the time of the infarction, to be predictive of

long-term smoking status outcomes during followup. Ejection fraction measures

showed that patients who relapsed to smoking during the followup period had

suffered less cardiac pump damage (i.e., they had higher ejection fractions) than

patients who abstained from smoking throughout the followup period. Thus,

once again, smoking cessation tended to occur in individuals with greater health

impairment, and smoking relapse tended to occur in individuals with lesser health

impairment. The differences in mean ejection fractions for the abstaining versus

relapsing groups was statistically significant, with p < 0.004.

ANTI-SMOKING INTERVENTION

A consistent finding in the first two studies was that smoking abstinence was

more likely in patients who had experienced a more severe infarction or suffered

greater cardiac impairment. These studies did not permit us to identify the

mechanism by which health status influenced behavior change; however, we

suspected that the mechanisms might be that the greater health threat served

more effectively to motivate behavior change.

In a subsequent study, we sought to increase the prevalence of post-MI smoking

abstinence by taking advantage of the motivational potential of the inpatient

cardiac treatment setting to encourage smoking cessation (Rand et al. 1985). One

hundred inpatients were randomized to receive either usual cardiology care and

education or to receive usual care plus a supplemental directive anti-smoking

message from a member of the research team. All patients received daily

interviewing about their smoking behavior, experience, and plans, as well as

daily breath carbon monoxide sampling to assess their smoking status.

As it turns outs, our randomization was irrelevant to outcome; rather it appears

that the attention we brought to bear on smoking for all subjects had an acrossthe-board effect of reducing in-hospital smoking relapse. The evidence for this

effect comes from examining the rates of in-hospital smoking relapse during this

study in comparison to the periods immediately preceding and immediately

following it. Prior to the start of this study, the incidence of in-hospital

smoking relapse was 39 percent. During this study, the incidence of in-hospital

smoking relapse fell, in successive time periods, first to 18 percent and then to 9

percent. Upon termination of this study and the contacts with patients and staff

concerning smoking, the incidence of in-hospital smoking relapse rose once

again--to 22 percent. Analysis of this final study is still underway, and its

results can only be considered preliminary. However, it appears that a procedure

of intensive data-gathering concerning smoking--a procedure that was intended

to be only neutral data-gathering and not an intervention--actually functioned as

an effective anti-smoking intervention and reduced the incidence of in-hospital

smoking relapse among post-MI cardiac patients. These data, though

preliminary, are encouraging of the possibility of developing and implementing

intervention programs for delivery in medical care settings that might effectively

reduce the prevalence of smoking inpatient populations.

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DISCUSSION

These data implicate patients’ health status and health concerns as important

determinants of smoking cessation and relapse. The preliminary results of our

intervention study suggest that it may be possible to develop intervention

procedures for incorporation into medical care settings that will significantly

reduce patients’ smoking. However, much work must yet be done to demonstrate

the practical feasibility of this approach. Survey data generally indicate that

concerns about health are the most common reason given by smokers for quitting

or for wanting to quit smoking. The present data suggest that smoking cessation

is enhanced to the degree that patients have experienced adverse health

consequences from their smoking. We would suggest that, for all the substance

abuse disorders, the probability of discontinuing substance use may depend, in

part, upon the extent to which the individual user has experienced adverse

consequences from that use.

REFERENCES

Baile, W.F.; Bigelow, G.E.; Gottlieb, S.H.; Stitzer, M.L.; and Sacktor, J.D. Rapid

resumption of cigarette smoking following myocardial infarction: Inverse

relation to MI severity. Addict Behav 7:373-380, 1982.

Bigelow, G.E.; Burling, T.A.; Baile, W.F.; and Gottlieb, S.H. Predictors of longterm smoking status after myocardial infarction. Paper presented at the

meeting of the American Psychological Association, Toronto, Canada, August

1984.

Burling, T.A.; Singleton, E.G.; Bigelow, G.E.; Baile, W.F.; and Gottlieb, S.H.

Smoking following myocardial infarction: A critical review of the literature.

Health Psychol 3:83-96, 1984.

Rand, C.S., and Bigelow, G.E. In-hospital relapse to smoking: An unexpected

intervention. Paper presented at the annual meeting of the Pavlovian Society,

1985.

AUTHORS

George E. Bigelow

Cynthia S. Rand

Janet Gross

Thomas A. Burling

Sheldon H. Gottlieb

The Johns Hopkins University School

of Medicine and Francis Scott Key

Medical Center

Baltimore, Maryland 21224

171
Clinical Implications of

Relapse Research

Bruce J. Rounsaville

Relapse and relapse prevention define the major clinical problems to be faced by

clinicians and researchers who work with substance abusers. Unlike other mental

disorders, substance abuse disorders have a necessary, if not sufficient, cause--

the abused drugs themselves. For all classes of abused substances, procedures are

highly developed for temporarily separating substance abusers from their abused

substances and keeping withdrawal symptoms at safe and comparatively

comfortable levels (Lowinsohn and Ruiz 1981). It is not necessary for any

detoxification procedures to last longer than 1 month and some can be

accomplished in less than 1 week (Riordan and Kleber 1980). Hence, if relapse

were not a major issue, substance abuse treatment could be limited to a small

subspecialty of medicine that concentrates on detoxification handled in medical

wards, emergency rooms, and outpatient medical clinics.

However, relapse (defined as resumption of substance abuse following a period of

abstinence) is the rule and not the exception in substance abusers entering or

completing treatment. Presentations in this volume and a large literature suggest

that a majority of those leaving a treatment program will relapse at least once

with greatest vulnerability to relapse in the first three months following

treatment (Hall, Hubbard, Maddux and Desmond, Simpson and Marsh, this

volume). Although successful efforts to curtail substance abuse may be more

frequent in untreated populations, as shown by the Viet Nam experience and

other reports (Robins 1980; Robins et al. 1974), clinicians are most concerned

with the comparatively poorer prognosis group who seek treatment.

In this chapter, the author will discuss material presented in previous chapters as

it relates to four issues: 1. commonalities and differences in relapse to different

substances of abuse; 2. promising directions for discriminating among groups of

patients to allow for better patient/program matching; 3. the need for more

research on the efficacy of different treatment strategies for relapse prevention;

and 4. relapse prevention strategies which are practicable within the kinds of

substance abuse treatment programs currently in place. The current state of

knowledge on factors related to relapse and its prevention raises more questions

than it answers. Hence, this chapter will be more heavily focused on possible

directions for future research than on immediate treatment implications.

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COMMONALITIES AND DIFFERENCES ACROSS DIFFERENT CLASSES OF

DRUGS

A theme across most chapters in this volume is the shared features of different

types of substance abuse. Regarding relapse, the most important shared feature

is the rate and speed of relapse to different substances. This is best illustrated

by the widely cited and reproduced graph by Hunt, Barnett and Branch (1971),

of relapse rates over 12 months following treatment, showing that smokers,

alcoholics, and heroin addicts are alike in having relapse rates of greater than 60

percent in the first year posttreatment and relapse rates of greater than 50

percent in the first three months. Most theories of drug abuse, including those

reviewed by Drs. Babor, Wesson and Grabowski (this volume), assume

commonalities in addiction and relapse to different substances, especially those

for which tolerance and withdrawal are prominent features. In addition, the data

presented by Dr. Hubbard from multiple substance abuse treatment programs

suggest that abuse of multiple drugs is the norm in those seeking treatment, and

relapse may take the form of resumption of abuse of the same substance or of

another substance, a finding which is consistent with much previous literature

(Green and Jaffe 1977; Simpson et al. 1979). Hence, in practice, substance

abusers appear to act as if there are important similarities in addiction and

relapse to different drugs.

Despite these widely recognized similarities across abused drugs, clinicians and

even self-help groups persist in physically and conceptually segregating the

treatment of those who abuse different classes of drugs. Thus, even if cross drug

similarities are important and recognized, many clinicians appear to believe that

dissimilarities across drugs are of sufficient importance to warrant the

development of independent treatment approaches. To translate theories of

relapse and research findings into improved treatment strategies, several

important cross-drug differences may need to be considered.

First, there are vast differences across drugs in the legality, social desirability,

availability, financial cost, medical consequences, and interaction of

pharmacological properties with ability to carry out productive work and family

life. Thus, for example, while smoking cigarettes and self-injecting heroin may

share underlying reinforcement principals and the propensity for relapse

following treatment. the “psychosocial” differences in the two addictions

profoundly affect the populations at risk and the circumstances leading to

treatment seeking. Cigarettes are comparatively inexpensive, legally obtained, do

not cause impairment in mental functioning during an intoxicated state, and

seldom lead to adverse social and occupational consequences, although the

medical consequences are profound. Conversely, heroin is illegal, expensive,

characterized in its effects by major fluctuations in mental state and mood

related to intoxication and withdrawal effects, and likely to be associated with

major legal, social, occupational, and medical consequences. Hence, cigarette

smokers seeking treatment come from all socioeconomic strata and are motivated

to curtail use by the desire to prevent or reduce physical consequences of their

habit. In contrast, heroin users are more frequently from disadvantaged segments

of the population, involved in illegal activities to support and obtain drugs, and

motivated to seek treatment because of serious social, occupational, or legal

pressure. These kinds of differences reduce the extent to which abusers of

different substances recognize a commonality with abusers of other substances.

Likewise, the treatment interventions aimed at maintaining abstinence and

preventing relapse for the different classes of drugs are likely to be greatly

affected by the differences in the populations involved. For example, the

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occupational and legal counseling needed by many treatment-seeking heroin

addicts is clearly irrelevant to the vast majority of those who need help with

stopping cigarette smoking. As another example, while a general cross-drug

principle in relapse prevention may be avoiding the situations in which use of

drugs is likely, these will be vastly different for heroin addicts, alcoholics, and

cigarette smokers.

The types of pharmacological strategies available for maintaining abstinence are

also greatly different across abused drugs. These include (a) maintenance on a

drug with similar agonist effects but pharmacological properties that reduce the

dysfunctional aspects of substance use, such as methadone maintenance or use of

nicotine chewing gum, (b) use of antagonists which reduce the positive

reinforcing properties of the substance if it is used after a period of abstinence,

and (c) use of substances, such as disulfiram, which lead to profound negative

reinforcement if the abused substance is used after a period of abstinence. While

the latter two types of pharmacological aids to maintaining abstinence have

appealed to only a relatively small minority of abusers of the relevant classes of

drugs (Green and Jaffe 1977), the maintenance approach has been the dominant

one for treatment of opioid addiction (Kosten and Kleber 1984). For no other

class of drugs has maintenance been a major treatment strategy, and this

difference results in major cross-drug dissimilarities in (a) the way that relapse is

defined, (b) the goals of treatment, and (c) the major parameters of treatment

such as its length, counseling strategies, etc. Thus, the definition of relapse is

fairly straightforward for drugs such as cocaine or cigarettes for which

abstinence appears to be the only acceptable outcome. In contrast, for opioid

addicts, continuation of powerful opioid use in the form of methadone is not

considered relapse as long as the client refrains from using illicit opioids. Hence,

the comparability of findings regarding predictors of relapse, efficacy of

treatment strategies, etc., is greatly limited when opioid addicts are considered.

To make cross-drug findings comparable, only those who are not maintained on

methadone can be utilized. To illustrate why this is necessary, one can consider

the issue of the impact of degree of dependence (Babor et al., this volume;

Edwards et al., in press) on relapse to different classes of drugs following a

period of abstinence while in treatment. While it may be predicted that those

with greater prior dependence might take a shorter time to relapse, this

prediction may not hold in a mixed group of heroin addicts who had entered

methadone maintenance or a drug-free program. For methadone maintenance,

those who were more severely dependent may be those most likely to stay in

treatment and thus to avoid relapse, while the converse would be most likely for

a drug-free program. Likewise, the option of drug maintenance as an approach

to treatment has profound effects on the goal of treatment and its desirable

duration. For opiate addicts, the ultimate goal of treatment may be abstinence

from all opiates. However, an intermediate goal for several years would be

maintenance on methadone while improving psychosocial functioning. For many

addicts, the goal of successfully curtailing methadone maintenance at any time is

believed to be unrealistic (Dole and Nyswander 1967). Alternatively, the goal of

treatment for other classes of drugs is either abstinence or, more controversially,

controlled use (Orford et al. 1976; Sobell and Sobell 1978). These fundamental

differences in goals of treatment necessitate great differences in the way that

abusers of different classes of drugs are encouraged to think about resolving their

drug use problem.

To sum up, while many underlying similarities can be noted across theories and

patterns of relapse to different classes of drugs, translating basic knowledge into

effective treatment strategies may need to be done separately for different classes

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of drugs. In some instances, the patterns of use are so similar across drugs that a

successful strategy for curtailing, for example alcoholism, can be readily

translated to cocaine abuse with minor modifications. However, whenever the

goal of treatment is not abstinence, relapse prevention strategies need to differ

greatly and comparison of followup research findings across drugs cannot be

made directly.

SOME ISSUES FOR CROSS-SUBSTANCE RESEARCH

Several of the chapters in this volume suggest the need for cross-drug research in

order to determine similarities and differences as they relate to potential

treatment strategies. For example, a major issue for the dependence construct

presented by Dr. Babor (this volume) is the degree to which behaviors

hypothesized as making up the dependence syndrome are found in drugs other

than alcohol. The dependence syndrome has important implications for the goals

and strategies of treatment because of its relationship to the issue of

multidimensionality of functioning and of controlled substance use as a goal of

treatment. According to the dependence construct, functioning of substance

abusers is multidimensional, so that severity of dependence is at least somewhat

independent of the social and occupational consequences of substance abuse.

Hence, improvement in one area, such as achieving abstinence, will not

necessarily lead to improvement in other areas. Conversely, failure to achieve

abstinence will not necessarily prevent attainment of treatment goals in other

areas. This emphasis goes against the strategies of medical model programs and

others, such as Alcoholics Anonymous, which emphasize abstinence as the major

goal which must be achieved before other issues are considered (Wesson et al.,

this volume). Another corollary of the dependence construct is that controlled

substance use may be an acceptable goal for those whose degree of dependence is

not high (Orford et al. 1976). This proposition has been highly controversial in

the treatment of alcoholism. If cross-drug studies show that the characteristics of

the dependence syndrome are similar across drugs and that severity of

dependence is related to relapse, this would add impetus to efforts to translate

successful treatment strategies developed with one substance to treatment of those

who abuse other substances, and increase the utility of multidimensional

outcomes and controlled use in treatment planning.

In developing innovative treatment strategies for preventing relapse to different

substances it would be desirable to have a paradigmatic substance, clients who

are comparatively amenable to participating in the research, a definition of

relapse which is clear and where treatment failure can be noted after a

comparatively brief interval. The several chapters in this volume pertaining to

cigarette smoking (Bigelow et al.; Brandon et al.; Hall and Havassy; Grabowski)

suggest that this type of substance dependence has these properties which may

make it a fruitful area in which to explore the determinants of relapse and to test

rapidly different approaches for preventing relapse. Because cigarettes are legal

and inexpensive enough to not be associated with financial strain to support the

habit, subjects are likely to be more cooperative and truthful about their

cigarette use. In defining relapse, there appears to be a powerful relationship

between smoking a single cigarette and resumption of compulsive use. Also,

abstinence is the usual treatment goal. Hence, relapse can be precisely measured.

In addition, the great majority of relapses appear to occur comparatively quickly

following completion of treatment, which is also comparatively brief. Hence, the

amount of time needed to complete paradigmatic studies is comparatively brief.

Because of these considerations, those who study treatment of cigarette smoking

are in a position to obtain more rapidly research results that could suggest

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promising directions to be taken by those working with other types of substance

abusers. However, as noted above, translation of strategies across drugs may

involve substantial modifications, and separate demonstration of treatment

efficacy of a given approach across drugs is needed.

DISCRIMINATING AMONG SUBSTANCE ABUSERS FOR PATIENT/

PROGRAM MATCHING

It is a truism that substance abusers are a heterogenous group, and this is

certainly true about their ability to avoid relapse, as a significant minority appear

to succeed with any given treatment effort. To increase the efficiency of

treatment efforts, there has been an upsurge of interest in defining subgroups of

patients who are likely to derive the greatest benefit from the different types of

treatments available. To provide an empirical basis for this patient/program

matching, investigators have long attempted to discover patient characteristics

that are associated with treatment success and failure in substance abusers

(Luborsky and McLellan 1978; Maddux and Desmond 1981; McLellan 1983;

Ogborne 1978; Szapocznik and Ladner 1977; Vaillant 1983). The most commonly

assessed predictors of outcome include clients’ demographic characteristics, drug

use history, and/or legal history. Reviews of the many such studies which have

been completed suggest that the help they provide to clinicians in matching

patients to programs is limited. Two trends characterize the results. First, most

studies tend to show the “rich get richer” phenomenon, with those clients with

the least severe symptoms or problems and the greatest social or psychological

assets tend to have the best prognosis. Second, the amount of variance accounted

for by patient predictors is generally modest, with any given predictor seldom

accounting for more than 5 to 10 percent of the variance in outcome.

The lack of clinical utility of most predictor studies is based on several factors.

First, many predictors which are studied have comparatively static traits or

characteristics. In general, the safest assumption in predicting the way clients

will perform is to assume that they will continue to do as they have in the past.

This general pattern was found in the study described by Dr. Taylor and

colleagues (this volume). However, the very thing which one is trying to predict

in treatment is change from current behavior, and measurement of past traits is

not necessarily a likely strategy for defining the propensity to change. Second,

many of the characteristics which have been evaluated as predictors are not

readily translatable to treatment strategies due to the static nature of the

predictors studied. For example, determining that black males with a long

criminal history have a poor prognosis does not suggest any particular clinical

response except, perhaps, to fret more over this group.

Several directions in prognostic research show promise toward yielding findings

which will be of greater utility to clinicians. First, the assessment of engagement

in treatment has the advantage of measuring the beginning of the change process

rather than some static trait that characterized past behavior. In the general field

of psychotherapy research, this concept has been captured in research on the

therapeutic alliance (Hartley 1985) which has yielded exciting and comparatively

powerful results. In the substance abuse field, findings in smoking programs

suggest that clients at the end of treatment are strongly able to predict their own

ability to maintain abstinence (Bigelow, Brandon, Hall, this volume). This

finding is consistent with the general concept that the clients’ engagement in

treatment or assessment of its success is a comparatively powerful index of the

change process. A second promising area is the assessment of psychopathology.

Using a global measure of severity of psychiatric problems, McLellan and

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associates have demonstrated that this variable is both strongly associated with

success in treatment of alcoholics and other substance abusers and that it is

useful as a guide to patient/program matching, as those with comparatively high

severity are most likely to benefit from professional psychotherapy (McLellan et

al., in press; Woody et al. 1984). Thus, this type of assessment has the advantage

of being associated with a treatment strategy designed to address the problem.

Similarly, depression, which has been shown to be responsive to psychological

and pharmacological treatments, has also been shown to be common in substance

abusers and related to poorer treatment outcome (Rounsaville et al. 1982a and b,

1985; Rounsaville et al., submitted), A third promising area for predictor studies

is the assessment of the posttreatment environment. Characteristics of the

posttreatment environment have been shown to be comparatively strongly related

to relapse (Maddux and Desmond 1982; O’Donnell 1969; Vaillant 1973) and are

more closely associated with treatment interventions, such as family therapy, that

may be used to enhance the supportiveness of this environment.

THE NEED FOR RESEARCH ON SPECIFICITY OF RESULTS FROM

DIFFERENT APPROACHES TO RELAPSE PREVENTION

In common with the literature on treatment approaches for other types of

disorders, treatment of substance use disorders is characterized by a wide variety

of techniques based, in part, on a bewilderingly diverse set of theoretical

propositions. A crucial task for treatment research at this time is to determine

the special properties of the different treatment approaches, either in the types

of effects yielded or in the types of clients for which they are most effective

(Parloff 1980). Because different types of treatment approaches involve different

expenses, length of time required, and different professional credentials of the

practitioners, evidence for differential efficacy across approaches is needed to

justify the effort and expense involved in maintaining this diversity.

For those who espouse a particular approach to treating substance abusers, the

crucial hypothesis to be ruled out is that effects of all treatment approaches are

due to some nonspecific common elements, such as counteracting demoralization

(Frank 1974; Klein and Rabkin 1984). In the general psychotherapy field, the

evidence suggesting the importance of nonspecific elements is extensive.

Reviews of the psychotherapy efficacy literature using meta-analysis have shown

that psychotherapy is usually found to be effective in contrast with comparison

conditions but that there is little evidence to date to suggest the greater efficacy

of any given approach (Smith et al. 1980). In the field of substance abuse

treatment, large-scale treatment followup studies such as those carried out by the

Texas Christian University group have shown that, while the results of drug

treatments are generally positive and related to being in treatment at least a

minimum length of time, the treatment outcomes for those receiving such diverse

programs as methadone maintenance, outpatient drug-free treatments, and

therapeutic communities were not statistically distinguishable (Simpson and Sells

1982). In a more focused, carefully controlled clinical trial evaluating the

efficacy of two very different forms of professional therapy as treatment of

clients on methadone maintenance, Woody and colleagues (1983) found that the

results of Supportive Expressive therapy (Luborsky 1984) and Cognitive Therapy

(Beck et al. 1979) were not significantly different, although both were superior to

the control condition.

Regarding the lack of specificity of effects from therapies based on different

theories of substance abuse, or of other types of psychopathology, it should be

noted that the empirical test of a theory-based therapy has no direct relationship

177
to testing the hypotheses of the theory. Therapies are always simultaneously

more and less than the theories on which they are based. All therapies include

elements, such as the therapists’ attempt to instill hope, that are not usually

specified or seen as crucial to the theory underlying more specific techniques

(Frank 1974; Klein and Rabkin 1984). In addition, most therapeutic maneuvers

can be seen as working through different mechanisms using different theoretical

conceptualizations of therapeutic change. For example, methadone maintenance

is seen as a treatment approach based on Dole and Nyswander’s substanceinduced metabolic deficit theory (Dole 1967) while it could as readily be seen by

a behavioral theorist as achieving its effect by blocking the positive

reinforcement yielded through intravenous heroin use. In addition to containing

elements which are not specified in the underlying theories, treatments never

include maneuvers which are relevant to all of the propositions suggested by the

theories. Because of these factors, evidence for the efficacy or lack of efficacy

of a theory is not relevant to supporting or refuting it. A faulty theory can

inspire an effective treatment as in the case of the development of lithium

treatment for mania (Cade 1949) and a correct theory can be translated into an

ineffective therapy. Hence, while the theories described in this volume may

inspire treatment interventions, testing the efficacy of theory-based treatment is

a separate process more directly relevant to clinical utility.

Determining the specific effects of a form of treatment is the second half of the

equation in the attempt to maximize the efficiency of patient/program matching.

The increased importance of research on patient/program matching is partially

caused by financial pressures to maximize the cost effectiveness of treatments

(Parloff 1982), but it is also related to advances in research methods to enable

investigators to assess specific effects of different treatments more precisely. In

the past 15 years, following the influential publication of guidelines suggested by

Fiske et al. (1970), research on the efficacy of psychotherapy has developed a set

of research standards which have allowed investigators to reduce the uncontrolled

variability which may have undermined previous efforts to detect specific

treatment effects (American Psychiatric Association Commission on

Psychotherapy 1982, Williams and Spitzer 1984). These design features include

the following: (a) use of credible control groups, which reduce the likelihood

that treatment effects of the therapies being studied are due to nonspecific

factors; (b) use of randomized treatment assignment, which reduces the likelihood

that differences in outcomes across treatments are due to differences in the types

of patients assigned to the treatments; (c) specified, homogenous patient groups,

which allow for better matching of treatment groups, greater specificity in the

treatment techniques utilized, and greater comparability in the measurement of

treatment outcome across patients; (d) specified lengths and “dosages” of

treatments, which have allowed comparability in the timing of outcome

measurements and in the determination of the amount of treatment received; (e)

improved methods for measuring outcome including use of reliable, standardized

instruments; measurement of outcome by blind, independent raters; use of

multiple outcome measures; use of multiple informants to measure outcome; and

use of outcome measures which are designed to detect the theoretically specific

effects of the different treatments being evaluated; (f) specification of the

psychotherapeutic techniques being compared in training manuals, which reduce

the variability in the delivery of treatments and reduce the overlap in the

treatments being compared; (g) greater specification and reduced variability in

the background of the therapists and of the specific training they have received

to conduct the therapy being tested; and (h) monitoring of the therapies being

contrasted to insure that the techniques are being practiced as described in

training manuals and to detect commonalities and differences in the therapies

178
being compared. While earlier psychotherapy efficacy studies have included

many of these elements, the project which utilizes all of the above features for

the first time is the NIMH Collaborative Study on the Treatment of Depression

(Elkin et al. 1985). This study compares four treatments for ambulatory patients

with Major Depression: (a) Cognitive Therapy (Beck et al. 1979); (b) Short Term

Interpersonal Psychotherapy; (c) Imipramine and Clinical Management; and (d)

Placebo and Clinical Management. This project breaks new ground in several

ways, and the results, which are due to be announced by the middle of 1986, will

be crucial for demonstrating the value of the methods listed above for detecting

specificity of different treatments for depression. If the treatments in this study

are shown to yield different types of results, this will suggest the value of

similarly designed studies of different treatments with other clinical groups, such

as substance abusers.

Carefully designed, controlled studies, with randomized assignment evaluating the

efficacy of different approaches to treatment of substance abusers are

comparatively rare (Desmond 1979; Rounsaville and Kleber 1985). Moreover, it

should be noted that most of the major modalities for treating substance abusers

today have not undergone efficacy testing of this sort. This includes such

widespread treatment packages as methadone maintenance, therapeutic

communities, and many outpatient drug-free approaches. Instead, these

treatment approaches became more widespread following promising uncontrolled

demonstration projects suggesting that the treatment had effects such as

treatment retention, which were clearly superior to those reported for other

approaches. Following the widespread use of these programs, followup studies

have suggested their efficacy (De Leon 1984; McLellan et al. 1982; Simpson and

Sells 1982). Although the research methods for evaluating efficacy of treatments

have been available for many years, there are several factors in performing

clinical trials with substance abusers which make this work difficult. First, the

urgency of the treatment needs of most substance abusers makes them and their

clinicians reluctant to participate in clinical trials, which include a theoretically

inert placebo or non-intensive control condition. Hence, as long as an active,

standard treatment is available as an alternative, recruitment is difficult. Second,

related to the treatment urgency, it has been difficult in treatment studies with

substance abusers to keep the treatment conditions distinct. In trials by Senay et

al. (1973) and Bales et al. (1980), clients who were assigned to different

treatments frequently obtained care in treatment conditions to which they were

not originally assigned. Third, because of the often heated controversy generated

by differences in treatment philosophy for proponents of different treatment

approaches (Davis 1970). clinicians espousing one or another of the established

approaches are often reluctant to allow clients to participate in studies which

include alternative methods.

Despite the difficulties described above, progress in developing and testing

improved methods for preventing relapse to substance abuse must take place

through a rational series of well-designed clinical trials using the features

described above. Once open trials and/or demonstration projects suggest the

value of new approaches, studies of two general types are needed to demonstrate

their unique properties. At one level, clinical trials are needed to suggest the

efficacy of a new treatment “package” such as a behavioral relapse prevention

approach (Marlatt and George 1984; Marlatt and Gordon 1980). At a second

level, studies are needed which aim at identifying the active ingredients of a

treatment package or conditions in which it is most effective. This can be

accomplished by offering the same general treatment approach to different

groups while varying a single crucial element such as time when the treatment is

179
offered or provision of a specific method for handling situations of high relapse

risk.

Several of the chapters in this volume suggest treatment comparisons which may

be fruitful. First, in Dr. Hall’s assessment of factors related to relapse to abuse

of three substances, she found that subjects who simply predicted that they

would not relapse were most likely to fulfill this prediction. This finding seems

to contrast with the theory and treatment approach of Marlatt and colleagues

(Marlatt and George 1984; Marlatt and Gordon 1980). which aims at helping the

subject recognize that a temporary resumption of drug use is likely. Clients are

encouraged to practice positive responses to this anticipated event. A systematic

comparison of approaches which emphasize anticipation of relapse with those

which simply rule out further use would be useful to determine if the specific

relapse anticipation is valuable. Second, several of the chapters suggest that

timing and duration of relapse prevention efforts are important elements. For

Dr. Bigelow’s study of a smoking prevention approach with myocardial infarction

patients, beginning the program before the use of the first cigarette proved

crucial (Bigelow et al., this volume). From the DARP and TOPS studies, the

findings on relapse suggest that the time of greatest vulnerability is shortly after

the cessation of treatment although vulnerability remains high throughout the

first posttreatment year and never disappears even after 12 years (Hubbard,

Simpson and Marsh). Regarding the efficacy of posttreatment relapse prevention

approaches, an important issue is the maximally cost effective duration of

posttreatment followup. If, for example, posttreatment followup efforts persist

beyond the first 6 months, does this yield any detectable added improvement in

relapse rates? Third, the longitudinal findings discussed by Drs. Maddux and

Simpson (this volume) suggest the importance for relapse prevention of a

supportive social environment following completion of treatment. Studies aimed

at evaluating approaches for enhancing the social network of substance abusers

after treatment may fruitfully compare such approaches as family psychotherapy,

provision of drop-in groups or centers, or provision of specific assistance while

in treatment in getting the client involved in self-help groups like Alcoholics

Anonymous, that can continue, following discharge from treatment.

CURRENTLY PRACTICABLE RELAPSE PREVENTION STRATEGIES

While a central conclusion of this chapter is that more careful research is needed

to develop and evaluate promising new strategies for reducing relapse to drug

abuse, this will be a long-term process, while the treatment needs of substance

abusers are immediate. The longitudinal findings presented in this volume

indicate that a substantial number of substance abusers will relapse following

treatment and much of this relapse will occur within the first year. A simplistic

response to these findings would be to extend treatment by 1 year. This response

is not likely to reduce relapse dramatically because many of those who relapse

following treatment were already beginning to resume drug use at the end of

their treatment and were not genuine program completers. Other problems with

simply extending the length of treatment include the added expense (especially

for those who need no further treatment) and the fact that attrition by those with

a high probability of relapse will take place even while they are offered

continuous treatment. Unless continuous treatment is to be considered a lifelong

answer for substance abusers, they need to be prepared to manage without it.

Five steps could be considered by programs at this time suggested by findings

presented in this volume. This list of strategies is not intended to be exhaustive

and a review of aftercare approaches is provided by Hawkins and Catalano (in

press).

180
A first, basic step in preventing relapse is making a recognition of its likelihood

a focus of the treatment program. At minimum this should involve explicit

policies regarding reentry into treatment when relapse occurs. Preferably, the

procedures for reentering treatment following a brief relapse should be facilitated

so that the client is encouraged to seek help early and before resumption of

substance abuse has become entrenched. These could include encouraging clients

to telephone their counselors if a slip occurs even if they are no longer on the

treatment program.

A second step which is likely to reduce relapse would be the inclusion of

interventions in treatment specifically designed to anticipate relapse. This could

include the kind of training for constructive responses described by Marlatt

(1980, 1984) and it could usefully include family members who could be trained

to recognize early signs of relapse and encouraged to place pressure on the

relapsing family member to re-enter treatment.

A third step would take the strategy of using the time in treatment to enhance

the supportiveness of the posttreatment environment. One relatively simple and

inexpensive intervention of this type would be to make efforts to encourage

clients to become engaged in self-help groups while they are also in treatment.

Counselors could accompany clients to self-help group meetings and make

explanatory literature available. Fellow clients who are farther along in

treatment could be encouraged to accompany new clients to self-help group

meetings. Spouses and family members of clients could be encouraged to get

involved in self-help spouse groups, such as Al Anon. A more staff-intensive

intervention would be to involve families or significant others of all clients in

treatment and to engage these members of the social network in relapse

prevention strategies as well as traditional family therapy.

A fourth step would be to develop aftercare programs which offer continued

contact with the client but at a much less intensive level than regular treatment.

Because the majority of relapse will occur during the first year following

treatment, this length of time would probably be optimal for these kinds of

efforts. Aftercare programs could take the form of monthly telephone calls by

counselors to check up on how the client is progressing; regular therapy meetings,

but on a much less frequent basis; or “drop-in” groups which meet weekly at a

specific time and which are open to any former clients who wish to attend. Such

aftercare efforts would necessarily involve considerable additional staff time and

this would need to be taken into account in fees collected from clients or funding

agencies while the clients are in the full treatment program.

A final step would be to make interventions while in treatment that take into

account the likelihood of drug substitution as a form of relapse. Segregation of

treatment programs for abusers of different drugs is the most common strategy,

and this may ignore drug abuse that is not seen by the client as primary but

which may increase in importance when the major type of drug abuse is

curtailed, as shown in Dr. Hubbard’s chapter (this volume). Addressing

additional drugs of abuse could take the form of engaging the client in multiple

treatment programs or forming subcomponents within a treatment program, such

as an alcoholics’ group that is run within a methadone maintenance program.

181
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ACKNOWLEDGMENT

Support for this work was provided by a Research Career Scientist Development

Award #K02 DA00089-01 from the National Institute of Drug Abuse.

AUTHORS

Bruce J. Rounsaville, M.D.

Associate Professor of Psychiatry

Yale University School of Medicine

333 Cedar Street

New Haven, Connecticut 06510

Director of Research

Substance Abuse Treatment Unit

Connecticut Mental Health Center

34 Park Street

New Haven, Connecticut 06511

Director of Research

Addiction Prevention and

Treatment Foundation

98 Park Street

New Haven, Connecticut 06511

184
Relapse and Recovery:

Some Directions for Research

and Practice

Carl G. Leukefeld and Frank M. Tims

The addictions treatment field is maturing. Studies can now be

cited which indicate that drug abuse treatments are effective and

produce desired behavioral change (Tims 1981). But these studies

also point to a high rate of relapse. Indeed, they tend to support

the concept of addiction as a "chronic relapsing disease." Growing

out of these studies are other findings showing that differential

prognoses appear to be a function of such variables as time in

treatment, commitment to seek change, and associated kinds (and

severity) of psychopathology. There are also abundant data showing

that drug abusers commonly experience multiple treatments. Given

these and related findings, a major problem confronting treatment

is the bringing about and maintenance of positive behavioral

change--preventing relapse. As is pointed out in several chapters

of this volume (e.g., Hubbard and Marsden; Taylor et al.),

consideration of relapse from either theoretical or clinical

practice perspectives encounters both philosophical and theoretical

dilemmas. What is the clinical significance of reverting to

"controlled" use or a shift to a substance not thought to be as

pernicious as the one(s) for which treatment was provided? At what

point is relapse considered to have occurred?

There has been more limited exploration of recovery. Recovery is a

desired end in which drug abuse and related behavior are no longer

problematic in the individual's life. In the Alcoholics Anonymous

model, an alcoholic never actually recovers, and is always at risk

for relapse. The debate over who recovers is a continuing one.

The few studies of untreated or "natural" recoveries (e.g., Waldorf

1983) suffer from major limitations, notably, unknown sampling

bias, and consequently, non-generalizability to the untreated drug

abuser. Some recent research indicates that a significant

percentage of treated addicts have relatively short addiction

careers (Simpson and Marsh, this volume). A major issue is the

definition of recovery. Some researchers and clinicians define

recovery as total abstinence, whereas others accept some limited

substance use. A similar question may be posed with regard to the

definition of relapse. Rigid criteria may be problematic to both

researcher and clinician, while a more permissive standard is

185
fraught with clinical risk (i.e., that permitted use of a less

pernicious drug may undermine the client's commitment to abstinence

in any of several ways -- such as triggering craving for other

drugs, lapses in self-control, and violation of an abstinence

norm). A single use of a given substance may be the first step to

loss of control, simply a slip from the path of recovery, or it may

have another, more specialized meaning of relapse (e.g., Duckitt et

al. 1985; Marlatt and George 1984).

This volume does not resolve the specific definitional questions

relating to relapse and recovery, but rather explores issues and

approaches to conceptual refinement, research directions, and

pragmatic questions for clinicians in these areas. The principal

thrust of the meeting on which this monograph is based considered

opiates, alcohol, and tobacco as the three substances across which

commonalities in relapse to use and recovery from dependence might

be usefully studied. Indeed, examination of the arguments for the

utility of this approach (National Academy of Sciences 1981)

suggested that it might yield valuable insights, and this has been

our experience. From practice, as well as from the observations of

researchers (see Hubbard and Marsden, this volume), it is evident

that multiple, chronic dependence is not unusual. This has been a

dilemma for methadone programs which give attention to heroin

addiction in a treatment population where alcoholism, smoking, and

abuse of other drugs is widespread. Should treatment be directed

toward one drug while ignoring others, or should the clinic staff

make demands on the client that other problematic substances, some

of which may be legal (e.g., alcohol, tobacco), also be given up?

This sort of question has numerous implications for both treatment

research and practice.

Before presenting the following specific recommendations for

practice and research, it is important to indicate that there was a

high degree of agreement, based on discussions regarding both

research and practice considerations, by the participants. In

fact, general merging toward total consensus might be a more

appropriate description. The extent of that consensus was

unexpected. Clearly, the following recommendations for research

and practice will overlap, and the separation here into three

sections focused on theory, research, and practice, is not intended

to detract from, but to enhance conceptual clarity. We hope this

volume focuses additional attention on relapse and recovery.

Alcoholics Anonymous, Narcotics Anonymous, and other groups which

have been labeled as self-help groups, have provided the supports

necessary for sustaining the recovering person. However, there are

clear definitional discrepancies regarding relapse when studies are

reviewed, including those in this volume.

Relapse and recovery have been defined in many ways. There was not

an attempt made here to standardize the definition of relapse or

recovery. Rather, these concepts are viewed as related phenomena

which are important for our better understanding of addiction and

practice interventions.

186
CONSIDERATIONS FOR THEORY: THEMES TO APPROACH THEORY AND THEORY

DEVELOPMENT

Numerous theoretical positions have been taken to explain relapse.

Yet, a coherent, integrated theory is lacking. Discussion related

to theory and theory development acknowledged the importance of

theory as a guide to research and practice, but the lack of

explanatory power in existing theory, and the lack of theoretical

organization, was repeatedly cited as cause for concern. For

example, it was noted that Lettieri et al. (1980) have identified

over 43 theories to explain drug abuse.

That aside, an overall theory as suggested by Edwards et al.

(1981), which combines cognitive, physiological, and behavioral

components, is important for developing a broad conceptualization

of relapse and recovery. In addition, a theory of relapse and

recovery should explain a variety of related phenomena. Specific

criteria need to be explicated so that they can be used to evaluate

theory--proven or disproven. Clearly, theories must be judged on

specific criteria which include utility and their ability to direct

research in a meaningful, parsimonious fashion. Moreover, theories

should help generate principles and techniques for clinical

practice, and should benefit from insight derived from practice.

Such interplay between theoretical formulation and clinical

experience is generally lacking.

A related question to consider when alcohol, tobacco, and drugs are

taken into account is the specificity of the behavioral disorder.

Current research and practice trends are focusing on specificity

and individual drugs, rather than the suggested focus on examining

relapse from a more general perspective.

IMPLICATIONS FOR RELAPSE AND RECOVERY RESEARCH

Overall, a great deal needs to be done in this area of research.

There are research opportunities which can lead to better

understanding of relapse and recovery. Specific discussion focused

on two broad areas: (1) Design issues related to planning relapse

and recovery studies, and (2) research implementation strategies.

As a beginning point and a carryover from discussions related to

theory, research definitions should relate to theory. It was

suggested that cognitive behavioral theories may have particular

utility for relapse and recovery. Ideally, it would be appropriate

to design prospective studies which examine relapse and recovery,

although use of available study populations may make it necessary

to approach studies retrospectively. It was suggested that

existing data bases such as TOPS and DARP might serve as a

beginning to examine relapse and recovery within retrospective

analyses. Five general types of studies were suggested to more

closely examine relapse and recovery:

1. Longitudinal studies which clarify the natural history of

addiction careers. Such studies would be designed to

allow researchers to examine more closely relapse and

recovery.

187
2. Descriptive studies to pinpoint who relapses. These

studies would provide a clearer understanding of sex, age,

and drug type variables as these variables impact on

relapse. Similarly, studies of individuals in recovery

might provide a clearer picture and description of

recovery processes.

3. Laboratory studies to examine physiological factors. Such

studies would provide further insight into the nature of

factors related to the clinical aspects of relapse and

recovery. Limited information is currently available

regarding the physiological aspects of those recovering.

4. Experimental studies to assess behavioral aspects of

relapse, particularly the role of environmental stimuli,

including both treatment and non-treatment factors. Such

studies should enable understanding of the role of

treatment as well as other variables in relapse processes

for well-defined subgroups of clients.

5. Clinical studies which would clarify the role of

psychopathology as a risk factor in relapse. This would

extend already existing findings on psychopathology as a

prognostic variable, and specify how subgroups of clients

respond to treatment and to the other stimuli present in

the natural environment, as well as how changes in

psychopathology moderate risk of relapse. In this

connection, it is important to assess clients on a

continuing basis at intake. during treatment, and during

the posttreatment period. Such studies might also address

familial characterlstlcs, as well as individual

psychopathology, as predisposing factors.

It was also suggested that treatment evaluations be designed to

incorporate relapse and recovery as an a priori focus. Such

treatment evaluations should include: (1) theoretical and

operational definitions of relapse and recovery, (2) credible

control group(s), (3) random assignment of groups to treatments,

(4) well-defined patient groups, (5) standardized treatments which

are adequately described in manuals, (6) specified treatment

lengths and treatment doses as well as assurance that interventions

are delivered, (7) use of consistent, reliable and valid outcome

measures, and (8) specific therapist characteristics and training.

The second broad area of discussion focused on research

implementation strategies which address specific problems. focus

shifted to specific areas and problems which mlght have high payoff

or should receive specific attentlon for the study of relapse and

recovery. The major impression gained from thls discussion was the

limited amount of information available on recovery. In the drug

abuse area, self-help groups based upon research findings are being

initiated as aftercare services (see McAuliffe. this volume) to

prevent relapse and enhance client recovery.

188
IMPLICATIONS FOR PRACTICE: RELAPSE AND RECOVERY

The overriding implication for practitioners, based on discussion

from this review, is that factors associated with relapse need to

be explicitly identified and become part of the treatment process.

That emphasis could decrease relapse and enhance recovery. A

better understanding of patient motivation and decision-making

should also be a significant part of treatment. Likewise,

understanding the timing of interventions could make an important

contribution to recovery.

Since a number of individuals start using substances immediately

following their departure from treatment, treatment could be

designed so that patients do not drift away from treatment

facilities. Formal procedures for discharging patients with

specified treatment protocols could go a long way toward decreasing

patient drift. Treatment contracts with individual patients might

form the foundation of reducing relapse.

The practitioner's role involves not only bringing about positive

behavioral change and cessation of drug use, but also maintaining

that change and preventing relapse. The development of a better

understanding on the part of practitioners and clients regarding

the risk of relapse, and the desirability of maintaining the gains

they have made, are important. Equally important is the

understanding of the relapse process itself so that appropriate

strategies and support systems may be devised and implemented.

This approach calls for skill development in self-regulation on the

part of the client while recognizing indications of increasing

risk. Thus, clinicians must explicitly deal with relapse as part

of the treatment process and treatment protocol. Perhaps the most

powerful determinant of relapse is the individual's (lack of)

commitment to abstinence. Careful consideration should be given to

formulatlng strategies for helping the client develop such a

commitment to abstinence. At the most basic level, commitment to

change should be incorporated into the treatment process from the

outset. It seems that identified and individualized factors

associated with relapse could also be incorporated with treatment

to decrease relapse. Practitioners must also realistically deal

with limited motivation or commitment by individuals to engage in

the treatment process. It was suggested that this emphasis might

also become part of treatment at the outset. Many users have a low

tolerance for stress and find it easy to return to use rather than

deal with stressors. Based on these discussions, the ability to

cope with distress was identified as an important component of

Alcoholics Anonymous and other self-help models.

Based upon information currently available, the first three months

of treatment are probably the most critical for relapse, as is the .

first year of treatment. With this in mind, clinicians should make

aftercare contacts at the:

first week after treatment

first month after treatment

third month after treatment

first year after treatment

189
It was suggested that individualized contact would be most

effective and that telephone contact would be acceptable, although

outreach/aftercare workers might be a more effective approach.

Given the constraints on available resources, insight therapy

should be limited. Rather, encouragement, support, containment,

and direct intervention, as well as confrontation, should be used

in clinical settings. In fact, there may be need for external

treatment controls or coercive approaches for alcohol and drug

abusers to decrease relapse rates. Such approaches as Bigelow's

crisis intervention model (this volume) which was developed with

nicotine dependent, myocardial infarction patients, may be quite

useful in developing strategies for reducing drug use and examining

relapse. While Bigelow's study dealt with a specialized treatment

population, it underscores the utility of exploring critical life

events and concerns of clients, and making timely interventions to

crystallize whatever potential commitment to abstinence may be

present.

REFERENCES

Duckitt. A.; Brown, D.; Edwards, G.; Oppenheimer, E.; Sheehan,

M.; and Taylor, C. Alcoholism and the nature of outcome.

Br J Addict 80:153-162, 1985.

Edwards, G.A.; Arif, A.; and Hodgson, R., "Nomenclature and

Classification of Drugs and Alcohol-Related Problems:

A WHO Memorandum." Bulletin of the World Health Organization,

59:225-242, 1981.

Lettieri, D.J.; Sayers, M.; and Pearson, H.W., eds. Theories

on Drug Abuse: Selected Contemporary Perspectives. National

Institute on Drug Abuse Research Monograph No. 30. DHHS Pub.

No. (ADM) 84-967. Washington, D.C.: Supt. of Docs., U.S.

Govt. Print. Off., 1980.

Marlatt, G.A., and George, W.H., Relapse prevention: Introduction and overview of the model, Br J Addict 79:261-273,

1984.

National Academy of Sciences, Guidelines for Studies in Substance

Abuse Treatment, Washington, D.C.: Academic Press, 1981.

Tims, F.M., Effectiveness of Drug Abuse Treatment Programs.

DHHS Pub. No. (ADM) 84-1143. National Institute On Drug

Abuse. Rockville, Md.: the Institute, 1981.

Waldorf, D. Natural recovery from opiate addiction: Some socialpsychological processes of untreated recovery. J Drug Issues

13(2):237-280, 1983.

AUTHORS

Carl G. Leukefeld. D.S.W.

Frank M. Tims, Ph.D.

National Institute on Drug Abuse

5600 Fishers Lane

Rockville. Maryland 20857

190
monograph series

While limited supplies last, single copies of the monographs may be

obtained free of charge from the National Clearinghouse for Alcohol

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For information on availability of NIDA Research Monographs 1-24

(1975-1979) and others not listed, write to NIDA Office for Research

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25 BEHAVIORAL ANALYSIS AND TREATMENT OF SUBSTANCE ABUSE. Norman A.

Krasnegor, Ph.D., ed. NCADI out of stock

GPO out of stock NTIS PB #80-112428 $24.95

26 THE BEHAVIORAL ASPECTS OF SMOKING. Norman A. Krasnegor, Ph.D.,

ed. (Reprint from 1979 Surgeon General's Report on Smoking and

Health.)

GPO out of stock NTIS PB #80-118755 $18.95

30 THEORIES ON DRUG ABUSE: SELECTED CONTEMPORARY PERSPECTIVES. Dan

J. Lettieri, Ph.D.; Mollie Sayers; and Helen W. Pearson, eds.

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Not available from NTIS

191
31 MARIJUANA RESEARCH FINDINGS: 1980. Robert C. Petersen, Ph.D., ed.

GPO out of stock NTIS PB #80-215171 $24.95

32 GC/MS ASSAYS FOR ABUSED DRUGS IN BODY FLUIDS. Rodger L. Foltz,

Ph.D.; Allison F. Fentiman, Jr., Ph.D.; and Ruth B. Foltz.

GPO out of stock NTIS PB #81-133746 $24.95

36 NEW APPROACHES TO TREATMENT OF CHRONIC PAIN: A REVIEW OF

MULTIDISCIPLINARY PAIN CLINICS AND PAIN CENTERS. Lorenz K.Y.

Ng, M.D., ed.

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37 BEHAVIORAL PHARMACOLOGY OF HUMAN DRUG DEPENDENCE. Travis

Thompson, Ph.D., and Chris E. Johanson, Ph.D.. eds.

NCADI out of stock

GPO out of stock NTIS PB #82-136961 $30.95

38 DRUG ABUSE AND THE AMERICAN ADOLESCENT. Dan J. Lettieri, Ph.D.,

and Jacqueline P. Ludford. M.S., eds. A RAUS Review Report.

GPO out of stock NCADI out of stock

NTIS PB #82-148198 $18.95

40 ADOLESCENT MARIJUANA ABUSERS AND THEIR FAMILIES. Herbert

Hendin, M.D., Ann Polllnger, Ph.D., Richard Ulman, Ph.D., and

Arthur Carr, Ph.D. NCADI out of stock

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42 THE ANALYSIS OF CANNABINOIDS IN BIOLOGICAL FLUIDS. Richard L.

Hawks, Ph.D., ed.

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44 MARIJUANA EFFECTS ON THE ENDOCRINE AND REPRODUCTIVE SYSTEMS.

Monique C. Braude, Ph.D., and Jacqueline P. Ludford, M.S.. eds. A

RAUS Review Report. NCADI out of stock

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45 CONTEMPORARY RESEARCH IN PAIN AND ANALGESIA, 1983. Roger M.

Brown, Ph.D .; Theodore M. Pinkert, M.D., J.D.; and Jacqueline P.

Ludford, M.S., eds. A RAUS Review Report. NCADI out of stock

GPO out of stock NTIS PB #84-184670/AS $13.95

46 BEHAVIORAL INTERVENTION TECHNIQUES IN DRUG ABUSE TREATMENT. John

Grabowski, Ph.D .; Maxine L. Stitzer, Ph.D., and Jack E.

Henningfield, Ph.D., eds. NCADI out of stock

GPO out of stock NTIS PB #84-184688/AS $18.95

47 PREVENTING ADOLESCENT DRUG ABUSE: INTERVENTION STRATEGIES.

Thomas J. Glynn, Ph.D .; Carl G. Leukefeld, D.S.W.; and

Jacqueline P. Ludford, M.S., eds. A RAUS Review Report.

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192
48 MEASUREMENT IN THE ANALYSIS AND TREATMENT OF SMOKING BEHAVIOR.

John Grabowski, Ph.D., and Catherine S. Bell, M.S., eds.

GPO Stock #017-024-01181-9 $4.50 NCADI out of stock

NTIS PB #84-145184/AS $18.95

50 COCAINE: PHARMACOLOGY, EFFECTS, AND TREATMENT OF ABUSE. John

Grabowski, Ph.D., ed.

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51 DRUG ABUSE TREATMENT EVALUATION: STRATEGIES, PROGRESS, AND

PROSPECTS. Frank M. Tims, Ph.D., ed.

GPO Stock #017-024-01218-1 $4.50 NTIS PB #85-150365/AS $18.95

52 TESTING DRUGS FOR PHYSICAL DEPENDENCE POTENTIAL AND ABUSE

LIABILITY. Joseph V. Brady, Ph.D., and Scott E. Lukas, Ph.D., eds.

GPO Stock #017-024-01204-1 $4.25 NTIS PB #85-150373/AS $18.95

53 PHARMACOLOGICAL ADJUNCTS IN SMOKING CESSATION. John Grabowski,

Ph.D., and Sharon M. Hall, Ph.D., eds.

GPO Stock #017-024-01266-1 $3.50 NCADI out of stock

54 MECHANISMS OF TOLERANCE AND DEPENDENCE. Charles Wm. Sharp,

Ph.D., ed.

GPO out of stock

56 ETIOLOGY OF DRUG ABUSE: IMPLICATIONS FOR PREVENTION. Coryl LaRue

Jones, Ph.D., and Robert J. Battjes, D.S.W., eds.

GPO Stock #017-024-01250-5 $6.50

57 SELF-REPORT METHODS OF ESTIMATING DRUG USE: MEETING CURRENT

CHALLENGES TO VALIDITY. Beatrice A. Rouse, Ph.D., Nicholas J.

Kozel, M.S., and Louise G. Richards, Ph.D., eds.

GPO Stock #017-024-01246-7 $4.25

58 PROGRESS IN THE DEVELOPMENT OF COST-EFFECTIVE TREATMENT FOR DRUG

ABUSERS. Rebecca S. Ashery, D.S.W., ed.

GPO Stock #017-024-01247-5 $4.25

59 CURRENT RESEARCH ON THE CONSEQUENCES OF MATERNAL DRUG ABUSE.

Theodore M. Pinkert, M.D., J.D., ed.

GPO Stock #017-024-01249-1 $2.50

60 PRENATAL DRUG EXPOSURE: KINETICS AND DYNAMICS. C. Nora Chiang,

Ph.D., and Charles C. Lee, Ph.D., eds.

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61 COCAINE USE IN AMERICA: EPIDEMIOLOGIC AND CLINICAL PERSPECTIVES.

Nicholas J. Kozel, M.S., and Edgar H. Adams, M.S., eds.

GPO Stock #017-024-01258-1 $5

62 NEUROSCIENCE METHODS IN DRUG ABUSE RESEARCH. Roger M. Brown,

Ph.D., and David P. Friedman, Ph.D., eds.

GPO Stock #017-024-01260-2 $3.50

193
63 PREVENTION RESEARCH: DETERRING DRUG ABUSE AMONG CHILDREN AND

ADOLESCENTS. Catherine S. Bell, M.S., and Robert J. Battjes,

D.S.W.. eds.

GPO Stock #017-024-01263-7 $5.50

64 PHENCYCLIDINE: AN UPDATE. Doris H. Clouet, Ph.D., ed.

GPO Stock #017-024-01281-5 $6.50

65 WOMEN AND DRUGS: A NEW ERA FOR RESEARCH. Barbara A. Ray, Ph.D.,

and Monique C. Braude, Ph.D., eds.

GPO Stock #017-024-01283-1 $3.25

66 GENETIC AND BIOLOGICAL MARKERS IN DRUG ABUSE AND ALCOHOLISM.

Monique C. Braude, Ph.D., and Helen M. Chao, Ph.D. eds.

GPO Stock #017-024-01291-2 $3.50 NCADI out of stock

68 STRATEGIES FOR RESEARCH ON THE INTERACTIONS OF DRUGS OF ABUSE.

Monique C. Braude, Ph.D., and Harold M. Ginzburg, M.D., J.D., M.P.H..

eds.

GPO Stock #017-024-01296-3 $6.50

69 OPIOID PEPTIDES: MEDICINAL CHEMISTRY. Rao S. Rapaka, Ph.D.;

Gene Barnett. Ph.D .; and Richard L. Hawks, Ph.D., eds.

GPO Stock #017-024-1297-1 $11

70 OPIOID PEPTIDES: MOLECULAR PHARMACOLOGY, BIOSYNTHESIS, AND

ANALYSIS. Rao S. Rapaka, Ph.D., and Richard L. Hawks, Ph.D., eds.

GPO Stock #017-024-1298-O $12

71 OPIATE RECEPTOR SUBTYPES AND BRAIN FUNCTION. Roger M. Brown,

Ph.D.; Doris H. Clouet, Ph.D.; and David P. Friedman, Ph.D., eds.

GPO Stock #017-024-01303-O $6

72 RELAPSE AND RECOVERY IN DRUG ABUSE. Frank M. Tims, Ph.D., and

Carl G. Leukefeld, D.S.W., eds.

GPO Stock #017-024-01302-1 $6

73 URINE TESTING FOR DRUGS OF ABUSE. Richard L. Hawks, Ph.D., and

C. Nora Chiang, Ph.D., eds.

GPO Stock #017-024-1313-7 $3.75

74 NEUROBIOLOGY OF BEHAVIORAL CONTROL IN DRUG ABUSE. Stephen I.

Szara, M.D., D.Sc., ed.

GPO Stock #017-024-1314-5 $3.75

75 PROGRESS IN OPIOID RESEARCH. PROCEEDINGS OF THE 1986 INTERNATIONAL NARCOTICS RESEARCH CONFERENCE. John W. Holaday, Ph.D.;

Ping-Yee Law, Ph.D .; and Albert Herz, M.D., eds.

GPO Stock #017-024-01315-3 $21

76 PROBLEMS OF DRUG DEPENDENCE, 1986. PROCEEDINGS OF THE 48TH

ANNUAL SCIENTIFIC MEETING, THE COMMITTEE ON PROBLEMS OF DRUG

DEPENDENCE, INC. Louis S. Harris, Ph.D., ed.

GPO Stock #017-024-1316-1 $16 NTIS PB #88-208111/AS $44.95

194
77 ADOLESCENT DRUG ABUSE: ANALYSES OF TREATMENT RESEARCH.

Elizabeth R. Rahdert, Ph.D., and John Grabowski, Ph.D., eds.

GPO Stock #017-024-1348-O $4

78 THE ROLE OF NEUROPLASTICITY IN THE RESPONSE TO DRUGS

David P. Friedman, Ph.D., and Doris H. Clouet, Ph.D., eds.

GPO Stock #017-024-01330-7 $6

79 STRUCTURE-ACTIVITY RELATIONSHIPS OF THE CANNABINOIDS

Rao S. Rapaka, Ph.D., and Alexandros Makriyannis, Ph.D., eds.

GPO Stock #017-024-01331-5 $6

80 NEEDLE-SHARING AMONG INTRAVENOUS DRUG ABUSERS: NATIONAL AND

INTERNATIONAL PERSPECTIVES. Robert J. Battjes, D.S.W., and Roy W.

Pickens, Ph.D., eds.

GPO Stock #017-024-01345-5 $5.50 NTIS PB #88-236138/AS $25.95

81 PROBLEMS OF DRUG DEPENDENCE, 1987. PROCEEDINGS OF THE 49TH

ANNUAL SCIENTIFIC MEETING, THE COMMITTEE ON PROBLEMS OF DRUG

DEPENDENCE, INC. Louis S. Harris, Ph.D., ed.

GPO Stock #017-024-01354-4 $17

82 OPIOIDS IN THE HIPPOCAMPUS. Jacqueline F. McGinty, Ph.D., and

David P. Friedman, Ph.D. eds.

GPO Stock #017-024-01344-7 $4.25

83 HEALTH HAZARDS OF NITRITE INHALANTS. Harry W. Haverkos, M.D.,

and John A. Dougherty, Ph.D., eds.

GPO Stock #017-024-01351-O $3.25

84 LEARNING FACTORS IN SUBSTANCE ABUSE. Barbara A. Ray, Ph.D., ed.

GPO Stock #017-024-01353-6 $6

86 COMPULSORY TREATMENT OF DRUG ABUSE: RESEARCH AND CLINICAL

PRACTICE. Carl G. Leukefeld, D.S.W., and Frank M. Tims, Ph.D., eds.

GPO Stock #017-024-01352-8 $7.50

IN PRESS

85 EPIDEMIOLOGY OF INHALANT ABUSE: AN UPDATE. Raquel A. Crider,

Ph.D., and Beatrice A. Rouse, Ph.D., eds.

88 MECHANISMS OF COCAINE ABUSE AND TOXICITY. Doris H. Clouet,

Ph.D., Khursheed Asghar, Ph.D., and Roger M. Brown, Ph.D., eds.

89 BIOLOGICAL VULNERABILITY TO DRUG ABUSE. Roy W. Pickens, Ph.D.,

and Dace S. Svikis, B.A., eds.

* U.S. GOVERNMENT PRINTING OFFICE: 1990 - 261 - 217/ 24829

195
DHHS Publication No. (ADM)90-1473

Alcohol, Drug Abuse, and Mental Health Administration

Printed 1986, Reprinted 1988, 1990