Adolescent

Drug Abuse:

Analyses of

Treatment Research

U.S. DEPARMENT OF HEALTH AND HUMAN SERVICES • Public Health Service • National Institutes of Health
Adolescent Drug Abuse:

Analyses of Treatment

Research

Editors:

Elizabeth R. Rahdert, Ph.D.

Division of Clinical Research

National Institute on Drug Abuse

John Grabowski, Ph.D.

Department of Psychiatry and Behavioral Sciences

University of Texas Health Science Center

NIDA Research Monograph 77

1988

U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES

Public Health Service

National Institutes of Health

National Institute on Drug Abuse

5600 Fishers Lane

Rockville, Maryland 20857

For sale by the Superintendent of Documents, 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

dissemination to the scientific and professional community.

Editorial Advisors

MARTIN W. ADLER, Ph.D.

Temple University School of Medicine

Philadelphia, Pennsylvania

SYDNEY ARCHER, Ph.D.

Rensselaer Polytechnic lnstitute

Troy, New York

RICHARD E. BELLEVILLE, Ph.D.

NB Associates, Health Sciences

Rockville, 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 Unversity School of

Medicine

Baltimore, Maryland

THEODORE J. CICERO, Ph.D.

Washington University School of

Medicine

St Louis, Missouri

MARY L. JACOBSON

National Federation of Parents for

Drug-Free Youth

Omaha, Nebraska

REESE T. JONES, M.D.

Langley Porter Neuropsychiatric lnstitute

San Francisco, California

DENISE KANDEL, Ph.D.

College of Physicians and Surgeons of

Columbia University

New York, New York

HERBERT KLEBER. M.D.

Yale University School of Medicine

New Haven, Connecticut

RICHARD RUSSO

New Jersey State Department of Health

Trenton, New Jersey

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
Adolescent Drug Abuse:

Analyses of Treatment

Research
ACKNOWLEDGMENT

This monograph is based upon papers presented at a technical review

on analyses of research concerning treatment of adolescent drug

abusers which took place on November 6 - 7, 1985, at Bethesda,

Maryland. The review meeting was sponsored by the Office of Science

and the Division of Clinical Research, National Institute on Drug

Abuse. At the time of the review, Dr. John Grabowski, coeditor of

the monograph, was chief of the Treatment Research Branch, Division

of Clinical Research. He is currently affiliated with the

University of Texas Health Science Center.

COPYRIGHT STATUS

The National Institute on Drug Abuse has obtained permission from

the copyright holders to reproduce certain previously published

figures and tables, as noted in the text. Further reproduction of

the copyrighted material is permitted only as part of a reprinting

of the entire publication or chapter. For any other use, the

copyright holder's permission is required. All other material in

this volume except quoted passages from copyrighted sources is in

the public domain and may be used or reproduced without permission

from the Institute or the authors. Citation of the source is

appreciated.

National Institute on Drug Abuse

NIH Publication No. 94-3712

Formerly DHHS Publication No. (ADM) 88-1523

Printed 1988 Reprinted 1994

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
Contents

Treatment Services for Adolescent Drug Abusers:

Introduction and Overview

Elizabeth R. Rahdert . . . . . . . . . . . . . . . . . . . . 1

Assessing Adolescents Who Abuse Chemicals: The Chemical

Dependency Adolescent Assessment Project

Ken C. Winters and George Henley . . . . . . . . . . . . . . . 4

Substance Abuse in Adolescents: Diagnostic Issues Derived From

Studies of Attention Deficit Disorder With Hyperactivity

Jan Loney . . . . . . . . . . . . . . . . . . . . . . . . . 19

Empirical Guidelines for Optimal Client-Treatment Matching

Reid K. Hester and William R. Miller . . . . . . . . . .

Family-Based Approaches to Reducing Adolescent Substance Use:

Theories, Techniques, and Findings

Brenna H. Bry . . . . . . . . . . . . . . . . .

Parent and Peer Factors Associated with Sampling in Early

Adolesence: Implications for Treatment

Thomas J. Dishion, Gerald R. Patterson, and John R. Reid . . . 69

Pharmacotherapy of Concomitant Psychiatric Disorders in

Adolescence: Substances Abusers

27

39

Barbara Geller . . . . . . . . . . . . . . . . . . . . . 94

Treatment Validity: An Approach to Evaluating the Quality of

Assessment

Steven C. Hayes . . . . . . . . . . . . . . . . . . . . .

Adolescent Drug Use: Suggestions for Future Research

Norman A. Krasnegor . . . . . . . . . . . . . . . . .

List of NIDA Research Monographs . . . . . . . . . . .

113

128

135

v
Treatment Services for

Adolescent Drug Abusers:

Introduction and Overview

Elizabeth R. Rahdert

The annual High School Senior Survey conducted by the University of

Michigan's Institute for Social Research reported that the number

of senior high school students who used cocaine, as well as most

other drugs, remained exceptionally high during 1985 (Johnston et

al. 1986). And these estimates of late adolescent drug use would

be even greater had the high-risk, difficult-to-sample high school

dropouts been surveyed. Unfortunately, the 1987 results from the

ongoing study indicate only a modest improvement over the 1985

figures (Johnston 1988). While the 1987 data suggest only a

slight, albeit statistically significant, decline in the use of

cocaine, marijuana, stimulants, and sedatives, there appears to be

little to no change in the student use of inhalants, LSD, heroin,

or other opiates. In addition, the most recent figures show that 4

in every 10 students surveyed said they tried one or more illicit

drugs at least once during the last 12 months. And nearly 5

percent of those questioned said that during the past month they

had used one or more illicit drugs on a daily basis, some of which

were potentially toxic and highly addictive.

These patterns of exposure to one or more potent psychoactive

agents indicate that many teenagers are far past the experimental

phase of illicit drug use, and provide a basis for predicting that

a clinically significant number will or already do suffer serious

physical, mental, and/or social effects after a relatively short

period of abusing drugs. And this prediction, in turn, suggests

that different types of therapeutic interventions will be necessary

to treat these more severely affected youth.

The first addiction facilities, designed to treat the adult male

alcoholic, admitted only a small fraction of the older, addicted

adolescents. Few of these programs made any adjustment to

accommodate even the most obvious developmental differences

1
evident in young drug-dependent clients. In any case, as the

numbers of drug-involved teenagers from the middle and upper

socioeconomic levels rose, so too did the number of treatment

facilities created solely to address the adolescents' age-related

problems. Often these newly established programs advertised a

broad range of therapeutic services, including different

combinations of and variations on drug education, family-based

therapy, parent training, peer group counseling, indlvidual

psychotherapy, and/or social skills training, with psychiatrically

oriented facilities at times offering medication as a therapeutic

option. What each program appeared to share was the common belief

that it was the appropriate place for any and all adolescent

clients. Few referred to other available programs, on a timely

basis, those teenagers they should not or could not treat.

Such all-inclusive admission policies reflect the fact that there

often is insufficient staff time, budgetary support, or perhaps

even administrative inclination, to critically self-evaluate each

service alone and on an interactive basis, to determine which young

clients they could and could not effectively treat. So too these

policies indicate the paucity of scientific evidence to support

specific optimal therapeutic combinations for treating

diagnostically different types of chemically dependent youth. The

current need for adolescent drug abuse treatment research is

apparent. As with most clinical research, designing and conducting

the necessary controlled clinical studies represents a difficult,

but challenging, task.

The contributors to this monograph have presented an overview of

adolescent treatment research with the dual aims of targeting the

specific difficulties associated with adolescent clinical studies

and providing a critical review of what has already been learned

about each step in the treatment process: 1) the initial screening

of high risk teenage populations in order to single out the

affected youth; 2) the diagnostic procedure for identifying

specific impaired or dysfunctional areas; 3) the selection of the

most appropriate treatment facility and/or program for the

indlvidual adolescent, with choice of treatment based on the

results of a diagnostic assessment; 4) the delivery of specific

types of treatment such as family-based therapy or pharmacotherapy;

and 5) the establishment of aftercare programs designed for

school-age youth. It is evident from each review that the field of

adolescent treatment research shares a significant number of design

problems common to any study involving human subjects. young or

old. In addition, many practical issues are identified that appear

unique to studies involving youth rather than adults.

What is most timely is the emphasis placed on the need to reliably

and cost efficiently examine the positive as well as negative

effects of therapeutic programs already in operation.

Concurrently, more creative effort should be channeled toward

developing new and innovative techniques to meet the treatment

needs so apparent in the results of our national adolescent surveys.

2
REFERENCES

Johnston, L.D.; O'Malley, P.M.; and Backman, J.G. Drug Use Among

High School Students, College Students, and Other Young Adults;

National Trends Through 1985. DHHS Pub. No. (ADM) 86-1450.

Washington, DC: Supt. of Docs., U.S. Govt Print Off., 1986.

Johnston, L.D. "Quantitative and Qualitative Changes in Cocaine

Use Among American High School Seniors, College Students, and Young

Adults." Paper presented at the NIDA Technical Review on The

Epidemiology of Cocaine Use and Abuse, Rockville, MD, 1988.

AUTHOR

Elizabeth R. Rahdert, Ph.D.

Treatment Research Branch

Division of Clinical Research

National Institute on Drug Abuse

5600 Fishers Lane

Rockville, Maryland 20857

3
Assessing Adolescents Who

Abuse Chemicals: The Chemical

Dependency Adolescent

Assessment Project

Ken C. Winters and George Henly

INTRODUCTION

There are opportunities and challenges in the treatment of adolescent chemical dependency. Survey data continue to indicate that

American teenagers are using alcohol and drugs at an uncomfortably

high rate (Johnston et al. 1984). More adolescents are being

served by a greater number of chemical dependency treatment programs than at any time before. At the same time, society as a

whole is both becoming more interested in chemical abuse problems

and their treatment and calling for more accountability by those

service providers.

Increased awareness of the problem has affected identification and

treatment of adolescent chemical dependency. Those who abuse alcohol or drugs are being identified at earlier stages of involvement by a wide range of professionals and agencies, which include

school teachers and administrators, officials in the juvenile justice system, and a wide array of therapists and counselors with

varying degrees of clinical training. Earlier detection by diverse professionals may be a positive step for the adolescent user

and the family. There exists the potential that abusers can be

identified before severe problems develop, and identification may

occur in settings that may encourage the individual to seek help.

Yet this trend, in some respects, poses a strain on the treatment

field. Increasingly, service providers are being asked to make

objective decisions about diagnosis, need for treatment, and referral for adolescents whose problem configurations are either

different or less well developed than those of adolescents treated

in the past.

CHALLENGE FOR ADOLESCENT ASSESSMENT

The traditional concepts of the nature of chemical dependency are

largely based on an adult model. When considering the case of

what Jellinek (1960) would classify as a gamma alcoholic (e.g., a

45-year-old individual with a long history of problems resulting

from excessive use of alcohol), it does not require a great deal

4
of sophistication to make a diagnosis of chemical dependency.

There is not likely to be much disagreement among professionals

about this diagnosis. Similarly, when an adolescent presents many

of the hallmark symptoms of adult chemical dependency, it is unlikely that assigning a diagnosis of chemical dependency to this

individual would prove controversial.

Professionals may become increasingly uncomfortable, however,

about making diagnostic and treatment decisions as adolescent

clients bear less and less resemblance to chemically dependent

adults. They may be reluctant to tell those adolescents that they

have a chronic, progressive disease for which lifelong abstinence

is the only treatment route.

Much of this discomfort in assessing and diagnosing the problems

of adolescents in the early stages of involvement with chemicals

is warranted. Studies of general population samples indicate

that, as in the past, substantial proportions of adolescent chemical abusers mature out of their problem use patterns without exposure to formal intervention or treatment. A recent study in

Madison, WI, found that only about half of a sample of adolescents

identified as alcohol abusers could still be so classified when

assessed 6 months later (Moberg 1983). Data from more extended

longitudinal research also indicate the transitory nature of adolescent chemical misuse (Jessor 1982). Although it is not known

whether remitted abusers will resume a pattern of misuse later in

life, data from the existing followup studies are provocative.

Another outcome of the increasing detection and treatment of youth

chemical abuse is that insurers and other third-party payment

organizations are facing mounting costs. Their reaction has been

to require treatment organizations to further document and better

justify the need for treatment. Consequently, and appropriately.

treatment programs must develop assessment procedures that are

more objective and reliable. They are also confronted with the

situation of making diagnostic decisions based on criteria often

formulated by those outside the field.

These strains on the assessment process are further compounded by

the growing attractiveness of chemical dependency treatment and

the reduced diagnostic stigma attached to the chemical dependency

label. Adolescents or their parents may seek a diagnosis of

chemical dependency in situations where chemical abuse may not be

the primary difficulty. Parents would prefer to believe that

their child is chemically dependent, rather than mentally disturbed, delinquent, or living in a chaotic family. The problem

configurations of such clients may be so complex that it is difficult to pinpoint the central target problem or problems. The need

to sort out target problems and make appropriate referral decisions will increase as adolescent chemical dependency treatment

facilities become the programs of first resort rather than of last

resort.
The development of increasingly diverse treatment programs along

the health care continuum increases the demands made upon assessment procedures. The luxury rarely exists today of simply deciding whether or not the adolescent's problems are sufficiently

severe to warrant placement in the one and only available treatment facility. Assessment procedures must become increasingly

detailed and multifaceted, if they are to permit matching the

client to an optimal treatment plan, as the trend moves toward

developing a variety of treatment levels and modalities from which

to choose.

The developments and issues described above pose major challenges

for adolescent assessment. Four of these challenges are identified below.

First, there is a need for increased objectivity of client assessment. At the present time, assessment practices in the field rely

heavily on clinical judgment. In a recent survey of adolescent

chemical dependency programs (Owen and Nyberg 1983), the majority

of respondents indicated that their assessment procedures are informal and typically based on in-house and relatively idiosyncratic questionnaires. As a result, it is problematic when

different programs wish to communicate about the nature of their

respective clientele, or when researchers hope to utilize assessment information from a variety of facilities for research purposes. This state of affairs is not necessarily the result of the

treatment community's unwillingness to use clinically useful and

standardized assessment tools. The reality is that such tools do

not exist.

Second, there must be meaningful differentiation of adolescents

across levels or stages of chemical involvement. Adolescents may

differ not only in terms of the severity and consequences of their

chemical use, but in the pattern of that use and in the configuration of factors that may play a role in leading to, or maintaining

chemical misuse. One central question is whether one can validly

differentiate short-term users or experimenters vs. those abusers

whose problems will endure. Extant data do not allow such discriminations of these two groups based on initial involvement with

drugs.

Another key issue is whether it is possible to differentiate

adolescents in terms of the configuration of their chemical

involvement. This configural perspective is similar to the

multiple-syndrome notion of adult alcoholism (Wanberg and Horn

1983) and may prove to be a more appropriate framework from which

to view adolescent chemical involvement than simply distinguishing

abusers along the severity dimension.

Third, there exists a need to identify and differentiate problems

accompanying chemical abuse. The ability to assess not only the

severity of the chemical use problem itself, but also the extent

of other problems that may complicate or be disguised by chemical

abuse, is a high priority.

6
Finally, there must be differential assignment of client to

appropriate treatment level and modality. As the diversity of

treatment services increases, the basis for choosing among them

for each available client becomes more complicated. There may be

some clients for whom no appropriate treatment currently exists,

while for others, decisions of formal treatment vs. education,

residential vs. outpatient treatment, or extended care vs. support

group, are the relevant questions.

Clearly the issues surrounding the assessment of adolescent chemical involvement are complex and controversial. In 1982, the

Chemical Dependency Adolescent Assessment Project was begun to address some of these issues. The 5-year project is unique in that

it is being completed collaboratively by a consortium of 16 established chemical dependency organizations in Minnesota. Funding

for the project comes from the Northwest Area Foundation. The

Saint Paul Foundation and the Amherst H. Wilder Foundation are

administering the grant on behalf of the consortium. The remainder of this report provides a brief summary of the relevant

assessment literature on adolescent chemical involvement and discusses the current status of research activities by the Adolescent

Assessment Project.

BRIEF OVERVIEW OF PERTINENT LITERATURE

With the exception of two brief screening instruments, the

Adolescent Alcohol Involvement Scale (AAIS) (Mayer and Filstead

1979) and the Youth Diagnostic Screening Test (YDST) (Alibrandi

1978), no psychometrically developed or validated paper-and-pencil

instruments for use with adolescent chemical dependency populations have been reported in the professional literature. The AAIS

has been validated, to some degree, against independent clinical

diagnosis and, in general, has undergone more research scrutiny

than the YDST (Moberg 1983; Riley and Klockars 1984). Nevertheless, the apparent value of the AAIS and YDST is limited to initial screening applications. While they may permit general

evaluation of the extent or severity of the adolescent's problem,

they do not provide for discrimination between different problem

types or configurations.

Related to the "problem severity" instruments is the group of

adolescent survey instruments. The Youth Experience Questionnaire

(Dunnette et al. 1980), the Research Triangle Institute's Study of

Adolescent Drinking Behavior and Attitudes (Rachal et al. 1980).

and the Institute of Social Research's Annual High School Senior

Survey Questionnaire (Johnston et al. 1981) are three important

examples of surveys of nonclinical adolescent populations. These

survey questionnaires typically evaluate use prevalence, extent of

consumption, reasons for use, use patterns, and effects and consequences of use.

Development of instruments for adult chemical-abusing populations

has received, by far, greater attention. These instruments can

offer models from which to work in developing similar instruments

7
for adolescents. The Michigan Alcoholism Screening Test (MAST)

(Selzer 1971), the MacAndrew Scale from the Minnesota Multiphasic

Personality Inventory (MMPI) (MacAndrew 1965). the Alcohol

Dependence Scale (Skinner and Allen 1982), the CAGE Questionnaire

(Mayfield et al. 1974), and the Drug Abuse Screening Test (Skinner

1982) represent popular screening instruments for adults with

substance use problems. Their value is limited, as in the AAIS,

because of their focus on a single, general problem severity

dimension. These questionnaires may be contrasted with the

Alcohol Use Inventory (AUI) (Wanberg et al. 1977). a sophisticated

and well-researched instrument that assesses multiple dimensions

of alcohol involvement. Skinner's (1981) factor analysis of the

AUI suggests four factors or alcoholism "syndromes" tapped by the

AUI: alcohol dependence, perceived benefits from drinking, marital discord, and polydrug use. These findings support a multiple

syndrome conception of alcohol abuse in adults.

In the domain of diagnostic structured interviews, there now exist

several interview protocols for adolescents (or children) that

address DSM-III criteria for mental disorders, including those for

substance use disorder diagnoses. Four prominent interview schedules include the Diagnostic Interview Schedule for Children and

Adolescents (Reich et al. 1982), the Kiddie Schedule for Affective

Disorders and Schizophrenia (Chambers et al., in press), the

National Institute of Mental Health Diagnostic Interview Schedule

for Children (Costello et al. 1984), and the Child Assessment

Schedule (Hodges et al. 1982). While these interviews have undergone evaluations for interrater agreement and have been validated

against external criteria, there are no published reports of the

validity of their substance use disorder diagnosis sections

against independent clinical diagnoses.

In addition to the focus on problem severity and diagnostic classifications, existing personality inventories and research instruments have been used to explore the role of psychosocial variables

in adolescent chemical use. These studies have included measures

of deviance, sensation seeking, aggression, alienation, impulsivity, self-esteem, locus of control, family cohesion, religiosity.

and peer attitudes (to list only a few). While many of these

variables have consistently discriminated samples of adolescent

chemical abusers from samples of nonabusers, the strength of the

observed relationships has generally been modest. Since it

appears that none of these variables constitutes a necessary or

sufficient basis for the development of adolescent chemical abuse

or dependence, it may be more appropriate to consider them as risk

factors that may play a role in predisposing adolescent experimentation with chemicals or perpetuating chemical use once it is

initiated.

It is also important to note that the aforementioned psychosocial

variables are often associated with a broad range of problem behaviors, including delinquency and sexual promiscuity (Jessor and

Jessor 1977; Rathus et al. 1980). Given the nonspecificity of

psychosocial risk factors for adolescent chemical abuse, there is

8
little validity in targeting high-risk individuals on the basis of

these variables alone. Psychosocial measures may, however, have

value in identifying subgroups of chemical abusers who have different treatment needs or prognoses. There is an increasing body

of research concerned with the identification of personality subtypes among adult alcoholics, and some common threads have emerged

across those studies (Costello 1981).

DEVELOPMENT OF A NEW ASSESSMENT BATTERY

In view of the limitations of existing tools to assess adolescent

chemical involvement, the Chemical Dependency Adolescent Assessment Project began the process of developing a new standardized

assessment battery.

The first year of the project was spent reviewing pertinent literature, consulting experts, and talking with direct service providers. A dominant theme that emerged was the complexity of the

problem configurations that characterize this clinical population.

Adolescents were viewed as differing in multiple (perhaps configural) ways, not only in terms of chemical use problem severity.

The convergence of anecdotal clinical reports and the emerging

viewpoint in the adult literature of multiple alcoholism syndromes

or types (Jellinek 1960; Morey et al. 1984) led the project to

base its model for instrument construction on a multidimensional

footing.

A three-ring model has guided the project's efforts in instrument

development (figure 1). The first ring, which occupies the center

of the model, is the problem severity domain. It involves the

signs, symptoms, consequences, patterns, etc., of chemical abuse

and dependency. The project instrument developed to assess this

domain is the paper-and-pencil questionnaire entitled "Personal

Experience With Chemicals Scales" (PECS).

The cluster of variables forming the second ring in the model

refers to the so-called risk factors of substance use. These

predisposing and perpetuating factors include genetic, sociodemographic, intra- and interpersonal , and environmental variables.

The second paper-and-pencil questionnaire that was developed, the

Personal Experience Scales (PES), addresses a subset of these

variables.

The third ring of the model includes variables associated with the

diagnostic classification of psychoactive substance use disorders

and attends primarily to factors associated with DSM-III-R criteria. We have developed a highly structured interview schedule,

the Adolescent Diagnostic Interview-Revised (ADI-R), to address

the third ring. Although the applicability of DSM-III-R substance use disorder diagnostic criteria to adolescents has been

questioned, it may be expected that DSM-III-R interview schedules

will be used to a greater degree as programs are forced to justify

and document their diagnostic decisions.

9
FIGURE 1. A model to guide initial instrument construction

Since tne PECS and PES have received the most attention to date,

the remaining discussion will focus on these two questionnaires.

Due to limitations of space, only a brief overview of the development of these instruments will be presented. A more detailed

report on the development of the battery can be obtained by contacting the authors.

Preliminary Instrument Construction

Three steps were involved in constructing the item pools for the

PECS and PES: (1) items were culled from existing measures and

organized into content categories; (2) ratings of the clinical

importance of each content area were obtained from service providers; (3) new items were written to represent each content area

that was rated important. Additional items were added to assess

defensiveness (items adapted from the Marlowe-Crowne Social Desirability Scale) (Crowne and Marlowe 1960) and invalid responding.

The resulting preliminary versions of the two instruments were

each about 250 items in length. In order to facilitate administration during the research phase, each instrument was divided

into two subsets having similar item content and style, so that

the instruments could be conveniently completed in two separate

sittings.

10
Administration Procedures

In order to remain within project timelines, the PECS and PES were

administered to independent samples at different times. Consenting adolescent clients at participating Minnesota chemical dependency evaluation and treatment programs were administered the PECS

or PES questionnaires during their first week of program contact.

The order of administration of the instrument subtests was randomized, so that the effects of item order and respondent fatigue

might be counterbalanced. The majority of clients completed both

subtests for an instrument in a single sitting. The instruments

were administered by staff members at the participating programs.

Subjects

Participants were consenting adolescents, ages 12 to 18, receiving

chemical dependency evaluation or treatment at 16 Minnesota sites

between March 1984 and May 1985. The participating programs included both hospital and free-standing units that provided either

evaluation or treatment services on either a residential or outpatient basis. Twelve of the sixteen sites are located in the

Minneapolis-St. Paul metropolitan area; the remaining sites are in

rural locations. Approximately 1,100 of the 1,600 clients identified as eligible to participate in the study completed either the

PECS or PES questionnaire. Comparisons of participants and nonparticipants during the PECS and PES administration phase failed

to detect statistically significant differences on either demographic (sex, age, race, prior treatment history) or psychological

(MMPI scale scores) variables. Sample characteristics are summarized in table 1. The majority of the sample is male, white, and

between the ages of 15 and 17.

Scale Analyses

Rational and empirical strategies were employed in the development

of the revised PECS. First, items were assigned a priori to

scales and then reassigned or deleted based on their own-scale and

other-scale correlations, so that scale reliability and independence could be maximized using the rational approach. Second, a

variety of factor and cluster-analytic procedures were employed to

define empirically the PECS. Scales that emerged consistently

across these procedures were then evaluated for clinical utility

and interpretability. Most of the empirical scales were conceptually similar to the rational scales; hence, the empirical scales

formed the basis for the selection of the final set of PECS. A

small number of rational scales were retained because their clinical utility was judged to be important. Rational scale construction procedures formed the primary basis for the development of

the revised PES. In the analyses for both instruments, scale

characteristics were derived and optimized on a development sample

and then tested on a separate, replication sample.

11
TABLE 1. Sample characteristics

Demographic

Variables

PECS (n=646*) PES (n=458*)

n Percent n Percent

Sex

Male

Female

377 60.4 265 61.6

247 39.6 165 38.4

Age

12

13

14

15

16

17

18

19+

Race

White 578 92.3 378

Black 10 1.6 28

American Indian 26 4.2 9

Other 12 1.9 12

Prior Primary Treatment

No

Yes

5

32

78

140

164

151

49

3

463 75.3 335 78.5

152 24.7 92 21.5

0.8 2

5.1 22

12.5 52

22.5 107

26.4 115

24.3 93

7.9 22

0.5 3

0.4

5.3

12.5

25.7

27.6

22.4

5.3

0.7

88.5

6.6

2.1

2.8

*Totals do not add to indicated n due to unavailable or missing data. N's refer

to development and replication samples.

Results

Titles and definitions of the resulting scales of the PECS and PES

are presented in table 2. Scale reliabilities, based on the replication samples, are reported in table 3. The revised PECS have

113 items that permit the scoring of five Basic Scales, five

Clinical Scales, and three Validity Indices. The Basic Scales

account for the majority of reliable instrument variance. The

Clinical Scales, whose items are largely redundant with the Personal Involvement Scale, restructure the information from that

single scale in a way that may be interesting to clinicians,

Estimates of internal consistency reliability for the revised PECS

range from .80 to .97. The 147 items of the revised PES are organized into eight Personal Adjustment Scales, four Family and Peer

Environment Scales, and two Validity Indices. In addition, four

brief problem screens are scored. Internal consistency reliability estimates for the 12 substantive scales range from .74 to .90.

12
TABLE 2. The revised scalesof the Personal Experience With

Chemicals Scales (PECS) and the Personal Experience

Scales (PES)

PERSONAL EXPERIENCE WITH CHEMICALS SCALES

Clinical Scales

1.

2.

3.

4.

5.

Personal Involment (29 items) - High scores on this scale suggest frequent

use at times and in settings that are inappropriate for drug use; use for

psychological benefit or self-medication; and restructuring activities to

better allow use (preoccupation). Low scores on this scale suggest relatlvely infrequent use associated with social settings. This set of items forms

the key scale to assess general problem severity.

Effects From Use (10 items) - The items of this set concern the immediate

psychological, physiological, and behavioral consequences of chemical use.

Social Benefits Use (8 items) - This scale reflects use associated with

increased social confidence and social acceptance.

Personal Consequences (11 items) - Items in this set focus on difficulties

with friends, parents, school, and various other social institutions that are

a result of the use of chemicals.

Social-Rereational Use (8 items) - Items from this scale are associated with

the use of chemicals for fun in social situations.

Basic Scales

6. Transsituational Use (9 items) - This set represents use in a variety of

settings, particularly ones that are inappropriate for drug use (e.g..

school).

7. Psychological benefits Use (7 items) - Items in this set suggest the use of

chemicals to reduce negative emotional states and to enhance pleasure.

8. Preoccupation (8 items) - This scale represents overinvolvement with chemical

use, for example, by preplanning future use, restructuring activities to

better allow private or social use, and rumination about use.

9. Loss of Control (9 items) - This set of items is associated with both the

inability to abstain from chemical use and the inability to moderate use on

occasions when chemicals are available.

10. Polydrug Use (8 items) - The items defining this scale are all indicators of

use of drugs other than alcohol.

Validity Indices

11.

12.

13.

Infrequent Responses (7 items) - These items, having very Iow rates of

endorsement, may be associated with “faking bad,” lnattention, or random

responding.

Defensiveness (15 items) - The basis for this set of items was the 33-item

Marlowe-Crowne Social Desirability scale, a frequently used measure of

defensiveness. The Items were modified slightly to make them appropriate for

an adolescent-population.

Pattern Misfit - Respondents with unusual pattern response on the Personal

Involvement Scale can be statistically identified; an unusual pattern can be

indicative of inattentive or random responding, or may represent actual, but

atypical, chemical use patterns.

13
TABLE 2. (Continued)

PERSONAL EXPERIENCE SCALES

PersonaI Adjustment Scales

1.

2.

3.

4.

5.

6.

7.

8.

PersonaI Adequacy (10 items) - This scale reflects general self-esteem and

self-regard, personal satisfaction, and feelings of competence.

Psychological Disturbance (10 items) - Items from this scale are associated

with psychological problems and distress, such as difficulties with mood,

thinking, and physical concerns.

Social Integration (6 items) - This scale represents social competence,

feelings of belonging to a social group, and degree of mistrust in one's

social Iife.

Self-control (12 items) - These items focus on tendency to act out, to

display anger and aggressiveness, and to defy authority.

Conventional Volumes (11 items) - The items in this set concern acceptance of

traditional beliefs about right and wrong.

Deviant Behavior (10 items) - High scores on this scale suggest involvement

in unlawful or delinquent behavlor.

Future Goal Orientatiom (11 items) - This scale represents planning for and

thinking about one’s future plans, goals, and expectations.

Spirituality (7 items) - High scores on this scale suggest belief in

spiritual Iife and use of prayer.

Family and Peer Environment Scales

9. Peer Chemical Environment (8 items) - The items defining this scale indicate

involvement with chemicals by one’s peers.

10. Sibling Chemical Use (4 ltems) - This set represents chemical use by brothers

or sisters.

11. Family Pathology (14 Items) - Items from this scale are associated with

family problems of chemical dependency, physical or sexual abuse, and severe

family dysfunction.

12. Family Estrangement (13 items) - This scale reflects lack of family solidarIty and closeness and the presence of a parent-child conflict.

Screens for Other Problems

These scales provide brief screens for the following problem areas:

13. Parent/Sibling Chemical Dependancy

14. Physical Abuse

15. Sexual Abuse

16. Eating Disorder

Validity Indices

17. Infrequent Responses (11 items) - These items have very low rates of endorsement and may refIect “faking bad ," inattention, or random responding.

18. Defensiveness (12 Items) - This set of items is based on the Marlowe-Crown

Social Desirability Scale and adapted for use with an adolescent population.

14
TABLE 3. Coefficient alpha reliability estimates for the PECS

and PES

Scale Coefficient Alpha

PECS

Personal Involvement .96

Effects From Use .87

Social Benefits Use .89

Personal Consequences .84

Social-Recreational Use .88

Transsituational Use .91

Psychological Benefits Use .93

Preoccupation .92

Loss of Control .87

Polydrug Use .79

PES

Personal Adequacy

Psychological Disturbance

Social Integration

Self-Control

Conventional Values

Deviant Behavior

Future Goal Orientation

Spirituality

Peer Chemical Environment

Sibling Chemical Use'

Family Pathology

Family Estrangement

.86

.80

.74

.84

.81

.80

.81

.90

.85

.87

.76

.88

Future Work

A series of more complete standardization and validation studies

were initiated in November 1985 to permit development of representative norms (both for treatment and nonclinical populations)

and to further evaluate the battery's validity.3

 Validity evaluations will include examining relationships of instrument scales to

concurrent measures and indicators (e.g., well-established personality measures, diagnoses, family history variables, and parental

report) and to subsequent events (e.g., evaluation and treatment

outcome). Time will not permit us to conduct an extensive outcome

study to evaluate the instruments' ability to predict long-term

treatment outcome; however, initial validation efforts will

examine other important treatment variables, such as referral

decisions, treatment, compliance, and treatment aftercare recommendations.

This assessment battery is expected to be ready for distribution

by June 1987. The package is expected to include a single

15
paper-and-pencil inventory that represents the combined items from

the PECS and PES, a brief screening test derived from the general

problem severity dimension found in the PECS, a structured diagnostic interview that addresses DSM-III-R criteria for psychoactive substance use disorders, and a user's manual.

CONCLUSIONS

The assessment package is intended to serve as an adjunct to clinical assessment. No assessment tool can address all the factors

that need to be considered in making clinical decisions. Rather,

the intent is to assist the clinician by providing information

that is of known reliability and validity and that can be referenced with regard to the larger population of adolescents having

problems related to chemical use. Sound assessment tools can also

provide a more solid foundation for future research. As professionals find that adult models of chemical dependency are unworkable when applied to an adolescent population, the search for new

models will intensify. The implementation of a standardized

assessment package can lead to the establishment of a data base

from which to launch that search.

FOOTNOTES

1.

2.

3.

The ADI-R contains the following sections: sociodemographic

information, alcohol use, cannabis use, other drug use,

psychosocial stressors, level of functioning, and a screen for

mental disorders. Currently, the interview is being evaluated

for interrater agreement and content validity.

Conservative decision rules were established for the rejection

of questionnaires whose responses were of doubtful validity,

due to high scores on the invalidity or defensiveness scale.

The revised versions of the PECS and PES were evaluated preliminarily against some available external criteria. High vs.

low PECS scores were differentiated on the MMPI (number of

elevated scales), on clinical diagnoses (abuse vs. dependence), and on the basis of inpatient vs. outpatient treatment

setting. A similar contrasted group analysis of the PES indicated a strong relationship between deviant PES scores and

scale elevations on the MMPI.

REFERENCES

Alibrandi, T. Young Alcoholics. Minneapolis, MN: Comp Care

Publications, 1978.

Chambers, W.J.; Puig-Antich, J.; Hirsch, M.; Paez, P.; Ambrosini,

P.J.; Tabrizi, M.A.; and Davies, M. The assessment of affective

disorders in children and adolescents by semi-structured interview: Test-retest reliability of the K-SADS-P. Arch Gen

Psychiatry, in press.

16
Costello, R.M. Alcoholism and the alcoholic personality. In:

Meyer, R.E.; Babor, T.F.; Glueck, B.C.; Jaffe, J.H.; O'Brien,

J.E.; and Stabenau, J.R., eds. Evaluation of the Alcoholic:

Implications for Research, Theory, and Treatment. National

Institute on Alcohol Abuse Alcoholism Research Monograph No.

5. DHHS Pub. No. 81-1033. Washington, DC: Supt. of DOCS.,

U.S. Govt. Print. Off., 1981.

Costello, A.J.; Edelbrock, C.S.; Dulcan, M.K.; Kalas, R.; and

Klaric, S.H. Report on the NIMH Diagnostic Interview Schedule

for Children (DIS-C). National Institute of Mental Health.

Washington, DC: Supt. of DOCS., U.S. Govt. Print. Off., 1984.

Crowne, D.P., and Marlowe, D. A new scale of social desirability

independent of psychopathology. J Consult Clin Psychol 24:349-

354. 1960.

Dunnette, M.D.; Peterson, N.G.; Houston, J.S.; Rosse, R.L.;

Bosshardt, M.J.; and Lammlein, S.E. Causes and Consequences

Adolescent Drug Experiences. Final report prepared under 

Contract No. ROI DA 01343 for the National Institute on Drug

Abuse. Minneapolis, MN: Personnel Decisions Research

Institute, 1980.

Hodges, K.K.; Kline, J.; Stern, L.; Cytryn, L.; and McKnew, D.

The development of a child assessment interview for research

of

and

clinical use. J Abnorm Child Psychol 10:173-189, 1982.

Jellinek, E.M. The Disease Concept of Alcoholism. Highland Park,

NJ: Hillhouse Press, 1960

Jessor, R. Adolescent problem drinking: Psychosocial aspects and

developmental outcomes. In: Towle, L.H., ed. Proceedings:

NIAAA-WHO Collaborating Center Designation Meeting and Alcohol

Research Seminar Public Health Service. DHHS Pub.No.(ADM) 

85-1370. Washington, DC: Supt. of DOCS., U.S. Govt. Print.

Off., 1982. pp.-104-143.

Jessor, R., and Jessor, S.L. Problem Behavior and Psychosocial

Development: A Longitudinal Study of Youth. New York:

Academic Press, 1977.

Johnston, L.D.; Bachman, J.G.; and O'Malley, P.M. Highlights From

Drugs and American High School Students 1975-1983. National

Institute on Drug Abuse.- Pub. No. (ADM)83-1317.

Washington, DC: Supt. of Docs., U.S. Govt. Print. Off., 1983.

MacAndrew, C. The differentiation of male alcoholic outpatients

from nonalcoholic psychiatric patients by means of the MMPI. J

Stud Alcohol 26:238-246, 1965.

Mayer, J., and Filstead, W.J. The Adolescent Alcohol Involvement

Scale: An instrument for measuring adolescent use and misuse of

alcohol. J Stud Alcohol 40:291-300, 1979.

Mayfield, D.; McLeod, and Hall, P. The CAGE Questionnaire:

Validation of a new alcoholism screening instrument. Am J

Psychiatry 131:1121-1123, 1974.

Moberg, D.P. Identifying adolescents with alcohol problems: A

field test of the Adolescent Alcohol Involvement Scale. J Stud

Alcohol 44:701-722, 1983.

Morey, L.C.; Skinner, H.A.; and Blashfield, R.K. A typology of

alcohol abusers: Correlates and implications. J Abnorm Psychol

93(4):408-417, 1984.

17
Owen, P.L., and Nyberg, L.R. Assessing alcohol and drug problems

among adolescents: Current practices.

1983.

J Drug Educ 13:249-254,

Rachal, J.V.; Guess, L.L.; Hubbard, R.L.; Maisto, S.A.; Cavanaugh,

E.R.; Waddell, R.; and Benrud, C.H. Adolescent Drinking

Behavior. Research Triangle Park, NC: Research Triangle

Institute, 1980.

Rathus, S.A.; Fox, J.A.; and Ortins, J.B. MacAndrew Scale as a

measure of substance abuse and delinquency among adolescents. J

Stud Alcohol 36:579-583, 1980.

Reich, W.; Herjanic, B.; Welner, Z.; and Gandhy. P.R. Development

of a structured psychiatric interview for children: Agreement

on diagnosis comparing child and parent interviews. J Abnorm

Child Psychol 10:325-336, 1982.

Riley,K., and Klockars, A.J. A critical examination of the

Adolescent Alcohol Involvement Scale. J Stud Alcohol 45:184-

187, 1984.

Selzer, M.L. The Michigan Alcoholism Screening Test: The quest

for a new diagnostic instrument. Am J Psychiatry 127:1653-1658,

1971.

Skinner, H.A. Primary syndromes of alcohol abuse: Their measurement and correlates. Br J Addict 76:63-76, 1981.

Skinner, H.A. The Drug Abuse Screening Test. Addict Behav 7:363-

371, 1982.

Skinner, H.A., and Allen, B.A. Alcohol dependence syndrome:

Measurement and validation. J Abnorm Psychol 91:199-209, 1982.

Wanberg, K.W., and Horn, J.L. Assessment of alcohol use with

multidimensional concepts and measures. Am Psychol 38:1055-

1069, 1983.

Wanberg, K.W.; Horn, J.L.; and Foster, F.M. A differential

assessment model for alcoholism: The scales of the Alcohol Use

Inventory, J Stud Alcohol 38:403-409, 1977.

ACKNOWLEDMENTS

Major funding for the Chemical Dependency Adolescent Assessment

Project was provided by a grant from the Northwest Area Foundation; additional funding and project administration were provided

by The Saint Paul Foundation and the Amherst H. Wilder Foundation.

All correspondence should be addressed to Ken Winters, Adolescent

Assessment Project, 1295 Bandana Boulevard North, Suite 210,

St. Paul, MN 55108.

AUTHORS

Ken C. Winters, Ph.D.

Project Director

George Henly. Ph.D.

Associate Director

Adolescent Assessment Project

1295 Bandana Boulevard North, Suite 210

St. Paul, MN 55108

18
Substance Abuse in Adolescents:

Diagnostic Issues Derived From

Studies of Attention Deficit

Disorder With Hyperactivity

Jan Loney

INTRODUCTION

The accumulated literature on the treatment of substance abuse in

adolescents with a history of DSM-III diagnosed Attention Deficit

Disorder with Hyperactivity or an associated Oppositional Disorder

or Conduct Disorder is extremely limited. In part, this is due to

complicated diagnostic questions which continue to command the

attention of many investigators, and controversies surrounding the

treatment of hyperactivity and attention deficit disorders. This

is especially true for children prescribed central nervous system

(CNS) stimulant medication.

The absence of an empirically based literature does not mean, however, that existing studies of these childhood psychiatric disorders have no value for clinicians concerned with the treatment

of substance abuse among troubled adolescents. On the contrary,

over the past decade, a great deal of information about the diagnosis, prognosis, and treatment of attentional, oppositional, and

conduct disorders has been gathered. Certainly this knowledge

will benefit clinicians in making assessment and intervention

decisions for drug-abusing adolescents.

The earliest research to be carried out focused on prognosis

(e.g., Weiss et al. 1971) and treatment (e.g., Werry and Aman

1975) and will be presented first. A discussion of the implications of several recent studies of diagnosis (e.g., Milich et al.

1982) will follow. A more detailed analysis of these and other

studies concerning substance abuse and childhood hyperactivity is

offered in Kramer and Loney (1982).

Although distinctions have been made between the terms "childhood

hyperactivity" and "attention deficit disorder," they will be used

as synonyms in this discussion, referring to a population of

hyperactive children who have been studied under these and related

terminologies (e.g., minimal brain dysfunction, hyperkinetic

syndrome). Similarly, the terms "childhood aggression,"

19
"oppositional disorder," and "conduct disorder" will be treated as

if they were essentially synonymous.

INFORMATION ABOUT PROGNOSIS

Early investigators tended to believe that childhood hyperactivity

was a form of "maturational delay," and, therefore, the associated

symptoms could be expected to disappear around the time of adolescence. However, carefully designed prospective studies found in

many hyperactive children a "continual display" of problems with

inattention and motor restlessness extending into the adolescent

and young adulthood years, and in several systematic followup

studies, a substantial minority of hyperactive children showed

what could be called "eventual decay," in that after 18 years of

age they were assigned adult psychiatric diagnoses, the most common being Antisocial Personality Disorder. Results from a recent

comprehensive outcome study of 100 children diagnosed as hyperactive (Gittelman et al. 1985) could be interpreted in terms of

"maturational delay" (52 percent of previously diagnosed hyperactive boys showed no psychiatric disorder at 16 to 23 years),

"continual display" (40 percent still displaying signs of an

attentional disorder), and "eventual decay" (27 percent having an

antisocial or conduct disorder at followup).

Hyperactive Children and Risk of Adolescent Substance Abuse

In theory, there are numerous grounds for expecting that hyperactive children might be predisposed to experimentation with illegal substances such as marijuana. Studies of the distinguishing

features of hyperactive children emphasize a host of behavioral

and emotional characteristics which are known or thought to be

related to illegal drug use: impulsivity, low self-esteem, noncompliance with authority, poor school performance, and susceptibility to peer pressure. Conversely, studies of the precursors of

substance abuse among normal children have identified a set of

predisposing factors which are known to describe the typical

hyperactive child.

Attempts to examine adolescent substance use among hyperactive

children have produced numerous methodological problems. Many of

the followup studies had been nonblind, had relatively few subjects, included no control groups, and sustained considerable

subject attrition. Most of these investigations involved samples

of hyperactive subjects averaging 14 years of age and ranging from

as young as 9 to as old as 23 years of age. It is difficult to

generalize from these samples, as they represent children at disparate developmental stages with respect to exposure to illegal

drugs. Few of the subjects in these studies are old enough to

have developed a pattern of serious abuse, and many of the youngest had not yet been exposed to the full range of drugs with abuse

potential. For these reasons, most research into substance use

among hyperactive children and adolescents had been limited to

subjects' use of marijuana and/or alcohol.

20
Few studies have investigated hyperactive children's attitudes or

intentions toward drug use. Fewer still have attempted to delineate the steps leading from the use of one type of drug to another.

The relative paucity of this kind of information makes a comprehensive theory associating adolescent substance abuse with hyperactivity and attention deficit disorders difficult to articulate.

An exception has been the work of Hechtman et al. (1984), who

presented a series of pioneering studies which described substance

use among groups of Canadian hyperactive children. The developmental focus permitted Hechtman et al. to contrast early substance

use with more recent use. Hyperactive youngsters were not reported to differ from controls in their recent use of most illegal

substances. However, control subjects were reported to use hallucinogens more frequently.

Developmental data can also help bring basic information about

initiation of substance use into clearer focus. For example, in

one of Loney's studies (unpublished), 33 of 95 adolescent hyperactive boys said that they had tried marijuana. However, only 70

of the boys knew someone who used marijuana, and only 50 of the 95

reported actually having the opportunity to smoke it. Thus, the

36 percent of the total sample who had tried the substance represented two-thirds of those having the opportunity. Sixty percent

of the 33 hyperactive boys who had "ever tried" marijuana had used

it some time during the month of the followup interview. Of the

20 boys who continued to use it, 8 escalated to "frequent" use

(defined as use of the drug on at least 15 days during the current

month). Only at the point of escalation did the hyperactive boys

tend to differ from their classmate controls; fewer controls used

marijuana frequently during the month of the followup interview.

Differential Risk for Hyperactive Subgroups

It has long been known that hyperactive children are a heterogeneous population, both at the time of initial psychiatric referral

and in terms of response to treatment. Thus, a recurring question

concerns identifying those characteristics or antecedent activities that will predict which hyperactive child will develop drugrelated problems. Fortunately, studies that have asked these

prediction questions represent the more controlled and least ambiguous research. This is true in part because the questions of

proper diagnosis and appropriate control groups were not of

central importance.

Loney et al. (1981a; Loney et al. 1981b) have systematically

followed approximately 300 hyperactive boys and controls into

adolescence (ages 12 to 18) and young adulthood (ages 21 to 23),

using an extensive battery of tests and interviews to obtain

information from the boys and their parents and teachers. All the

hyperactive boys were originally referred to a major medical center for outpatient psychiatric evaluation, and all were treated

with either psychostimulant medication or with behaviorally oriented parent and teacher counseling. The results of these studies

indicate that among so-called hyperactive children, those who were

21
more aggressive, oppositional, and conduct disordered eventually

had problems with illegal drug use. In contrast, hyperactive

children who did not show signs of aggressivity at referral

appeared more at risk for academic problems.

INFORMATION ABOUT TREATMENT

This discussion will be confined to studies of treatment with

stimulant medications because of their presumed association with

later substance use.

There is no question that the majority of hyperactive children

respond with behavioral improvement after treatment with stimulant

medication such as methylphenidate. Numerous well-controlled

within- and between-group studies have established their shortterm efficacy. Unfortunately the studies that focus on the longterm consequences of the medication are rife with problems and,

therefore, difficult to interpret. Many compare medicated hyperactive children with unmedicated nonhyperactive children, such as

brothers and classmates, making it impossible to differentiate the

signs of a hyperactive disorder from the short-term effects of the

stimulant medication. However, it is impossible to assign hyperactive children randomly to either long-term medication or nontreatment conditions.

Results from the earliest studies of the long-term stimulant

effects were discouraging because investigators expected the druginduced behavioral improvements, in evidence during childhood, to

affect performance through adolescence even if a child was no

longer on the medication. Instead, there appeared to be no longterm drug effects on adolescent behavior (Weiss et al. 1975).

However, later studies suggested that the effects, while minimal,

were positive. For example, Loney, Kramer, and Kosier (Loney et

al. 1981a) found that, at 5-year followup, hyperactive boys who

had been medicated for an average of 2 years were rated by their

mothers as having fewer problems with motor coordination and selfesteem than the unmedicated boys. However, when teachers rated

both medicated and unmedicated hyperactives, no difference was

found between groups in these or any other behaviors. In addition, stimulant medication was unrelated to adolescent performance

on intelligence and achievement tests.

Childhood Drug Treatment and Risk of Substance Abuse in

Adolescence

Early concern about the long-term effects of treating hyperactive

children with a stimulant drug stemmed from the fear that such

treatment would lead to later use of illegal drugs. This fear

resulted from several coexisting factors: (1) Public sensitivity

to the increasing use of illegal drugs among youth, and (2) an

expectation that at maturity hyperactive children might become

dependent on stimulant medication in the same way as nonhyperactive adolescents. In the absence of data, public concern about

22
stimulant medication acting to precipitate later drug abuse was

hard to allay.

Clinical reports verify that many hyperactive children dislike

taking their stimulant medication because of its side effects,

because their peers tease them about being on "speed," or because

they dislike taking any kind of pills. Many adolescents refuse to

take their prescribed medication. Therefore, clinicians often

have difficulty maintaining their patients on a stimulant regimen,

and many consider it improbable that drug abuse will emerge.

In an adolescent followup study of medicated and unmedicated

hyperactive boys, Loney et al. (1981a) found no differences between groups in self-reported delinquencies such as stealing,

property damage, and car accidents, although the unmedicated boys

reported significantly more instances of drunk driving. Similarly, the medicated and unmedicated boys did not differ in the

seriousness of their overall involvement with legal authorities,

although the unmedicated boys reported significantly more serious

police involvement for substance-related offenses. In a further

study of the same sample, Kramer et al. (1981) found few differences between medicated and unmedicated hyperactive boys in attitudes toward and experimentation with various illegal substances,

but the trend was toward a higher use among the unmedicated hyperactive boys. Results from these studies suggest that if early

treatment with stimulants can decrease the irritability and

impulsivity of hyperactive children and raise their frustration

tolerance and self-esteem, those effects might even decrease the

probability of ultimate drug abuse. This is a hypothesis that

needs to be tested.

INFORMATION ABOUT DIAGNOSIS

Over the decades that childhood hyperactivity has been studied,

questions regarding proper assessment and diagnosis have been frequent and frustrating. While early investigators focused their

attention on whether drug treatment was safe and effective, the

underlying disorder was little understood. It was acknowledged

that any given group of children selected for study was heterogeneous in that the subjects varied from one another, and each

behaved differently across different situations and from one time

to the next. Thus, the diagnostic issues surrounding attention

deficit disorders with hyperactivity were increasingly addressed.

Initial diagnostic studies directed attention to aggressive behaviors that had been identified as important predictors of treatment

success. It became clear that many hyperactive children were also

aggressive. For example, in a group of clinic-referred boys who

met criteria for hyperactivity on the widely used Conners teacher

rating scale, 65 percent were classified as both hyperactive and

aggressive, whereas only 17 percent were exclusively hyperactive

(Loney and Milich 1982).

23
In contrast, unpublished data from a large metropolitan clinic

yielded very different findings. Only 25 percent of the referred

hyperactive boys received a mixed diagnosis. In addition, only 17

percent of the hyperactive students from an elementary school sample could be described as mixed hyperactive-aggressive children

(Loney and Milich 1982). These findings have major diagnostic and

prognostic implications.

Despite controversy concerning the interdependence of hyperactivity and aggression, there is evidence that each of these

characteristics should be measured as independent dimensions.

Each may have different childhood antecedents and different

adolescent and adult consequences (Loney et al. 1981b). For clinicians interested in the treatment of illegal and norm-violating

behaviors such as substance abuse, it is important to note that

these behaviors appear to be more closely related to childhood

aggression, conduct problems, and oppositional behavior than they

are to childhood overactivity, short attention span, and cognitive

impulsivity.

As clinical investigators become more sensitive to the diagnostic

issues, fewer include aggression in their definition of hyperactivity. However, the lack of discriminant validity of the measures of hyperactivity and aggression suggests that hyperactivity

and aggression may be two separate problems (Loney et al. 1978).

two intertwined problems (Prinz et al. 1981), or indistinguishable

facets of the same problem--a Conduct Disorder (Quay 1979). Most

scales used to measure these two constructs have been moderately

to highly intercorrelated. However, when the behavioral observation data were substituted for teacher rating-scale data, correlations between hyperactivity and aggression were markedly reduced

(Loney and Milich 1982).

Meanwhile, what appears to be a relationship between childhood

hyperactivity and adolescent substance abuse may actually be the

previously well-documented relationship between childhood aggression and substance abuse. Most of the rating scales and structured interviews used to assign scores on hyperactivity factors or

to diagnose children with attentional disorders contain items

which tap factors related to aggressive behavior as well as motor

activity and ability to concentrate. Therefore, the selected samples of hyperactive children often include aggressive/oppositional

as well as exclusively hyperactive children. Obviously, data on

the drug use of these samples cannot be interpreted with clarity

and confidence.

Attempts have been made to obtain more homogenous samples by excluding children with DSM-III diagnosed conduct disorders. This

method is likely to remove the oldest and most antisocial children, but an unknown number of oppositional and/or aggressive

children will remain in the group. Since these children are known

to be at risk for drug abuse, their presence will confound the

results. Other frequently used methods to identify hyperactive

adolescents may actually increase the heterogeneity. When parent

24
input is added to the results from teacher questionnaires which

gather data on children in structured, attention-demanding situations, diagnostic heterogeneity is often increased.

Diagnostic procedures that use several methods of assessment or

high cut-off scores to select the most severely dysfunctional

children will probably increase the proportion of mixed hyperactive-aggressive children in their samples. Results from those

studies might have less generalizability to populations of pure

hyperactive children. But these limitations will persist until

valid measures of attentional, conduct, and oppositional disorders

are available.

At present an empirical foundation is in the process of being

 built. Meanwhile, critically important questions will remain in

understanding the relationship between attentional deficit and

adolescent substance abuse disorders.

REFERENCES

Diagnostic and Statistical Manual of Mental Disorders. 3rd

edition Washington, DC: American Psychiatric Association.

1980.

Gittelman, R.; Mannuzza, S.; Shenker, R.; and Bonagura, N. Hyperactive boys almost grown up: I. Psychiatric status. Arch Gen

Psychiatry 42:937-947, 1985.

Hechtman, L.; Weiss, G.; and Perlman, T. Hyperactives as young

adults: Past and current substance abuse and antisocial

behavior. Am J Orthopsychiatry 54:415-425, 1984.

Kramer, J., and Loney, J. Childhood hyperactivity and substance

use: A review of the literature. In: Gadow, K.D., and Bialer,

I., eds. Advances in Learning and Behavioral Disabilities.

Vol. I. Greenwich, CT: JAI Press, 1982.

Kramer, J.; Loney, J.; and Whaley-Klahn, M.A. The role of prescribed medication in hyperactive youths' substance abuse.

Poster presented at the annual meeting of the American

Psychological Association, Los Angeles, 1981.

Loney, J., and Milich, R. Hyperactivity, inattention, and aggression in clinical practice. In: Wolraich, M., and Routh, D.K.,

eds. Advances in Developmental and Behavioral Pediatrics.

Vol.3 Greenwich,CT: JAI Press 1982.

Loney, J.; Langhorne; J.E., Jr.; and Paternite, C.E. An empirical

basis for subgrouping the hyperkinetic/minimal brain dysfunction

syndrome. J Abnorm Psychol 87:431-441, 1978.

Loney, J.; Kramer, J.; and Kosier, T. Medicated versus unmedicated hyperactive adolescents: Academic, delinquent, and symptomological outcome. Poster presented at the annual meeting of

the American Psychological Association, Los Angeles, 1981a.

Loney, J.; Kramer, J.; and Milich, R.S. The hyperactive child

grows up: Predictors of symptoms, delinquency, and achievement

at follow-up. In: Gadow, K., and Loney, J., eds. Psychosocial

Aspects of Drug Treatment for Hyperactivity. Boulder, CO:

Westview Press, 1981b.

25
Milich, R.; Loney, J.; and Landau, S. The independent dimensions

of hyperactivity and aggression: A validation with playroom

observation data. J Abnorm Psychol 91:183-198, 1982.

Prinz, R.J.; Connor, P.A.; and Wilson, C.C. Hyperactive and

aggressive behaviors in childhood: Intertwined dimensions.

J Abnorm Psychol 9:191-202, 1981.

Quay, H.C. Classification. In: Quay, H.C., and Werry, J.S.,

eds.

York: Wiley, 1979.

Psychopathological Disorders of Childhood. 2nd ed. New

Weiss, G.; Minde, K.; Werry, J.S.; Douglas, V.; and Nemeth, E.

Studies on the hyperactive child VIII: Five-year follow-up.

Arch Gen Psychiatry 24:409-414, 1971.

Weiss, G.; Kruger, E.; Danielson, U.; and Elman, M. Effects of

long-term treatment of hyperactive children with methylphenfdate. Can Med Assoc J 112:159-165. 1975.

Werry, J.S., and Aman, M.G. Methylphenidate and haloperidol in

children: Effects on attention, memory, and activity. Arch Gen

Psychiatry 32:790-795, 1975.

AUTHOR

Jan Loney, Ph.D.

Professor

Department of Psychiatry and

Behavioral Science

South Campus, Putnam Hall

State University of New York

at Stony Brook

Stony Brook, NY 11794-8790

26
Empirical Guidelines for Optimal

Client-Treatment Matching

Reid K. Hester and William R. Miller

INTRODUCTION

In the last 10 years, interest in treating adolescent substance

abuse appears to have increased dramatically. A great deal more

treatment is now being provided to this population, frequently

utilizing intervention strategies which have been extrapolated

from those used to treat adults. Unfortunately, our understanding

of which interventions are most beneficial for which adult clients

is in its infancy. The purpose of this paper is to develop guidelines for matching adolescent clients to treatments, based on the

current substance abuse treatment literature. An underlying

assumption in developing such guidelines is the following hypothesis: Adolescents who are appropriately matched to treatment will

show outcomes superior to those who are unmatched or mismatched.

This hypothesis predicts an interaction between client variables

and treatment outcome even in the absence of main treatment

effects. Figure 1 shows how client characteristics could interact

with treatment outcome to produce a potentially confusing picture

of the effects of treatment.

Education, which significantly interacts with treatments A and B,

has been labelled the predictive variable. In study 1, for clients with low educational levels treatment B has a better outcome

than A. In study 3 the opposite is true, while in study 2 there

is no significant difference. Averaging all educational levels

results in no main effect of treatment, thereby leading to the

erroneous conclusion that the treatments are equivalent. In fact,

however, there is a significant interaction between education levels and treatments, and for certain clients there is a substantial

difference in effectiveness between the alternative interventions.

Matching a client's needs to specific treatments has validity and

is routinely done in medicine. Although widely discussed, this

notion has seldom been applied in the area of alcohol and drug

abuse treatment. It is a notion which is just beginning to develop in the area of adolescent substance abuse treatment, and there

27
FIGURE 1. A hypothetical client-by-treatment interaction

are few data which can be used to develop guidelines. The reasons

for this are several. First is the common and, we believe, mistaken assumption of uniformity of drug or alcohol abuse. Alcoholism, in particular, has been thought to have a common etiology and

therefore one method of treatment. A second factor discouraging

individualization of intervention has been the historic tendency

for treatment professionals and programs to adhere to a single,

often dogmatic view of etiology and proper remediation. To be

sure, there are rival and alternative approaches to intervention,

but each particular program has tended to embrace and manifest a

specific strategy, be it education, group confrontation, drug substitution, therapeutic community, Alcoholics Anonymous or Narcotics Anonymous, or training in alternatives to drug use. As a

consequence of these factors, assumption of uniformity and adherence to a particular philosophy of intervention, treatment, and

prevention programs have often offered a very narrow range of

alternative strategies necessarily constraining the potential for

individualizing intervention.

We will review the adolescent data first, then the adult literature, to determine potentially fruitful areas of investigation.

Next, we will present recommendations for the development of

potentially promising approaches and procedures to evaluate client

treatment interactions. Of necessity, much of what will be presented is extrapolated from the adult alcohol and drug abuse

treatment literature. Although there may be significant differences in treatment interventions which are appropriate for adolescents, how to match a client with optimal treatment is still an

empirical question. The adult treatment literature has valuable

28
information which can be used efficiently and effectively to

develop and evaluate adolescent client treatment interactions.

PREDICTOR DATA

Adolescent literature

National studies (e.g., the Drug Abuse Reporting Program (DARP)

and the Treatment Outcome Prospective Study (TOPS)) to date appear

to have been designed to gather data on the overall outcome of

clients receiving treatment in the various settings. Only the

DARP included an "intake only" comparison group of clients

(Simpson and Sells 1982). Unfortunately, Simpson and Sells did

not find any data which might indicate an optimal client-treatment

setting match. They did note, however, that the best predictors

of specific posttreatment outcomes were pretreatment measures of

functioning (e.g., pretreatment alcohol problems predicted heavier

consumption after treatment). Simpson and Sells also noted that

continued time in treatment, completion of treatment, and favorable behavior during treatment were positive prognostic indicators

of outcome.

The TOPS specifically evaluated treatment outcome for adolescents

(Hubbard et al. 1985). Unfortunately, this study does not appear

to have included any untreated control groups. Consequently, it

is impossible to determine how much of the improvement in outcome

measures after treatment may have been affected by confounding

factors.

Two studies of young drug abusers in Scandinavia have specified

client characteristics which influence outcome after treatment.

Holsten (1980) found that 26 percent of the variance in outcome at

1 to 6 years after treatment was associated with: (a) the youth

not being registered for criminality for the 12 months prior to

the first contact, (b) no alcohol problems at the time of the

first contact, (c) being female, (d) being raised in a broken

home, and (e) having a father who had no alcohol problems during

the youth's childhood. Benson (1985) found that continued users

after treatment tended to: (a) deviate more from school careers,

(b) be more truant if they were male, and (c) have one or more

alcoholic parents if they were female. Low intensity of drug and

solvent abuse were positive prognostic factors.

Vaglum and Fossheim (1980) reported that adolescents' primary drug

of abuse was associated with how favorably they responded to various forms of treatment. For users of psychedelic drugs the amount

of family therapy, followed by individual psychotherapy, was most

strongly correlated with outcome, whereas confrontive milieu therapy was slightly negatively correlated with outcome. Conversely,

for opiate and central nervous system (CNS) stimulant users, the

degree of confrontive milieu therapy was strongly correlated with

outcome, followed by family therapy and individual psychotherapy.

29
Unfortunately, for the purposes of developing matching criteria,

these studies, with the exception of that of Vaglum and Fossheim,

were primarily concerned with the overall impact of substance

abuse treatment. Comparisons were between treatment settings, and

it is impossible to determine what sort of specific interventions

were conducted within those settings. This lack of specificity

severely limits the utility of these data in developing matching

criteria.

Adult Literature

If there are very few relevant data in the adolescent treatment

literature, perhaps useful implications can be derived from the

literature describing adult treatment strategies. While there may

be substantial differences in the specific problems which adolescents and adults present, perhaps by examining the adult literature we may at least avoid reinventing the wheel (or the Edsel)

and avoid some of the mistakes reported in the adult literature.

We will examine the adult literature by client variables rather

than by treatment interventions because the search for potential

matching criteria is of foremost concern here.

Psychopathology. A recent National Institute on Drug Abuse (NIDA)

report (1983) presented the results of two studies of client

treatment interactions where the treatment populations were opiate

addicts. Both studies evaluated the effects of structured psychotherapies in addition to the usual drug counseling of the clinic

programs. In one study, conducted in Philadelphia at the VA Medical Center, clients with low levels of psychiatric symptoms had a

better outcome than those with higher levels of such symptoms.

They also reported that the "high-severity clients assigned to

additional therapy groups showed more significant improvements,

while those high-severity clients who received counseling alone

showed progress only in reducing their drug use" (NIDA 1983,

p. iv). In addition, depressed clients received substantial benefits from the additional therapy, while those with antisocial

personality showed little improvement except in drug use. In contrast with these results, the New Haven study in the NIDA report

did not find significant client treatment interactions. The

discrepancies between the two studies were attributed to the differences in treatment populations and problems with the implementation of the second study.

McLellan and his associates (McLellan et al. 1983), who conducted

the 1983 NIDA study in Philadelphia, also conducted a retrospective and prospective study to develop a multivariate equation

which optimally matched clients with treatments. In their initial

study they found that measures of psychiatric symptomatology and

social stability interacted with outcome in complex ways. The

investigators used this information, attempting to match clients

prospectively to various treatments. They found that clients

appropriately matched to treatment had a significantly better outcome than those who were unmatched or mismatched. Clients were

not randomly assigned to matched or unmatched conditions, however,

30
and some of their statistical analyses may have overestimated the

effects of matching. Nevertheless, these two studies represent a

significant advance in client-treatment matching research.

Cognitive style. Cognitive style can be defined as "enduring

patterns of perception and information processing that the client

evidences in a broad range of situations" (Miller and Hester, in

press). McLachlan (1972; McLachlan 1974) found a strong interaction between a client's conceptual level (CL) and the structured

nature or directiveness of treatment. People with low CL tend to

depend on authority and prefer simpler rules and constructs. In

contrast, high-CL individuals are more independent and more complex in their thought processes. McLachlan hypothesized that

high-CL alcoholics would benefit more from a less structured and

nondirective approach, while low-CL clients would show greater

benefit from a more structured and directive approach. At 12- to

16-month followup (McLachlan 1974), clients matched during treatment and aftercare had a 71-percent recovery rate, whereas those

who were mismatched in treatment and aftercare had a 38-percent

recovery rate. Recovery rates for clients only matched to treatment or to aftercare showed intermediate rates of recovery.

Finally, although no main effects for treatment were found, there

was a strong interaction effect. McLachlan would have concluded

erroneously that directiveness of treatment has no effect on

outcome had he not investigated the effects of CL.

In a retrospective prediction of outcome, Thornton et al. (1977;

Thornton et al. 1981) found an interaction between developmental

level (DL) and outcome. DL is a construct similar to CL. At

followup they found that high-DL clients were more likely to drink

moderately when they did drink, whereas low-DL clients drank more

frequently and more heavily.

Finally, Karp et al. (1970) studied the relationship between field

dependence, a measure of cognitive style, and outcome. For

alcoholics, field independence predicted initiation of and continuation in psychotherapy. In contrast, dropouts from psychotherapy

for drug abuse were slightly more field independent. When they

combined interventions in analyses, field dependence failed to

predict compliance in treatment.

Neuropsychological functioning. O'Leary et al. (1979) found

neuropsychological impairment to be negatively associated with

outcome for alcoholics. They did not find, however, that providing cognitively impaired alcoholics with more or longer treatment

significantly improved outcome (Walker et al. 1983). This does

not preclude the interesting possibility that clients with cognitive impairments might differentially benefit from different types

of interventions.

Self-esteem. Annis and Chan (1983) found a significant interaction between self-esteem and a confrontational group therapy

intervention. Alcoholic clients with high self-esteem benefited

31
from the additional intervention; for those with low self-esteem,

it was detrimental, and they fared better without it.

Social stability. Both Levinson (1977) and Smart (1978) found

married and employed alcohol abusers to be more likely to develop

moderate drinking outcomes, compared to less socially stable

clients. Azrin et al. (1982) found that unmarried clients benefited differentially from a broad-spectrum community approach.

Married clients, on the other hand, had comparable outcomes when

they received either the comprehensive community program or disulfiram with a behavioral compliance program. Thus, clients with

less social stability may need a more broadly based system of

interventions.

Client choice. Satisfaction with treatment (Vannicelli 1978),

compliance in treatment (Sanchez-Craig 1980), and outcome from

alcoholism treatment (Thornton et al. 1977) have been positively

associated with the amount of client choice in determining the

goal and nature of treatment. Kissin et al. (1971) randomly

assigned clients to receive up to three treatment choices.

Abstinence rates at followup increased with the number of choices

offered to the client.

Summary of Client Variables

The brief review provided above of interaction between adult

client variables and treatment suggests that there may be a number

of similar or identical variables which influence treatment outcome among adolescents. It would be grossly premature to recommend specific criteria for matching adolescents to treatment at

this time. However, a number of general principles can be extrapolated from the data on adult matching. In a recent review of the

adult literature in this area (Miller and Hester, in press), we

came to the following tentative conclusions:

The degree of differential benefit from a broad-spectrum

intervention (such as the "alternatives" approach common in

drug abuse intervention with adolescents) depends upon the

degree to which the individual manifests the life problem or

deficit for which the additional intervention is an effective

treatment.

Clients show greater improvement when matched with a treatment

that is congruent with their cognitive style relative to clients who are unmatched or mismatched.

Clients who choose their treatment approach from among alternatives show greater acceptance of, compliance in, and improvement following treatment relative to clients offered only a

single program or approach.

Clients with more severe alcohol-related problems benefit

differentially from more intense (though not necessarily

inpatient) treatment, whereas clients with less severe problems

32
benefit at least as much, if not more, from a minimal

intervention.

RECOMMENDATIONS FOR FUTURE RESEARCH

At this point it is clear that the field would benefit from welldesigned studies to determine which adolescents benefit most from

which specific interventions. Jaffe (1984) has already recommended that this be a focus of future research and has expanded the

notion. He further cites data suggesting that different dimensions of drug abuse and life adjustment are modestly intercorrelated at best, This notion has been supported in the adult

alcoholism literature by Horn (1978). Specifically, he notes

that:

If this relative independence (of outcome measures) is

true for all programs, then the old question of which

programs are best suited to which patients becomes more

complex. It may be necessary to pay more attention to

the components of individual programs to learn which

program elements influence which outcome dimensions for

which patients. (Horn 1978, p. 20)

Again extrapolating from the adult literature, we offer a number

of recommendations about how such studies could be designed to

provide the most useful information. The aspects that need to be

considered include research strategy and design, treatment interventions, and assessment approaches.

Research Strategy

Two appropriate strategies are the differential research strategy

and a modelling approach. The differential approach compares two

or more treatment interventions within the same population and

study. Ideally, clients are randomly assigned to treatment.

A priori blocking with a selected predictor variable (e.g., clients high vs. low on severity) ensures equal distribution of the

variable in each treatment. A second option involves no a priori

blocking but multiple regression on client variables within each

treatment. Although random assignment is preferred, some quasiexperimental designs allow for nonrandomized assignment to treatment. An example is the regression discontinuity design (Campbell

and Stanley 1963; Lettieri, unpublished manuscript; Trochim 1984).

This design establishes a cutoff score on a predictor variable.

Clients are then assigned to treatment or control groups solely on

the basis of the cutoff score. If done retrospectively, cases are

selected which meet the established cutoff scores. The differential effect of the programs is measured by examining the regression lines. Profiles of successful clients for each treatment can

be developed with differential strategies.

An intriguing alternative to the development of elaborate actuarial schemes for client-intervention matching is to offer individuals a range of well-specified options and allow the clients to

33
choose for themselves. As indicated above, current data suggest

that this procedure diminishes dropout rates and enhances both

compliance and outcome, relative to procedures which assign treatment. In the absence of valid empirical criteria for matching,

self-selection from several options may offer an optimal approach.

In reality, self-selection occurs even when limited alternatives

are offered, operating through mechanisms such as differential

dropout and compliance. An interesting question for future studies is whether empirical-actuarial schemes for optimizing matching

can improve outcome over client self-selection from the same menu

of options, or therapist intuitive matching using the same menu.

Should it be found that either the clients themselves or certain

therapists are superior in selecting optional approaches, a mathematical modelling strategy can be used to develop empirical representations of the strategies employed. The actuarial application

of derived decision rules may either equal or exceed the efficiency of the human judgment processes from which they were derived

(Goldberg 1972).

This modelling approach investigates how clinicians or clients

select treatment; in other words, how and what criteria are used

in assigning clients to alternative approaches. This perspective

was developed by Goldberg (1968; Goldberg 1971) to study the decision making of clinicians. Quantitative client characteristics

are the independent variables, and the chosen treatment is the

criterion variable. Using a discriminant function analysis, one

can generate a multivariate equation which models the decisionmaking process. After compliance in treatment and outcome are

measured, it is possible to determine which judgments about treatment result in the best outcomes for which clients. This approach

can be applied to clinicians' judgments or clients' judgments

about treatment.

Treatment interventions

Selecting a research strategy and experimental design will be a

futile exercise unless the interventions themselves are operationally defined. With the exception of some family therapies

(Szapocznik et al. 1983). there is little specificity in the

adolescent literature about what is actually done in treatment.

It is insufficient to describe treatment in terms like "individual

counseling" or "group psychotherapy." To enable replication of

treatment, matching research must specify the amount (length of

session, number of sessions over what period) and content of

interventions. With regard to content, the development and publication of research treatment procedures manuals would be helpful

in specifying interactions of interventions.

Assessment Approaches

A solid research design with specified interactions will still

fail to yield adequate matching criteria if client characteristics

34
and outcomes are poorly assessed. The selection of intake and

outcome data should take into consideration the frequent independence of various client characteristics and problems. Potentially

predictive variables which have been investigated in the adult

literature and show some promise are: (a) problem severity which

can be defined as problem duration, severity or cumulative signs

of dependence, level and pattern of alcohol/drug consumption, or

severity of current or cumulative consequences; (b) concomitant

psychopathology; (c) social stability which could also include

measures of family functioning and dynamics; (d) neuropsychological functioning; (e) personality characteristics, with emphasis on

personality subtypes; (f) cognitive style; (g) locus of control;

(h) perceived choice; (i) family history; and (j) stage of change

(Prochaska and DiClemente, in press).

Although there are many options for predictors, each study should

specify a small number of focal predictor variables chosen on

theoretical or empirical grounds. Otherwise, small samples will

limit the utility and power of multivariate analyses (Harris

1985). Measurement should be conducted in such a way as to allow

for replication in other clinical and research settings.

Measures of outcome also need to assess posttreatment experiences.

Moos and his colleagues (Ffnney et al. 1980) have repeatedly demonstrated that non-treatment-related experiences have a substantial impact on posttreatment functioning. In addition, these

experiences may interact with specific client characteristics and

treatment in ways which are, as yet, not understood.

CONCLUSIONS

The use of matching procedures shows promise of improving the

overall effectiveness of treatment. Significant differences in

effectiveness may be unmasked where interventions were previously

found to be equivalent. In this area the adult literature is in

its infancy, while the adolescent literature is in the prenatal

stage. Nevertheless we offer the following recommendations about

current clinical practice and future research:

First, intervention systems should offer a range of approaches

varying in content, setting, and intensity. Variety is a

prerequisite for matching research.

When single programs fail to manifest alternatives, priorities

should be given to higher order brokering systems capable of

matching clients with interventions.

High priority funding should be given to quality research on

matching.

35
Matching studies should clearly specify in replicable, operational terms the interventions under study and should include

an adequate range of assessment tools for specifying client

characteristics and outcome.

Random assignment designs are highly desirable, although quasiexperimental alternatives (e.g., regression discontinuity) are

appropriate for studying matching processes.

Client self-selection among alternatives should be considered

and studied as a procedure for optimizing client-intervention

matching, thereby diminishing dropout, increasing compliance,

and improving outcome.

Finally, the utility of actuarial systems should be contrasted

with that of client self-selection and therapist assignment

among the same alternative interventions.

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AUTHORS

Reid K. Hester, Ph.D.

Behavior Therapy Associates

Albuquerque, NM 87110

William R. Miller, Ph.D.

Department of Psychology

University of New Mexico

Albuquerque, NM 87131

38
Family-Based Approaches to

Reducing Adolescent Substance

Use: Theories, Techniques, and

Findings

Brenna H. Bry

INTRODUCTION

Knowledge regarding the effects of family-based interventions upon

adolescent substance use is currently being pursued simultaneously

from two significantly different theoretical viewpoints. These

two conceptual frameworks, family systems theory and behavioral

theory, generate differing explanatory hypotheses and focus on

differing sets of variables. Mature scientific disciplines thrive

on disparate viewpoints, in that competing orientations challenge

researchers to clarify, extend, and expand their own frameworks to

account for increasingly more phenomena. Consequently, I expect

the presence of the two paradigms to enhance knowledge about

family-based interventions. Accordingly, the purpose of this

paper is to highlight the accomplishments of scientists in both

paradigms by (a) presenting the premises and current concepts of

both competing theories, (b) describing the interventions each

framework has spawned, and (c) reviewing the findings each has

generated.

FAMILY SYSTEMS THEORY

Assumptions and Concepts

General systems theorists propose that since human behavior is

inextricably embedded in systems of reciprocally interdependent

interactions, behavior problems can best be understood by studying

the structures and processes of systems within which behavior

occurs (Bertalanffy 1981; Miller 1978). More specifically, family

systems theorists believe that adolescent problems can best be

understood by studying the characteristics of one of the systems

within which they occur, the family system.

Some of those family systems characteristics are: (a) clarity and

permeability of boundaries, (b) flexibility of interactions, (c)

proximity of the interrelated parts (family members), (d) autonomy

of the interrelated parts, (e) degree of interdependence between

the family and surrounding systems , and (f) repetitive behavioral

39
sequences that maintain the family homeostasis or status quo

(Foote et al. 1985; Kaufman 1984; Stanton et al. 1982).

Descriptive studies lend support to systems theory assumptions

that family systems characteristics will covary with members'

problems. In a multiyear, multimethod study, Lewis et al. (1976)

found that, compared to families without a symptomatic adolescent,

families with an adolescent problem had less involvement with and

more suspicion of other families, used distancing communication

mechanisms, and had reduced spontaneity and lower levels of personal autonomy. Steier et al. (1982) also found that families

with drug addicts were more rigid in their communication patterns

and alliances than matched families without an addict.

To reduce adolescent problems, family systems therapists attempt

to change some of the above family characteristics through: (a)

gaining access and influence in the system, (b) interrupting the

reciprocal relationships between the dysfunctional family characteristics and the adolescent problems, and (c) establishing new

family characteristics to interact with new adolescent behaviors

(Szapocznik et al. 1984). My categorization of techniques that

are commonly employed in family systems research to test the above

concepts follows, along with recent findings regarding their

effects.

TECHNIQUES

Gaining Access and Influence in the Family System

Introduction to treatment. Typically, one family member seeks

help, motivated by a combination of (a) personal dissatisfaction

with one member's behavior, (b) a sense of powerlessness regarding

changing this behavior, and (c) fear of negative consequences if

it does not change. For Stanton et al. (1982), adult male methadone maintenance patients were their initial contacts, and the

challenge was persuading them to allow a therapist to contact

their parents. Adolescents typically enter treatment after a

mother makes the initial telephone call in search of a theraoist

to whom the family can transfer full responsibility for helping

their adolescent. That there is still a need for techniques to

gain access to family systems is demonstrated by the Foote et al.

1985) report that onlv 15 percent of the familv members who

called their clinic about adolescent problems actually entered

family therapy.

Stanton et al. (1982) were able to recruit 70 percent of the adult

addicts' families for family therapy through applying 21 basic

principles outlined in their book, including: (a) the therapist

contacts the family within 3 days of obtaining permission and delivers a nonblaming message to each individual; (b) the rationale

for family treatment is presented in such a way that a family member's refusal would be tantamount to stating that he or she wants

the addict to remain symptomatic; (c) the therapist is given

strong incentives for recruiting the family. In one-fourth of

40
Stanton et al.'s cases, home visits were made to recruit families.

In one particularly difficult case, the recruitment efforts took

30 days and included 4 contacts with the adult addict, 24 contacts

with other family members, and 15 talks with the addict's drug

counselor.

In an ongoing study, Joanning et al. (unpublished) are testing the

use of a broader system, the whole community, in recruiting families. Rather than having just one therapist conduct all the recruitment efforts, they are training teachers, judges, and police

officers to support the therapist in persuading families to enter

treatment.

Joining the family. Since the family is viewed as a system with

boundaries, simply sharing a therapy room is not presumed to be

sufficient to provide enough access to analyze and influence a

family system. Thus the family system therapist joins the family

(a) physically, by arranging him- or herself in its midst, (b) empathetically, by demonstrating and accepting each family member's

goals and values, and (c) contractually, by promising that if the

family will engage in therapy for a specified, limited period of

time, the therapist will help it reach those goals (Kaufman 1984).

In addition, Joanning et al. (unpublished) are testing the effects

of having the therapist in regular telephone contact with the

family between sessions, attempting to obtain more information and

change dysfunctional patterns that interfere with treatment.

Enactment. Since the unit of analysis in systems theory is the

whole system, the predominant family assessment technique is for

the therapist to direct the family to interact during the session

in diagnostic ways (Szapocznik et al. 1983). The therapist observes, and at times interacts, to discover recurring behavioral

sequences, alliances, unspoken family rules, etc., that are maintaining the status quo and may, at the same time, be maintaining

the adolescent's problem.

Interrupting Dysfunctional Family System/Behavior Relationships

Focusing on concrete behavior. Stanton et al. (1982) report that

when families initially appear to agree about family rules,

attempts to elicit a consensus on specific details often reveal

hidden disagreements and dispel the myth of family harmony. They

found, for instance, that weekly urine analysis results upset the

family status quo, preventing the family from denying or sidestepping drug use.

Reversals. Family systems therapists can direct family members to

react, during a session or between sessions, contrary to their

usual way. This direction, coupled with whatever new behavioral

sequences occur in the family as a result, may be sufficient to

break recurring dysfunctional patterns (Szapocznik et al. 1984).

41
Reframing. The therapist can explain a behavioral sequence or

family characteristic in a new, more positive way that is, nevertheless, compatible with the family's value system (Kaufman 1984).

This new interpretation theoretically prevents the family from

continuing to interact in their usual way without awareness.

Intensifying. The therapist can choose an issue that evokes some

minor emotions that everyone in the family acknowledges, such as

irritation over shoes being left in the family room, and focus on

the issue until it becomes so important that the family chooses to

deal with it (Szapocznik et al. 1984).

Paradoxical instruction. When the family is continuing a dysfunctional interaction despite direct attempts by the therapist to

change it, the therapist can try the indirect approach, instructing the family to continue to engage in the dysfunctional interaction and to slow their change process. The symptoms then

theoretically become controllable instead of uncontrollable, and

the family becomes able to change them if they want to (Kaufman

1984).

Home Detoxification, Probation, and the Community Network Approach

If the above techniques have not reduced the adolescent drug use,

Quinn et al. (submitted for publication) report using larger societal systems to interrupt the family's interactions. The therapist arranges for teachers, school officials, police and probation

officers to support the family's goals in their interactions with

the adolescent. This could include placing the adolescent on probation if the drug use continues, and home detoxification where

the adolescent is watched 24 hours a day to assure that no drugs

are taken. The involvement of outsiders theoretically changes the

system within which the family interacts and, thus, supports new

family behaviors.

Establishing New Family System/Behavior Relationships

Restructuring techniques. After the family system has been destabilized, several techniques are used to direct the system to

reform in specific, health-producing ways. Boundaries within the

system are clarified by establishing rules such as (a) allowing

family members to finish talking before someone interrupts them,

(b) prohibiting members to speak for each other, (c) establishing

some rights to privacy for the adolescent, and (d) separating the

parents from their children for discussions about limit setting

and marital problems (Kaufman 1984). Boundaries around the system

are changed to keep family crises within the family for resolution

and to connect the family with natural support systems outside

(Stanton et al. 1982).

Family members are directed to change not only their distance from

one another but also their interdependencies, so that the enmeshed

relationships become more differentiated and the disengaged, more

involved (Szapocznik et al. 1984). Therapists endeavor to change

42
behavioral sequences through enactment during sessions and through

assigned homework tasks in the "real world." Resistance to these

directions may be dealt with through paradoxical instruction

(Stanton et al. 1982). Finally, the therapist disengages him- or

herself from the family system by scheduling the final sessions

increasingly farther apart.

Standards for the new structure. Family systems theorists use

normal developmental stages as guidelines for restructuring dysfunctional systems, so that they can be more health producing.

For instance, for adult male methadone maintenance patients,

Stanton et al. (1982) set independent living as a goal and helped

their parents move the identified patients out of their homes.

Conversely, Kaufman (1984) reports that parents of young adolescents are encouraged to set limits on their children's freedom.

Findings

Research guided by family systems theory investigates the effect

of family therapy interventions primarily on family system characteristics and, secondarily, individual members' problems.

Although empirical testing of family systems assumptions is relatively recent, findings have been obtained about the effect of

both global interventions and specific components of those

interventions.

Effects of Family Recruitment Efforts

The results indicate that a great deal of outreach effort must be

expended to gain access to the family system of a client with substance use problems. Evidence for this conclusion comes from a

comparison of the percentage of families, with a problem user who

made inquiries, that came into treatment with Foote et al. (1985)

(20 percent) or Stanton et al. (1982) (70 percent). Reports about

the techniques that produced such relatively high engagement rates

are more anecdotal than systematic at this point; thus, more research into the components that heighten engagement must be done.

Factors to be investigated include: (a) delivery system variables, such as speed with which the family is contacted after the

initial inquiry and the incentive system for therapists regarding

the number of families recruited, and (b) therapy variables, such

as the amount of family commitment required and attitudes communicated regarding the family's blame for the problem.

Effects of Global Interventions Guided by Family Systems Theory

Research from the family systems perspective has produced evidence

that such interventions can be more effective than traditional

individual approaches, both in changing family function and in

changing dysfunctional behavior of an individual member. Stanton

(1979) reports, for instance, that Hagglund and Pylkkanen found

that adding family therapy to individual and group therapy, for

adolescents just released from residential treatment, resulted in

the direction of family aggression moving away from the identified

43
patient toward other objects. In addition, 56 percent of the

adolescents in family therapy reported having better relationships

with their environments. Sixty percent reported cessation of drug

use, and 12 percent reported reduced use. Sixty-four percent of

the youths whose families were in family therapy also became gainfully employed.

Szapocznik et al. (1983) observed healthier family structure, less

blaming of the adolescent, better conflict resolution capacity,

flexibility, more appropriate distances, and more advanced developmental stages in families who had had from 4 to 12 sessions of

Conjoint Brief Strategic Family Therapy for adolescent substance

abuse. Families continued to improve on all these dimensions

through followup. The families and the identified patients (IPs)

also reported increased family expressiveness and moral-religious

orientation by termination. In addition, the IPs reported overall

reductions in delinquent behavior and, specifically, drug use at

termination. Although at 6- to 12-month followup, drug use and

other delinquent behaviors were beginning to return, the levels

were still significantly below pretreatment.

While neither the Hagglund and Pylkkanen (Stanton 1979) nor the

Szapocznik et al. (1983) research had nonfamily treatment controls, Stanton et al. (1982) did have appropriate controls. They

found that three different intensities of family intervention,

including a relatively weak weekly family trip to the movies, all

produced less drug use, more autonomous living, and fewer deaths

for adult IPs and a higher percentage of days employed or in

school than the traditional treatment.

Effects of Paying the Family for Clean Urines and Attendance

With their three intensities of family treatment, Stanton et al.

(1982) began to investigate the differential impact of different

components of treatment. Paying a family for increasing the number of drug-free days of their adolescent enhanced significantly

the treatment's impact on drug use but did not affect the number

of days at work or school relative to other family treatments. A

separate analysis, however, showed that family attendance at sessions was positively affected (Stanton et al. 1982). In the

absence of the incentive pay, seeing the family for systemsoriented therapy had a greater effect than showing educational

movies.

These results are tantilizing and lead to more questions. Urine

testing, for instance, is a component of all interventions used by

Stanton et al. (1982) and Joanning et al. (unpublished). What

role does this treatment component play? In addition, of the

techniques used in systems-oriented family therapy, which ones are

necessary and/or sufficient?

44
Effects of One-Person Family Therapy

Szapocznik et al. (1983; Szapocznik et al. 1986) carefully studied

how necessary it is to involve the whole family in systemsoriented therapy and obtained some challenging results. Not only

could systems-oriented therapists working solely with one family

member (usually the adolescent) obtain results as positive as a

therapist working with the whole family, but some indicators at 6-

to 12-month followup suggested that the family and adolescent

might do even better if seen alone most of the time. While adolescents seen with the family were beginning to engage in some

delinquent behavior and drug use again at followup, adolescents

seen in One-Person Family Therapy were continuing to reduce their

drug use at followup and saw their families as more cohesive and

less controlling after followup than before. More research into

these interesting effects needs to be done. A therapist manual is

available to facilitate replication (Szapocznik et al. 1985).

Effects of Reframing and Paradoxical Instruction

Other than paying for attendance, clean urines, and the number of

family members involved in treatment, the relative efficacy of

most of the myriad other components of family systems therapy'have

not been investigated experimentally. Interestingly, the combined

efficacy of two of the components have been demonstrated scientifically in work apparently guided by the other predominant family

paradigm--behavioral theory. Kolko and Milan (1983) found that

the addition of reframing and paradoxical instruction to a modified token economy intervention reduced previously intractable

drug use, school failure, and absenteeism problems, suggesting

that the techniques can be effective even when used by therapists

without family systems orientation.

CONCLUSIONS

Substantial knowledge has been developed recently in investigations of family systems assumptions about adolescent substance

abuse. Some types of family interactions which occur with substance use have been discovered, and certain service delivery

system variables which increase family participation in treatment

have been found. Various effects of family system therapy and its

components upon family interactions and adolescent behavior have

been demonstrated.

As Kaufman (1985) points out, however, many theory-based questions

remain. It is not known, for instance, whether the observed differences between families with and without substance abusers precede or follow the substance abuse. Many of the effects that

family systems therapy is assumed to have upon family characteristics are yet to be demonstrated, and finally, many of the postulated interconnections between family characteristics and

adolescent substance use have yet to be validated.

45
BEHAVIOR THEORY

Behavior theorists view all behavior as a function of: (a) the

consequences the behavior produces, (b) competing behavior/consequences relationships, (c) the individual's learning history, (d)

current state, and (e) genetic endowment (Skinner 1953). Thus all

adolescent behavior, including drug use, is also seen as a function of past and present environmental and genetic variables. A

particular behavior is considered to be understood in the behavioral paradigm when enough of its antecedents and consequences are

known to permit modification of behavior through manipulation of

controlling factors. Consequently, since observable environmental

events are eminently more manipulable than an individual's genetics, history, or current state, behavior researchers choose to

explain as much behavioral variance as possible through its

relation with environmental variables.

The basic units of analysis for understanding how family variables

affect adolescent problems are the functional relationships, or

contingencies, among (a) discrete adolescent behaviors, (b)

family-related consequences of the behaviors, and (c) antecedents

that signal what consequences are in effect. Some concepts which

behavioral theorists use to describe salient relationships are:

(a) positive reinforcement, (b) negative reinforcement (including

escape), (c) schedules of reinforcement, (d) punishment, (e) discriminative stimuli, (f) establishing operations or setting

events, (g) avoidance, (h) extinction, and (i) rule-governed

behavior (Kantor 1959; Michael 1982; Skinner 1953; Skinner 1969).

Correlational support for the behavioristic notion that adolescent

problems can be a function of antecedents and consequences in the

family environment comes from Reid et al. (1982). In families

with children exhibiting behavioral problems, they observed both

excessive aversive parent-initiated behavior toward the child

(antecedents) and weak or ineffective consequences. Alexander

(1973) found parents of adolescents with problems doing more

blaming, evaluating, and preaching (vs. discussing) than nondistressed parents. Another type of antecedent--vague or interrupted commands with which a child cannot comply--was found to

covary with child behavior problems by Forehand et al. (1986).

Furthermore, in response to family disagreements such as arguments

about curfew, families with drug-abusing adolescents tend to

change the topic and discuss areas of agreement significantly more

often than do other families, thus precluding constructive problem

solving (Mead and Campbell 1972).

That environmental variables can affect drug use directly is clear

from research with adults by Bigelow et al. (1976), Hall et al.

(1979), McCaul et al. (1984), and Stitzer et al. (1982). Each research group decreased drug use by modifying specific antecedents

and/or consequences of discrete instances of drug use. Drug use

was punished, nonuse was reinforced, or the amount of effort required to obtain drugs was increased.

46
Thus, to reduce adolescent problems, behavior family therapists:

(a) analyze what functional relationships each problem behavior

appears to have with antecedents and consequences, (b) select one

target problem behavior which is measurable and appears to be

contingent upon modifiable family antecedents and/or consequences,

(c) record the base rate of that behavior per unit of time, (d)

change the therapist-controlled environment such that the parents

will change the hypothesized family-related antecedents and/or

consequences of the targeted adolescent behavior, (e) record the

impact of environmental changes on the targeted behavior, (f)

select another adolescent problem and repeat steps c through e,

(g) change the therapist-controlled environment such that parents

will generalize and maintain their new behavioral antecedents

and/or consequences and generate their own ideas about how to

change other contingencies after they no longer see the therapist

regularly. In other words, behavior family therapists help parents change their own behavior in order to change their adolescents' behavior. My categorization of the methods and content

which behavior family therapists use to change parent and adolescent behaviors follows, along with findings regarding their

effects.

TECHNIQUES

Behavioral Assessment

Functional analyses. Gordon and Davidson (1981) describe thoroughly what techniques behavior therapists use to analyze adolescent problems. Briefly, by combining interviews with both the

parents and adolescents, behavioral and reinforcement checklists,

and analogous and naturalistic observations during the therapy

session both at home and at the adolescent's school, potential

target behaviors along with potential controlling antecedents and

consequences are specified. Parents and adolescents typically

begin by discussing only global nonbehavioral problems and blaming

each other. The therapist not only respectfully prompts and

reinforces nonblaming responses about observable stimulus/

response/reinforcement relationships, but also observes salient

correlated parent and child behaviors such as self-deprecatory

comments, inaccurate problem reporting, and expressions of dissatisfaction with therapy (Wahler and Fox 1982). Griest et al.

(1979), for instance, found that mothers' depressive behavior

tends to be more correlated with their reports of child behavior

than is the actual child behavior.

Unseen problem behaviors, such as stealing and drug taking, can be

defined so that they are observable (Chamberlain and Patterson

1984). Stealing can become "taking or being in possession of

something that does not belong to you." Drug use can become

"money disappearing unaccountably," "sleeping at unusual times,"

"smelling pungent," "not making focused eye contact," "possessing

paraphernalia," or "being in the company of known drug users."

47
Another approach to analyzing unseen problem behaviors is to

substitute similar or functionally dependent behaviors that are

observable (Reid et al. 1982). Since drug use, for example, often

occurs on school days and lowers school performance (Pandina and

White 1981; Pandina et al. 1981), measurements of school performance can be useful substitutes for unseen heavy drug use.

Gordon and Davidson (1981) also describe criteria behavior therapists use to select target behaviors. Since adolescent behavior

change usually depends on parent behavior change, one of the initial criteria for target behavior selection is that the parents

are concerned about the behavior. The greater the concern, the

greater should be the parents' participation in treatment. Other

criteria are: (a) the behavior can be directly observed by the

parents; (b) the behavior has a high frequency, or parents desire

a high frequency; and (c) the behavior has educational or social

significance.

Parent Training Methods

After selecting target behaviors, therapists select methods and

content to influence parent behaviors. Behavior family therapists

work more directly on parental than adolescent behaviors--not

because they assume that parents cause adolescent problems, but

because parents have access to many family-related antecedents and

consequences of the adolescents' behavior (O'Dell 1985). Thus,

through judicious application of these events, the parents can

modify the child's behavior.

Common behavioral methods which are used both singly and in combination to influence parent behaviors include:

Providing reading material. Giving parents pretested books and

brochures and monitoring subsequent behaviors has proven effective

in reducing children's antisocial behavior (Green et al. 1976),

inappropriate mealtime behavior (McMahon and Forehand 1978), and

disruptive shopping behavior (Clark et al. 1977). Several empirically based parent manuals have been produced by behavior therapists to be used alone or in combination with other behavior

change techniques (Becker 1969; Blechman 1985; Miller 1975;

Patterson 1971; Patterson and Forgatch, in press).

Instruction. In combination with other methods, informal oral

instruction is probably the most commonly used behavior change

method in behavior therapy (O'Dell 1985). There is evidence that

individualized, interactive instruction is more effective in

changing parent and child behaviors and producing parent satisfaction than group didactic instruction (Eyberg and Matarazzo

1980). Microanalyses suggest, however, that discrete episodes of

informal instruction during therapy sessions can produce contingent momentary noncompliant responses on the part of parents

(Patterson and Forgatch 1985). These findings will be discussed

subsequently in the context of the effects of other therapist

behaviors.

48
Modelling. Modelling--teaching new parent behaviors by demonstrating their desirable effects--is a particularly effective

behavior change methodology (Nay 1975). Perhaps modelling is

superior to written and oral presentations because it communicates

nonspecific components of the new behavior, such as affective

components (Alexander and Parsons 1973). Videotaped modelling

appears to be as effective as live modelling in teaching basic

skills (O'Dell 1985).

Prompting, shaping, and behavioral rehearsal. While parents are

interacting with their adolescents in the therapist's presence,

the therapist can prompt and shape the parents' behavior by coaching and praising successive approximations of the new antecedents

and consequent relationships (Gordon and Davidson 1981). Wahler

(1969), for instance, went into homes and prompted and shaped

mothers' differential reinforcement and punishment skills. If

used to change parents' verbal and attending behavior during therapy sessions, prompting, shaping, and behavioral rehearsal can

produce rapid parent behavior change (Guerney, unpublished).

Providing reinforcement. The therapist can provide positive and

negative consequences to increase or decrease specific parent and

adolescent behaviors. Family attendance at therapy sessions is

extremely important for effectiveness, and, thus, behavior family

therapists provide positive reinforcement. Contingent upon only

attendance, most behavior therapists provide praise, a congenial

setting, and respect by asking the family members for advice, involving them in decision making, and treating them like cotherapists. Patterson et al. (1975 also provide telephone inquiries

three times a week. Besides phone calls, Szykula et al. (1982)

provide home visits which are gradually attenuated after attendance is established.

Rinn et al. (1975) provide small fee reimbursements for attendance; Peine and Munro (unpublished) do so for punctuality. Gordon

et al. (1979) refund a fee deposit for attendance and completion

 of homework. Other Incentives reported are prizes (Muir and Milan

1982), therapist time (Eyberg and Johnson 1974) and selfdisclosure, and prompt feedback about improvement in target behaviors (Gordon and Davidson 1981). Recall that this procedure

was incorporated by Stanton and Todd in traditional family

therapies in the form of explicit payment.

Not only has positive reinforcement improved session attendance

(Szykula et al. 1982) and homework completion, but also parent

satisfaction with the whole intervention (Gordon et al. 1979).

Only one study found a negative effect along with the positive

ones: Blechman and Taylor (unpublished) report that payment for

attendance and homework completion decreased performance maintenance and generalization as compared to mere social reinforcement.

Assigning homework. Asking family members to practice between

sessions the skills they have learned and to report their results

at the next session is a common behavior therapy practice to

49
increase the probability that changes will occur outside the therapy sessions. Few families, however, comply automatically.

Therefore, Guerney (unpublished) has developed a technology utilizing both rehearsal and reinforcement to teach families to do

homework. It is generally assumed that homework is effective, but

Foster et al. (1983) report that in at least one parent training

study it decreased generalization and maintenance. They speculate

that assigning homework can put home behavior change under so much

therapist control that the new behavior disappears when the therapist does.

Parent Training Content

Through the above methods, behavior change principles and skills

are taught to parents and family members, both singly and in combination. To help therapists choose which principles and skills

to teach, Blechman (1981) has developed an algorithm for matching

content to the situations which families present.

Parent contingency management skills. Because most parents initially assume that the adolescent is the sole cause of his or her

own problems, the first concept taught is that most behavior is

learned through interaction with the social environment, which

leads to a reinterpretation of the cause (Nichols 1984). Once it

is clear that the behavior family therapist is not going to "fix

the child" but help the parents instead to "fix the environment,"

parents ask what they can do. Skills taught include: (a) pinpointing behavior, or describing exactly when, where, and what the

adolescent does that concerns the parent, (b) discriminating and

reporting accurately when (and when not) the defined behavior

occurs, (c) analyzing the behavior's antecedents and consequences,

and (d) changing the behavior's consequences. To change the consequences, parents are taught to: (e) state the new rules to the

adolescent in a calm, matter-of-fact manner, (f) reduce the frequency of their demands, commands, and nagging, (g) consistently

praise or provide a tangible reward for desirable behavior, and

(h) consistently punish or withdraw attention or rewards for undesirable behavior (Gordon and Davidson 1981).

Each of the above skills is difficult and may need to be taught

separately. For instance, in their training manual, Patterson et

al. (1975) warn therapists that many parents do not know how to

make eye contact, label the target behavior, and state, just once,

what the consequence is with appropriate expressions on their

faces. Equally complex are the skills involved in changing the

antecedents of target behaviors, reducing commands, demands, and

other aversive controlling stimuli.

Communication skills. Parents and adolescents often nag and shout

at each other when they have no other means of influencing each

other. Through communication training, they can learn more desirable ways to influence each other. Specifically, Klein et al.

(1977) taught family members to: (a) state clearly what they want

and (b) state their understanding of what other family members

50
want. Guerney (1983) views communication training, which he calls

Relationship Enhancement, as "teaching people to gain...control

over what had previously been... reflexive interpersonal behaviors." He sees the skill as so important in problem resolution

that his training manual calls for 4 hours of basic communication

skills practice before even minor family disagreements are discussed (Guerney, unpublished).

Problem-solving skills. Once parents and adolescents have communicated what they want from each other, contingency management

approaches are not always appropriate or effective. At that stage

in their child's development, parents often want the child to

develop good independent decision-making skills instead of merely

complying with their wishes. Further, even if the parents are

still seeking compliance, they often cannot use contingency management techniques because most of the adolescents' contingencies

and consequences are out of their direct control. Another typical

barrier is disagreement between the parents regarding what and how

to discipline. Consequently, the therapist teaches the whole

family problem-solving skills. Then both the parents and the

therapist can model them for the adolescent.

Robin and Foster (1984) describe problem solving in detail.

Foster’s (unpublished) training manual spells out the logical

progression of communication components that families are taught

to reach an agreement about a specific problem: (a) defining the

problem (as a dissatisfaction) concisely without accusations, (b)

"brainstorming" a variety of alternative solutions, (c) evaluating

the costs and benefits of the most popular solutions and negotiating a solution that maximizes benefits and minimizes costs for

everyone involved, (d) specifying the details of the implementation agreement, including what will happen if difficulties arise.

Contingency contracting skills. A contingency contract is a written document detailing specific behaviors to be changed and their

reinforcement arrangements that have been agreed upon by members

of the family (Stuart 1971). It should be accompanied by a system

to record at appropriate intervals whether or not behaviors

occurred. Preparing a contingency contract requires all the above

listed skills, contingency management, communication, and problemsolving skills. Contracts are particularly well-suited for adolescent problems because they specify that every member in the

family, including the adolescent, will get something they want

through compromise (Nichols 1984).

Therapist manuals by Alexander and Parsons (1982) and Barton and

Alexander (unpublished) spell out family contingency contracting

training procedures in detail. To guide families through their

initial contract formation and to assist them in maintaining and

generalizing the skills, Blechman (1977) has developed a board

game that therapists can teach them to play and then give families

to take home.

51
Self-management skills. Often parents and adolescents demonstrate

the above skills consistently when they are prompted by the therapist but fail to do so without prompting. One approach to this

situation is to teach parents and motivated adolescents how to

anticipate on their own when opportunities for performing their

new behaviors will arise and monitor their own new behaviors.

To increase mothers' attention to appropriate child behaviors,

Herbert and Baer (1972) taught mothers to use a golfer's wrist

counter to monitor the number of episodes of appropriate attention

they gave for their child's behavior. Csapo (1979) and Wells et

al. (1980) added self-reward to the behavioral sequence, teaching

parents to give themselves rewards such as a coffee break when

they provided appropriate consequences for their children's behavior. McCrady and Abrams (unpublished) have written a therapist's

manual for training spouses in self-management, and Marlatt and

Gordon (1985) have developed procedures for single adults.

Generalization and Maintenance

Even though a major reason for training parents to change their

children is to enhance generalization of those changes across

time, settings, behaviors, and siblings, empirical evidence indicates that transfer of treatment effects seldom occurs without

specific programming. Consequently, behavior family therapists

must attend to controlling variables outside the session, too

(Gordon and Davidson 1981; O'Dell 1985).

Family-based reinforcement. Kelley et al. (1979) specifically

taught spouses to reinforce each other's new child management

behaviors in the same way that they were taught to reinforce their

child's positive behaviors. Rabin et al. (1984) added explicit

training in positive affective behavior to problem-solving training to maintain the latter. Generally, training parents to support each other comes after training them to manage their

children, since their first concerns are about the children

(Gordon and Davidson 1981).

Often, however, parents with adolescent problems do not increase

their supportive behaviors for each other, even when they are

modelled, prompted, and shaped. In his comprehensive therapists'

manual, Miller (1975) lists the possible variables that may be

operative in such training failures and, thus, need behavior family therapists' attention. There may be interpersonal demands,

aversive stimuli, and distractions of which the parents may not be

aware that interfere with the parents' using their new skills.

Parents may have unreasonable, absolutistic thoughts about how

teens act or how parents cooperate that lead to unrealistic goals,

attributions of malicious intent on the part of their spouse or

child, and/or self-blame. Parents may also be uncertain about

whether or not their spouse will stay in the marriage.

To train mothers to be more aware of aversive interpersonal stimuli to which they respond aside from their children's behavior,

52
Wahler and Graves (1983) and Griest et al. (1982) discuss actual

coercive exchanges that mothers have had with relatives and other

adults. Wahler (unpublished) also uses "redirects" in conversations with mothers who are not aware of the impact upon them of

these non-child-related aversive "setting events." He continually

asks, "What else was going on (beside your child's being 'rude')?"

and "Tell me more." Wahler is currently testing whether or not

such treatment will result in fewer child-directed aversive

responses on the part of the mothers.

Identification and challenging of unfounded thoughts, such as

"Disapproval means our relationship will end," that lead to ineffective, rule- governed parent behavior were undertaken by Robin

and Foster (1984), Alexander and Parsons (1982). and Barton and

Alexander (1981) through examination of actual interpersonal contingencies. Patterson et al. (1975) and McCrady and Abrams

(unpublished) describe marital contingency contracting to enable

therapists to help spouses elicit more desirable responses from

each other.

School-based reinforcement. Another extrasession source of controlling variables is the school. Positive changes in an adolescent at home do not necessarily correlate positively with changes

at school (Forehand et al. 1981). To both assess the school variables and arrange for more reinforcement of new parent and adolescent behaviors, therapists can hold school conferences as

Patterson et al. (1975) describe in their manual. The outcome

could be weekly report cards (Bailey et al. 1970) or Progress

Reports, as most schools call them, where teachers send parents

regular reports about targeted school behaviors that are consequated at home. Alternatively, school personnel can be trained to

provide consequences for targeted behaviors in school with the

knowledge and support of parents (Bry 1978; Bry 1982; Bry and

George 1979; Bry and George 1980). Stanley et al. (unpublished)

have written a manual to train school personnel in the latter

methodology.

Community-based reinforcement. Behavior family therapists also

mobilize non-school-based community reinforcements for new parent

and adolescent behaviors. For instance, when Wahler (unpublished)

found that some parents did not maintain new behaviors outside the

clinic, he proposed training friends to provide the same "redirects" outside therapy that therapists provide in therapy.

Csapo (1979) provided community-based reinforcement for parents by

training them in a group and prompting parents to reinforce each

other weekly in group meetings and call one another daily to ask

how new contingencies were working. Szykula et al. (1982) also

arranged for parents to receive babysitting, housing, legal, and

medical attention if needed.

For adolescents, family-based interventions have included coordinated job training placement and social reinforcement for good

performance (Barton et al., submitted for publication). At least

53
two technologies have been developed to help recovering substance

abusers obtain community-based reinforcement in employment settings (Azrin and Basalel 1982; Hall et al. 1981).

Booster sessions. The demonstrated effects of intermittent reinforcement on resistance to extinction (Ferster and Skinner 1957)

have lead behavior therapists to use gradual reductions in the

number of booster sessions over time to enhance temporal generalization of positive behavior changes instead of offering timelimited therapy that ends abruptly Gordon and Davidson 1981). In

fact, because of previous findings that the positive effects of

contingency management training do not last for young people who

steal, Patterson (1982) does not terminate treatment for such families but merely lengthens time between contacts. Another type of

booster procedure is to maintain telephone contact with families,

providing retraining when necessary (Patterson et al. 1973).

FINDING

As stated above, behavioral researchers seek to understand adolescent behavior problems through their control. The goal of

programmatic research, then, is to reduce problem behaviors progressively through the introduction of increasingly more effective

behavior change technologies. Below are findings regarding techniques that have been shown to reduce adolescent behavior problems

to date.

Effects of Combinations of Techniques

Through family contingency contracting, communication training,

and homework assignments, Alexander and Parsons (1973) reduced

adolescent problem behavior, first over an 18-month period, and

then for up to 3 years (Klein et al. 1977). Robin et al. (1977)

combined communication and problem-solving training to reduce lying and interrupting by the adolescent and the number and intensity of arguments reported by the parent (Robin 1981). Foster et

al. (1983) also reduced number and intensity of parent-child disputes using similar techniques and maintained the changes through

a 6- to 8-week followup.

Two behavioral family researchers have demonstrated some control

over adolescent substance use. Fredericksen et al. (1976) combined problem solving, contingency contracting, and booster telephone calls to reduce both parent and adolescent complaints about

the family and reduce drug use throughout a l-year followup. Bry

et al. (1986) combined problem solving, communication training,

and school conferences to reduce drug use and school failure by

the end of a 15-month followup (figure 1).

None of the above studies, of course, demonstrated perfect control. Types of inter- and intrasubject variabilities include

subjects' not responding to treatment at all, varying degrees of

54
FIGURE 1. Long-term effects of family communication and problem-solving trainging on adolescent grades,

drug use, and their correlates

NOTE: Solid lines connect grade point averages, number of days without drug use, mean daily packs of cigarettes smoked. and number

of days without alcohol use for three 15- to 16-year-olds during each report card grading period (73 days) before, during, and

1/4 years after their families received targeted communication and problem-solving training. Dotted lines connect correlated

indices of subjects’ questionnaire responses about their school and home environments.

SOURCE: Bry et al. 1986, Copyright 1966, Haworth Press, Inc.
response, varying amounts of delay before response, varying

durations of response,

followup.

and problem behavior recurrences during

Potential Additional Controlling Variables: Correlates of Problem

Behavior Change

When behavior control is less than perfect, behavioral researchers

examine correlates of behavioral variability for additional potential controlling variables (Sidman 1960). Findings suggest that

less than optimal outcomes are due to less than optimal (a) family

communication, consequating, and problem-solving behaviors, (b)

community and school variables, and (c) therapist behaviors.

Family behaviors. When Alexander and Parsons (1973) examined

which family communication variables correlated with juvenile

delinquent recidivism, regardless of type of treatment, they found

that (a) equality of speaking time among family members, (b) proportion of talk time to silence, and (c) frequency and length of

interruptions all correlated negatively with amount of arrests.

In another study, Alexander et al. (1976) found that families with

better treatment outcomes had higher ratios of supportive to defensive (e.g., sarcasm, blaming) communications.

Robin et al. (1977) found that as the use of three of the components of problem-solving behavior on the part of both adolescents

and parents increased, the reports of adolescent behavior problems

decreased. During other effective interventions, Robin (1981)

found more improvement in parents' problem-solving skills than in

the adolescents'; Foster et al. (1983) found that the adolescents

reported more improvement in their mothers‘ than their fathers'

behaviors. Bry et al. (1986) found that decreases in an adolescent boy's drug use and school failure were accompanied by increases in his reports of positive interactions with his father.

Patterson and Fleischman (1979) actually observed more positive

child-parent exchanges as behavior problems reduced. More specifically, Taplin and Reid (1977) report that (a) maternal aversive

consequences following deviant behavior, (b) maternal aversive

consequences following prosocial behavior, and (c) maternal positive consequences following deviant behavior decreased as behavior

problems decreased. Taken together, correlational findings suggest that greater control over the adolescent‘s behavior may be

gained by training the parents more specifically to (a) reduce

sarcasm and blaming, (b) provide nonaversive appropriate consequences, (c) discriminate prosocial from deviant behavior, (d) use

all the problem-solving components, (e) increase positive childparent exchanges, (f) increase interruptions for clarification and

feedback, and (g) acknowledge behavioral improvements.

Communmity and school variables. Wahler and Graves (1983) discovered that aversive exchanges that isolated mothers have with

adults outside the family (e.g., welfare workers, relatives) early

in the day appear to function as setting events (Kantor 1959) for

56
aversive parent-child exchanges later in the day. Assuming that

they could not control the setting events, Wahler and Graves

(1983) investigated the relationship by training isolated mothers

to identify the setting events that were increasing their aversive

interactions with their children. They found that as mothers

reported more details about aversive exchanges outside the parentchild relationship, their aversive communications (e.g., blaming)

about their child decreased.

Bry et al. (1986) measured some promising school-based correlates

of problem behavior change. As adolescents' drug use and school

failure returned during followup, so did their reports of inappropriate, inaccessible, and unclear contingencies at school. As

their drug use and school failure decreased again, their reports

about school improved (figure 1). Thus, other potential sources

of variables controlling parent and adolescent behaviors are in

the community and the school.

Therapist behaviors. Therapist behaviors have also been found to

correlate with changes in client problem behavior. Stuart and

Lott (1972) first observed that therapist variables affected outcome more than any other characteristic of therapy. This observation lead Alexander et al. (1976) to find that therapist behaviors

such as self-disclosures, jokes, integrations of affect and behavior (called Relationship behaviors), and directives and clear

expressions of confidence (called Structuring behaviors) accounted

for 60 percent of the outcome variance, including whether or not

clients stayed in treatment.

After Chamberlain et al. (1984) discovered that high initial

levels of parent resistance behavior (interruptions, nesative

attitudes, challenges, following their own agenda) predict early

treatment drooout. Patterson and Forgatch (1985) examined temporal

relationships'between all therapist behaviors and client resistance to see whether any therapist behaviors increased or decreased

client resistance. Indeed, when therapists supported (encouraged,

joked with the client) or facilitated ("um-humm," "sure"), resistance became less likely; when therapists taught (provided information about parenting or family life) or confronted a client

(challenged a client with disagreement or disapproval), resistance

became more likely.

That therapist behaviors are actually controlling variables was

subsequently demonstrated through an ABAB single-subject design in

which client resistance behaviors increased and decreased as the

therapist systematically presented and withdrew teaching and confronting behaviors. These findings are significant contributions

to knowledge, since client resistance behaviors typically occur

from 6.4 to 14 times per therapy session. Practical applications

are not immediately apparent, however, for other research suggests

that supportive and facilitative communications alone change adolescent behavior significantly less than when combined with teaching and confronting (Alexander and Parsons 1973; Patterson et al.

1982).

57
Effects of Single Components of Behavior Family Therapy

As systematic research continues, the following findings regarding

the effects of separate behavior family therapy techniques and

contents could suggest methods to gain greater control over

adolescent problem behaviors:

Written materials. O'Dell et al. (1980) found that adding a takehome manual to parent training eliminated previous variability in

generalization. The authors speculate that parents used the manuals at home after termination to remember behavioral principles

and solve new problems.

Interactive shaping, prompting, and rehearsal. These were found

to be more effective and attractive to parents than didactic

training (Eyberg and Matarazzo 1980).

Modelling. Alone, modelling has produced parent behavior changes

that lasted for at least 1 year (Webster-Stratton 1982) and produces such behavior changes more rapidly than other techniques

(Green et al. 1976).

Positive reinforcement. Blechman et al. (1981) found that giving

parents just 1 hour of individual attention and then calling them

to support their reinforcement of "home notes" from school produced greater consistency in their children's improved school performance and greater generalization to situations with no tangible

reinforcement than did a similar intervention without parent

reinforcement.

Instruction in behavioral management principles. For McMahon et

al. (1981), instruction in behavioral management principles proved

to increase generalization at followup.

Communication training. Relationship Enhancement, when applied

intensively (20 to 30 hours of systematic training), significantly

increases expressive and listening behavior, overall communication

behavior, reported satisfaction in the family, and changes in the

topography of both adolescent and parent communication behavior at

termination (Guerney et al. 1981) and at 6-month followup (Guerney

et al. 1983), compared with equal time spent in a discussion

group. When parent communication training is added to other parent training techniques, previously ungeneralized behavior change

can become generalized (Kelley et al. 1979). When specific training in positive affective communication is added to straight

problem-solving training, affective elements of couple communication increase, and couples report better moods (Rabin et al.

1984).

Problem-solving training. Shown to increase negotiation behavior,

parent-adolescent agreement, and the number of agreements kept

(Kifer et al. 1974), problem-solving training is rated higher in

social acceptability than are behavioral contracting, paradoxical

58
family therapy, and medication (Finfrock and Robin, submitted for

publication).

Self-management training. When added to didactic training, selfmanagement training reduced child behavior problems significantly

more than did didactic training alone or combined with social

reinforcement from the community (Csapo 1979). There is evidence

that self-management training also improves generalization.

Whereas no differences were apparent at termination, the children

of parents who received self-control training in addition to regular parent training were less deviant at E-month followup than

were children of parents who received only regular parent training

(Wells et al. 1980).

Family-based reinforcement. Techniques in family-based reinforcement have produced more positive child behaviors at 2-month

followup than has parent training without them (Griest et al.

1982). Wahler and Graves (1983) did not directly manipulate

relatives' behavior, but, by reviewing videotapes and shaping and

prompting isolated mothers to report their aversive interactions

with relatives in a more complex fashion, they reduced the frequency of behavior problems in isolated mothers' children on days

when these aversive interactions with relatives occurred. McCrady

et al. (submitted for publication) found that, as compared with

minimal or no spouse involvement, active involvement of spouses in

an outpatient alcohol treatment program decreased the amount of

drinking by patients after relapses and increased life satisfaction, marital relationship, and consumer satisfaction ratings.

School-based reinforcement. When added to family-based interventions, school-based reinforcement can have powerful and long-term

effects. Patterson (1974) added contingencies in school to contingencies at home and found that school performance improved for

those young people. As mentioned above, when parents reinforced

"home notes" from school personnel, school behavior changed for

the whole school year (Blechman et al. 1981). Conversely, Bien

and Bry (1980) and Bry and George (1979) found that providing reinforcement in school for "high risk" adolescents brought positive

behavior changes only if parents were also systematically involved

in the program.

Community-based reinforcement. When community-based reinforcements such as babysitting, housing, and legal and medical help

were added to behavior family therapy, the dropout rate for parents decreased from 46 percent to 26 percent (Szykula et al.

1982). When daily calls to parents from other parents who were

also implementing a child behavior change program were added to

parent training, Csapo (1979) found significantly greater reductions in some target child behaviors than occurred without the

community reinforcement. When job-search training, advice on

non-alcohol-related social and recreational activities, and instruction in how to establish non-alcohol-related social relationships and how to adopt a pet were added to family-encouraged

disulfiram treatment for young adult alcoholics, four different

59
indices of substance use problems were positively affected over a

6-month followup (Azrin et al. 1982). For serious adolescent

offenders, the addition of family therapy coordinated job training

and placement reduced recidivism from 93 percent to 60 percent

(Barton et al., submitted for publication).

Booster sessions. There is clear evidence that the addition of

even two 1-hour booster sessions can increase maintenance of behavior changes (McDonald and Budd 1983). In a very systematic

look at booster effects, Guerney et al. (1983) found that the

communication behavior of a randomly assigned group that received

four booster sessions in communication training at 6-week intervals continued to increase over followup, while communication

behavior in the non-booster-sessions group deteriorated.

CONCLUSIONS

Over the past 20 years, knowledge has grown about behavior therapy

techniques that affect parenting behaviors and parenting behaviors

that, in turn, affect child behavior problems. Clear training

manuals that render the techniques replicable have been tested.

Although much of the research reviewed here has focused on either

non-substance-use problems in younger children or substance use in

adults, a sufficient number of combinations and components of behavior family therapy have affected adolescent behaviors, including substance use, to establish its relevance for that age group

and problem. A great deal of variability exists, however, in

treatment effects among treatment settings, therapists, families,

and problem behaviors. The systematic process of accounting for

this variability and controlling it, particularly for adolescent

substance use, is just beginning.

To guide that process, O'Dell (1985) argues that the most likely

source of differential outcomes is variable performance of new

behaviors by parents. According to O'Dell, parent variability

could be due to, in order of importance, (1) variable levels of

participation by parents in treatment, (2) concurrent personal,

family, and community problems of the parents, and (3) parents'

failure to discriminate problem from nonproblem behaviors in their

children. Technologies exist that can affect each of these

hypothesized sources of variance, but each requires considerable

effort, consistency, and planning by the therapist. Consequently,

agency conditions that establish and maintain the most effective

therapist behaviors must be investigated.

Finally, theory-based questions still face behavior family researchers. Few studies have experimentally investigated the

assumed functional relationships between discrete changes in

parent-initiated antecedents and consequences and adolescent

problem behavior. Likewise, there have been few experimental

demonstrations of the assumed functional relationships between

therapist behavior and parenting behavior.

60
SUMMARY

There has been much discussion over the last two decades concerning the theoretical and philosophical, as well as practical merits

of the two perspectives discussed in this chapter. Both theories

recently have developed knowledge that benefits all researchers

and practitioners and are in the process of developing more.

Adherents to both orientations agree that the family and greater

social context play important roles in determining adolescent substance use. They also concur that successful interventions to

change adolescent behaviors include: (a) targeting behaviors

appropriate for the adolescents' developmental status, (b) recognizing that adolescents are seldom self-referred, and (c) utilizing the fact that parents still potentially control much in their

lives. Theoretical differences lie in choices of salient family

and adolescent variables, units of measurement, levels of scientific analysis, and notions about cause and effect. Both theories, however, currently are generating knowledge that reduces

adolescent substance use, and this bodes well for the future.

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AUTHOR

Brenna H. Bry, Ph.D.

Graduate School of Applied and

Professional Psychology

Rutgers University

Box 819

Piscataway, NJ 08854

68
Parent and Peer Factors

Associated With Drug Sampling in

Early Adolescence: Implications

for Treatment

Thomas J. Dishion, Gerald R. Patterson, and John R. Reid

INTRODUCTION

There are two directions which can be taken when addressing the

problem of adolescent substance abuse. The first (and most

common) is to develop a reasonable treatment strategy which helps

youngsters whose early lives are disrupted by excessive use of one

or many drugs. Although much has been done in this direction,

both in terms of inpatient and outpatient treatment, the theoretical model guiding such treatment often lags far behind (Hubbard et

al. 1985).

A complementary direction is to conduct careful longitudinal

research to identify antecedents and covariates of substance use

patterns, from early initiation to the actual abuse of one or more

substances. Toward this goal, the writers are involved in a

research agenda which focuses on the influence of families and

peers on the development of antisocial child behavior and substance (ab)use (Patterson et al., in press). The assumption

underlying this approach is that such developmental research will

yield findings that might, in turn, be applied in the design of

effective interventions.

The theoretical framework underlying this research has been termed

"social interactional" (Cairns and Green 1979; Patterson and Reid

1984). It is based on the fundamental assumption that progress in

the behavioral sciences can best be achieved by examining momentby-moment social interactions in terms of the individual differences. Specifically, in the study of child development up to and

through the adolescent years, it is assumed that interactions with

both family and peers are necessary points of focus with applied

implications. Such an interactional perspective provides a

rationale within which to study the changing etiological variables

as they relate to prevention and treatment effects (Dishion and

Loeber 1985; Patterson and Reid 1984; Patterson et al., in press).

This applied perspective is the direct result of over two decades

of programmatic work at the Oregon Social Learning Center (OSLC),

69
involving the development and evaluation of clinical procedures

designed for families whose children have conduct problems

(Patterson 1978; Patterson and Reid 1984). The Center provides

parent training, based largely on social learning principles,

which has been shown to affect considerable improvement in children's behavior (Patterson et al. 1982). These effects extend at

least 1 year after treatment termination (Patterson and Fleischman

1979). Recent studies demonstrate that parent training for families of adolescents who have committed at least three offenses can

reduce the rate of police contact with these youths over a period

of 2 to 3 years (Marlowe et al., in preparation). In addition,

current research efforts are directed at elucidation of the

client-therapist interaction process contributing to the family's

change during therapy (Chamberlain et al. 1984; Patterson and

Forgatch 1985).

This clinical experience of working with the families of conductproblem children and adolescents led to an emphasis on the role of

specific parenting practices in the etiology of adolescent conduct

problems, later chronic antisocial behavior, and substance use.

In turn, efforts were focused on implementation of a longitudinal

study on the contribution of family management practices to characteristics of normal and pathological development. Concurrent

relationships were demonstrated (across settings) among inept

parental discipline, negative microsocial exchanges within the

family, and the child's tendency to be physically aggressive

(Patterson et al. 1984). Similar relations between child-rearing

practices and a generalized index of the child's antisocial behavior were later found (Patterson and Bank 1985; Patterson et al.,

in press). It is hypothesized that maladaptive family management

practices have a persistent adverse impact in terms of antisocial

behavior, eventual drug abuse, and developmental lag in academic

skills, peer relations, and self-esteem. A systematic review of

the literature corroborates this hypothesis by showing that disrupted family management practices were the best predictors of

later male delinquency (Loeber and Dishion 1983).

In studying the etiology of substance (ab)use, it is important to

clarify the criteria to be addressed. Baumrind (1985) has raised

the crucial point that the varying definition of substance abuse

across studies is a serious detriment to the utility of the findings of those studies. In this research, three criteria of drug

use are defined: drug use exploration (number of drugs sampled),

patterned drug use, and drug abuse. In part, the distinction

among these three criteria is logical: youngsters must proceed

through these steps to arrive at a stage where they are using a

substance at a level that is immediately dangerous or that is

detrimental to future development. In this vein, Baumrind's

contention that drug abuse should be defined empirically--based,

in part, on research showing the immediate and long-term effects

of drug dosages on youngsters of the same age--is correct. The

results described here relate to factors influencing the preadolescents’ sampling of diverse substances. Future study of the

longitudinal cohort will permit definition of factors associated

70
with patterned drug use and patterned use of specific substances

as well as polydrug use. Finally, during late adolescence, study

of the progression from patterned use to abuse can be undertaken.

This sequential strategy for studying adolescent drug use is also

supported empirically. Several studies document the continuity

between early problem behavior and maladjustment in adolescence

and adulthood (Loeber and Dishion 1983; Robins 1966), as well as

substance abuse (Kellam et al, 1983). More to the point, early

drug use in adolescence (before age 15) is predictive of abusive

use of alcohol and other drugs in adulthood (Robins and Przybeck

1985).

Thus, we assume that a model explaining early drug exploration may

not be equivalent to the model explaining patterned drug use in

adolescence. Moreover, these models may not explain well the

movement into drug use habits more appropriately labelled as abusive. However, the predictive validity of each stage of analysis

will most likely be enhanced (Robins et al. 1977) and, therefore,

the applied utility of the findings.

ANTISOCIAL BEHAVIOR AND DRUG USE

There has been debate about the causal relation between drug use

and the commitment of delinquent acts (Clayton and Tuchfeld 1982).

The major impetus for positing that drug use causes criminal

activity comes from clinical outcome studies in which, for example, methadone treatment for heroin addiction was accompanied by

decrements in criminal activity (Chambers 1974). However, it

appears that delinquent behavior usually preceded drug use, and

epidemiological studies on substance use in adolescence definitely

corroborate this finding. For example, research by Johnston et

al. (1978) reveals that the adolescents who began using drugs the

earliest were those also engaging in behaviors such as interpersonal aggression, theft, and vandalism. Furthermore, as time

progressed and new groups of youngsters began using drugs, the

relative positions of those youngsters on a general delinquency

composite did not change. In fact, all groups decreased their

involvement in delinquent behavior as time progressed. In addition, Kellam et al. (1983) reported that, in their longitudinal

analyses, aggressive behavior in the first grade correlated with

substance use in adolescence. The best predictor of substance use

was a combination of aggressiveness and shyness in the first

grade. This supports the hypothesis of greater risk of problems

in adolescence for children with combined skill deficits and antisocial behavior (Dishion et al. 1983; Patterson 1982). These data

give rise to the hypothesis that both drug use and delinquency in

adolescence are mutual outcomes of similar circumstances. Research on predicting the onset of marijuana use (Jessor and Jessor

1975) and alcohol use (Jessor 1976), and research on the development of problem drinking (Donovan et al. 1983) consistently indicated that self-reported delinquent behavior was among the

strongest predictors of each. Similar results on the concomitant

development of drug use were reported in the followup phase of the

Cambridge-Sommerville study (McCord 1981).

71
Evidence of overlap between the development of antisocial behavior

and drug use exists, but the overlap is not perfect. This supports the view that there are probably multiple pathways leading

to drug use in adolescence (Bry et al. 1982; Elliott et al. 1985).

The alternative pathways to drug use in adolescence can be delineated by dividing a sample and examining profiles on relevant

factors. Pulkkinen (1983) followed this strategy in a longitudinal study conducted in Finland. Similarly, Dishion and Loeber

(1985) reported that youngsters who used drugs regularly (at least

once per month over a 1-year period) showed a profile almost identical to that of the nondelinquent abstainer group on the measures

of peer deviancy and parent monitoring, while those who used drugs

and had an official record of police contact for nondrug offenses

were the most pathogenic on these variables (figure 1).

DETERMINANTS OF ADOLESCENT DRUG USE

A number of factors have been suggested as causally related to

substance use in adolescence. Major factors include the child's

attitudes, such as low law abidance (Huba and Bentler 1983), and

exposure to drug use among peers and significant adults (Dishion

and Loeber 1985; Elliott and Huizinga 1983; Huba and Bentler 1983;

Noll and Zucker, unpublished; Zucker 1976). Research by Bry and

associates indicates that, as the number of risk factors increases, the likelihood of adolescent substance use greatly increases

(Bry et al. 1982). Generally neglected in the study of etiology

has been the relation of specific parenting practices to the

child's acquisition of addictive behaviors (Dishion and Loeber

1985). A model under development is directed at evaluating the

hypothesis that child-rearing practices underlie the child's

initial exploration of drug use and evolution of a pattern of

regular use.

The major problem in interpreting previous research on the role of

child-rearing factors in initiation of drug use has been dependence on the child's self-report. Dishion and Loeber (1985) (table

1) found a moderate covariation between such a generalized composite of the monitoring practice and the adolescent's use of alcohol

(r=-.36) and marijuana (r=-.43). Similarly, a measure of parent

discipline practices, based on home observer impressions across

three home observation sessions, correlated with the adolescent's

report of alcohol use (r=.29). Consistent with other studies on

adolescent drug use, a composite measure of deviant peers covaried

highly with adolescent alcohol (r=.35) and marijuana use (r=.44).

In the context of a multiple regression analysis (table 2), parent

monitoring practices did not add to the variance accounted for by

deviant peers in alcohol use, but did so for marijuana use. These

findings were consistent with the hypothesis that parent monitoring practices exert an indirect and direct influence on adolescent

drug use. The indirect effect is mediated through the child's

association with a deviant peer group. Poor monitoring of the

child is likely to increase his/her availability for deviant

peers. A similar model has been tested and confirmed with

72
FIGURE 1. Profiles of adolescent delinquent drug users compared to nondelinquent drug users and

abstainers on family management, deviant peers, and mother’s alcohol use

SOURCE: Dishion and Loeber (1985). Copyright 1985, Marcel Dekker. Inc.
TABLE 1. Bivariate correlations between self-reported substance

use and parent and peer variables for 7th- and 10thgrade adolescent males

Frequency of Use

Variables Alcohol n Marijuana n

Alcohol use:

Mother

Father

Both parents

Parent monitoring

Parent discipline

Deviant peers

-.05 130 .17* 129

-.07 96 .13a

-.07 88 .05

96

88

-.36*** 103 -.43*** 103

-.29** 61 -.12 61

.35*** 117 .44*** 116

ap<. 10

*p<.05

**p<.01

***p<.001

SOURCE: Dishion and Loeber (1985). Copyright 1985. Marcel Dekker. Inc.

TABLE 2. Multiple regressions of self-reported drug use on parent

monitoring, deviant peers, and mother’s alcohol use

for Cohort I (n=91)

Stand. a

Adjusted

Dependent Independent Beta

Variable Variable Coef. (R) R

2

R

2

E

Self-reported Parent monitoring -. 19 (.41)

alcohol use Mother's alcohol use -.01 .17 5.98**

Deviant peers .28* .14

Self-reported Parent monitoring -.26* (.52)

marijuana use Mother's alcohol use .10 .27 11.01**

Deviant peers .31* .25

a

Adjusted for estimated shrinkage under cross-validation

*p<.05

**p<.001

SOURCE: Oishion and Loeber (1985). Copyright 1985, Marcel Dekker, Inc.

correlational data on adolescent delinquency (Patterson and

Dishion 1985).

Other researchers have reported covariation between child-rearing

practices and substance use. Pulkkinen (1983) found through

74
interviews that a measure of child-centered guidance, when the

child was 14 years old, was related to the child's smoking and

drinking habits at that age and later in adolescence. However, in

the Jessors' studies, the child's report of parental control was

not found to be related to the onset of alcohol use (Jessor and

Jessor 1975) and was only marginally related to marijuana use

(Jessor 1976). Clearly, as noted by Baumrind (1985), the problem

of measuring processes must be surmounted to prevent premature

conclusions from being drawn (e.g., the contribution of childrearing practices). However, it is hypothesized that parent

monitoring practices are important, and that it is partly the

exposure to drug use among friends and parents that determines the

child's initial exploration of drugs.

In the current research, attention has focused on five family

management practices: Parent Monitoring, Discipline, Positive

Reinforcement, Parent Involvement, and Problem Solving. The focus

is on forming constructs incorporating the unique vantage point of

all social participants, including that of professional observers.

These more generalizable constructs should be more robust under

the scrutiny of both cross-validation and longitudinal analysis.

This follows from the principle of aggregation (Buss and Craik

1983) in personality theory and is primarily a measurement issue.

The relationship between the five management practices and disrupters is important. There are events that both the child and

his or her parents experience that disrupt the exercise of normal

family management (Patterson 1982; Patterson 1983). For example,

heavy alcohol or drug use by a parent could be a family disrupter

and is, thus, included in the model as an important factor for two

reasons. First, it may directly affect the child's initial exploration of drugs as the child models parent behavior and by making

the drugs more readily available. Second, heavy parent substance

use is likely to disrupt monitoring practices, as well as other

family management variables. This effect may be particularly

relevant in preadolescence, when the influence of parents on

social development may be more important than peers' influence.

Consistent with research by Krosnick and Judd (1982) and Kandel

(1973), peer substance use may be more influential in adolescence.

However, it may be premature to draw conclusions about the relative influence of parents and peers, since models incorporating

both direct and indirect influences of each have not been

adequately evaluated.

AIMS OF THE PRESENT RESEARCH

The study reported here focused on a model to explain the child's

initial sampling of various drugs. Drug exploration, as a criterion variable, has been examined in relation to the composite

indices of family management practices, family interactional processes, peer influence, and parent drug use.

75
Subject Recruitment

These data represent the first collection wave in a longitudinal

study of two cohorts. Schools located in neighborhoods with higher risk for delinquency were selected based on police arrest data,

The 15 highest-risk schools were approached to join the study for

Cohort I, and 14 agreed to be in the study. The 10 highest-risk

schools were randomly ordered, and the first 6 schools were recruited. Schools were recruited until a sample of 103 families

was obtained. This process was repeated for Cohort II, except

that the remaining 10 highest-risk schools were randomly reordered. In Cohort II, 7 schools were recruited to acquire 104

families.

Adjusting for the families not solicited, the rate of recruitment

and completion for Cohort I was 76.7 percent, and, for Cohort II,

72.2 percent. Thus, 30 of 153 families and 40 of 155 families

declined participation in Cohorts I and II, respectively.

Sample Characteristics

Table 3 contains the basic demographic characteristics of the two

longitudinal cohorts. Whenever possible, further data are supplied from more representative samples to provide an anchor for

comparative purposes. For socioeconomic status, the National

Youth Survey (Elliott et al. 1985) data were provided, since these

data reflect the distribution of families within three categories,

according to Hollingshead's index (Hollingshead, unpublished

manuscript): lower class represents categories 1 and 2; working

class represents category 3; and middle class, categories 4 and

5. The unemployment rate of 9 to 10 percent for the longitudinal

cohorts is noteworthy, even though it is not directly comparable

to the National Youth Survey sample and does not include "discouraged workers" (individuals who are no longer collecting unemployment benefits and have abandoned seeking new employment).

Inspection of table 3 reveals that the middle class in the longitudinal cohorts was underrepresented, and families with lower

incomes were overrepresented.

Data Collection Procedures

Data collection proceeded in three phases: the school phase, the

interview phase, and the home phase (Patterson et al., in press).

The school phase involved collection of school information such as

teacher ratings, peer nominations , and school records and achievement test scores. The only contact we had with the study children

in the school setting was in collecting peer nominations, which

involved groups of 4 to 12 children and required about 15 to 20

minutes of class time to administer.

76
TABLE 3. Demographic charcteristics of longitudinal study

samples

Demographic

Characteristic Cohort I Cohort II Comparative Statistics

Family SES*

Lower (1 & 2)

Working (3)

Middle (4 & 5)

Unemployed

Family Income

$O-4,999

$5,000-9,999

$10,000-14,999

$15,000-19,999

$20,000-24,999

$25,000-29,999

$30,000-39,999

$40,000+

($25,000+ total) (32%)

Family Structure

Single parent

1-2 children

3-4 children

5-6 children

Mean age:

Mother

Father

34

36

Child Achievement

WRAT reading**

(SD)

34% 28%

23% 26%

22% 26%

22% 20%

11%

21%

16%

14%

17%

8%

13%

3%

(24%)

16%

20%

17%

14%

14%

10%

6%

3%

(19%)

31%

52%

37%

12%

40%

58%

32%

11%

36

37

106.0 108.7

(13.8) (17.0)

National Youth Survey,

U.S., 1978

42%

29%

23%

U.S. Census,

Western U.S., 1979

12%

15%

15%

14%

13%

 *Holllngshead Index of Socioeconcmic Status, 1975

**Wide Range Achievement Test, mean standard score

The interview phase of data collection consisted of a visit to

OSLC. During the interview session, the parents and child were

interviewed and completed questionnaires separately, but participated together in a videotaped problem-solving task.

77
The home phase involved the collection of data In a series of six

telephone calls to the child and parent(s) separately, and three

home observations lasting 60 minutes each. The telephone reports

were structured interviews that lasted from 10 to 15 minutes per

respondent. The home observation sessions were structured to

facilitate the coding of all family members' behavior and to prevent interruptions in interaction sequences.

The format was consistent with that described by Reid (1978) for

home observations in assessing behavior change in parent training.

Observation was based on the Family Process Code (Dishion et al.

1983) which includes ongoing behavior and emotional valence with

every behavior recorded.

Obviously, the study of the longitudinal cohorts included a

plethora of measures tapping many facets of family functioning.

The approach that was used to build constructs with the longitudinal cohorts has been described as "bootstrapping" (Patterson and

Bank 1985; Patterson and Bank, in press; Cronbach and Meehl 1955).

Whenever feasible, multiple agents, settings, and methods were

used to assess every construct. The resulting score is usually

referred to as the "construct score." A 3-year pilot study (the

Planning Study) provided the opportunity to test the initial

measurement hypotheses about family management.

The following is a brief description of the composite scores used

in this study. Details of the items for each of the composites

and their specific data sources are provided in Patterson et al.

(in press).

Child Behavior Composites

Child’s drug exploration. This composite was based on parents'

and children's reports of drug use. The child scale consisted of

six items asking the child if he had ever tried cigarettes, beer,

wine, hard liquor, marijuana, or other drugs. The parents also

reported on whether the child had tried cigarettes, alcohol,

marijuana, or other drugs.

Antisocial behavior. For boys 9 to 10 years old, it was assumed

that a general score combining information concerning both overt

and clandestine noncompliance to rules would be prototypic of behaviors describing the antisocial child. This score sampled

global ratings from peer nominations, teacher and parent Child

Behavior Checklists (CBCs), and the daily telephone interview with

the parent and the child. The behaviors included in this score

ranged from fighting and arguing with siblings to more extreme

behaviors, such as stealing and vandalism.

Friends’ drug use. Information on the subject child's friends was

obtained in the child interview. The child was asked if any of

his friends used alcohol, tobacco, marijuana, or other illicit

drugs, or sold illicit drugs.

78
Academic skills. An average score was computed for each child

from parent and teacher CBC ratings of academic competence, as

well as the Wide Range Achievement Test (WRAT) and Standardized

Achievement Tests (SATS) administered in schools. The WRAT was

administered during the structured interview. SATs and WRAT

ratings were on math as well as various language arts.

Normal peer relations. School data are integral to this construct. The Unpopular Scale from teacher CBCs and Peer Nominations on friendliness and popularity were used along with the

child's self-report on making friends.

Antisocial peers. This score reflects the degree to which the

child associates with peers who commit antisocial acts. The composite consists of the child's report on peer antisocial activity,

peer nominations of children who associate with "tough kids," and

the parents' global rating.

Coercive child. Three variables were taken directly from the home

observation data that defined the child's coercive reactions to

family members. The variables were (1) mean duration of the coercive interactions initiated by the target child with his mother,

father, and siblings; (2) the likelihood of the child's initiating

a conflict (startup) given that the parents were either neutral or

positive in their immediately prior reaction to the child; and

(3) the likelihood of the child's startup with siblings. Startup

refers to the likelihood of the child's initiating a coercive

response when his sibling was previously neutral or positive.

Self-esteem Three measures based on the child's self-report are

used as indicators for this construct. Self-ratings on academic

and social competence from the Skills Checklist (Patterson et al.

1984) are used in conjunction with global ratings of self-worth

(Kaplan 1975).

Antisocial attitudes. This score represents a composite of the

child's report of a negative attitude about teachers, parents,

police, and school; the child's perceptions of how permissible

deviant behaviors are; and the interviewer's impression of the

child's having an antisocial attitude.

Child depression. This represents teacher and parent reports of

depressive symptomatology on the Child Behavior Checklist and the

home observer's impression of the child's depression aggregated

over three observation sessions.

Parenting Composites

Discipline. There are four indicators used to define parent discipline practices: Two are based on observation data, one on the

observers' global ratings after the home observations, and one on

parent reports in the interview on discipline strategies.

79
Two scores derived from the home observations describe the likelihood of an aversive parental reaction given that the parent was

interacting with the child. One of the scores, explosive discipline, describes the likelihood that the parental reaction was

extreme (e.g., threats, hitting). The other score, nattering,

defines the likelihood of the parent's reacting in a scolding or

nagging fashion given that he/she was interacting with the child.

There is, in addition, a composite based on the observers' global

ratings of punishment, consistency, and followthrough. These

scores are internally consistent and were shown to be a useful indicator for the definition of discipline (Patterson et al. 1984).

The fourth indicator consists of ratings obtained from the mothers

during an interview, sampling their perceptions of the discipline

confrontations as being harsh and inconsistent.

Monitoring. The parent's composite score on monitoring has three

indicators. It is measured by two different assessment methods

and by reports from three different agents. The first indicator

is from the parent and child interviewers' global ratings on how

well the child is monitored. The second is a composite score

based on child interview items that describe house rules for monitoring the child's return home from school, his whereabouts in the

evening, and his activities when away from home. The third indicator is based on daily telephone reports of the number of hours

the parent and child spend together. This is a single score averaged across 6 days of reporting.

Parent involvement. Four indicators of parent involvement were

developed from three data types and two agents. Three of these

are child reports of activities with parents, collected from questionnaires, telephone interviews, and the structured interview.

Parent reports on similar activities from questionnaire data are

also used.

Parent rejection. Parents report in the face-to-face interview on

how pleasant their son has been to raise, how difficult it is to

be patient with him, and how well they get along with him. Observers were asked to comment on whether relations between parents

and son were friendly, and interviewers were asked if parents

seemed accepting of the subject child.

Positive reinforcement. This score reflects parent use of positive reinforcement to encourage prosocial behavior. One indicator

for this construct represents the likelihood of the parent's being

positive given the child is positive or neutral in the home.

Additionally, staff observers' and interviewers' impressions of

the parent's reinforcing behavior are used in conjunction with the

parent's daily telephone report of using rewards (verbal, physical, or monetary) and the parent's interview responses concerning

general reinforcing practices.

Problem solving. This measure assesses parent competence in

handling family problems (Forgatch 1984). The score is based

80
primarily on the videotaped family problem-solving task at the

Center, where coders and parents provide global impressions of the

family's problem-solving performance. In addition, home observers

made global ratings of parent competence in solving family problems as observed in the home, combined across three home observation sessions.

Parent drug use. This is a composite score combining the parent's

use of alcohol, marijuana, and illicit drugs (e.g., LSD, cocaine)

with minor drug use, such as use of caffeine or sleeping pills.

The questions regarding substance use were acquired by two questionnaires: one developed here at the Center, and the Michigan

Alcoholism Screening Test (MAST) developed by Selzer et al.

(1975).

RESULTS

Percentages of the child's Yes responses to queries on use of each

drug are presented in table 4. Note that the two cohorts are

relatively comparable on all drugs, although a slightly higher

percentage of Cohort II had experimented with marijuana. Alcohol

was the most commonly sampled drug in the 9- to lo-years age

group. The number and percentages of boys sampling multiple substances is presented in table 5. Relatively few boys (21 in

Cohort I and 19 in Cohort II) in the sample had not sampled any

drug, whereas 7 youngsters in Cohort I and 15 in Cohort II had

experimented with four or more drugs.

A composite score reflecting the child's drug sampling was formed

by combining the parent and child reports. The correlation between the parent and child reports was .84 in Cohort I and .88 in

Cohort II. Table 6 shows the intercorrelation of the child's drug

use and that of his friends to antisocial behavior and attitudes,

peer relations, self-esteem, child depression, observed child

coerciveness, and academic skills. Note that for Cohort I the

highest correlations are observed between the child's use of drugs

TABLE 4. Frequency of drug use exploration in two cohorts of

9- to 10-year-old boys

Percent Yes

Cohort I Cohort II

Have you ever tried...?

Cigarettes 24 29

Beer, even a sip 71 76

Wine, even a sip 47 48

Hard liquor, even a sip 16 28

Marijuana 5 15

Anything else to get high 3 4

81
TABLE 5. Percent of preadolescent boys' polydrug use

Number of

Substances Cohort I (n) Cohort II (n)

Sampled (Percent) (Percent)

0 21 (21) 18 (19)

1 29 (29) 21 (21)

2 25 (25) 33 (31)

3 18 (18) 13 (13)

4 6 (6) 8 (8)

5 0 (0) 5 (3)

6 1 (1) 2 (4)

TABLE 6. Correlation of child’s drug use and friends’ drug use to

other measures of child behavior and adjustment

Child Measures

General antisocial

Observed child coercion

Antisocial peers

Normal peer relations

Self-esteem

Depression

Academic skills

Child's Drug Use Friends' Drug Use

Cohort I Cohort II Cohort I Cohort II

.37*** .15a

.28** .07

.25** .15a

.09 .20*

.27** .47*** .39*** .51***

-.09 -.15a

-.03 -.19*

-.24* -.20* -.15a

-.14a

.23* -.05 .03 -.02

-.09 -.03 -.04 .10

a

p<.10

*p<.05

**p<.01

***p<.001

and his antisocial behavior. This correlation was found to replicate only partially in Cohort II. In the second cohort, deviant

peer influences covaried quite strongly with the composite measure

of child drug exploration, which was consistent across the two

cohorts. The child's sense of self-esteem correlated with early

drug sampling at a low level in both cohorts.

The next step in the analysis was to examine the covariation between five measures of family management, as well as one measure

of the parent-child relationship, with the child's and his

friends' drug use. Parent Monitoring practices were significantly

correlated with Child's and Friends' Drug Use in both cohorts

(table 7). Parent Discipline practices were found to covary with

82
TABLE 7. Correslation of child’s drug use and friends' drug use to

six family management constructs

Family Management

Constructs

Child's Drug Use Friends' Drug Use

Cohort I Cohort II Cohort I Cohort II

Parent monitoring -.39*** -.19* -.22** -.18*

Positive reinforcement -.16a

-.10 -.13a

-.08

Parent involvement -.28** -.05 -.01 -.23**

Discipline practices -.27** -.18* -.13a -.02

Parent rejection -.31*** -.02 -.21* -.05

Parent problem solving -.26** -.10 -.09 -.05

a

p<.10

*p<.05

**p<.01

***p<.001

Child's Drug Use in both cohorts and Friends' Drug Use, marginally, in Cohort II. Parent Involvement was associated with

Child's Drug Use in Cohort I and Friends' Drug Use in Cohort II.

Also notable was the correlation between a composite measure of

parent rejection and both the child's and friends' drug exploration in Cohort I. However, this finding did not replicate in

Cohort II. It is hypothesized that the major causal influence on

family management relates parent monitoring to the child's exposure to peers who use drugs. It is also hypothesized that the

longer the child's foray into drug use goes undetected by significant adults, the more likely it will be that the child will develop a pattern of drug use. While at this early age there are no

patterned drug users in either cohort, the moderate degree of consistency between the two cohorts in the patterns of correlations

should be considered. It is also important to consider the possible indirect influence of monitoring on the child's drug sampling.

For example, parent monitoring correlated with antisocial peers:

-.36 (p<.001) in Cohort I and -.40 (p<.001) in Cohort II.

Parent drug use was assumed to serve two functions, as described

earlier. Table 8 provides correlations between the different indices of parent drug use and the child's and friends' drug use.

Note that the mother is primarily implicated, since four of five

measures of her reported drug use correlate with the child's drug

use. The father's'heavy drinking score correlates with the criterion variable. The level of the child's exposure to parent substance use could not be determined. Further analysis'of the

relation between the pattern of parent drug use (e.g., at home vs.

83
TABLE 8. Correlations between parent drug use and child’s and

friends’ drug use

Parent Drug Use

Child's Drug Use Friends' Drug Use

Cohort I Cohort II Cohort I Cohort II

Mother:

Heavy drinking score

MAST score

Marijuana use

Minor drug use

Hard drug use

Father:

Heavy drinking score

MAST score

Marijuana use

Minor drug use

Hard drug use

Parent composite

.24** .35***

.18* .07

.36*** .24*

.00 .07

.32*** .27**

.32***

.08

.15a

.06

.08

.35***

.24*

.15

.09

.17a

.18a

.34***

-.07 .26**

.08 .11

-.04 .05

-.01 .05

.06 .20*

-.07 .09

.03 -.05

.13 -.09

-.01 -.01

.05 .25*

-.04 .19*

a

p<.10

*p<.05

**p<.01

***p<.001

in a bar) and the beginning of substance use by the child is needed, as is further clarification of the extent to which children of

drug-using parents find substances more readily available.

It is also hypothesized that parents' immoderate use of substances

may interfere with their parenting practices, in general, and

their monitoring, in particular. The data presented in table 9,

provide only marginal support for this hypothesis. In Cohort I,

the composite measure of parent drug use correlated significantly

with monitoring practices and parent involvement with the child.

These correlations, however, were not replicated in Cohort II.

The hypothesis that parent monitoring of and involvement with the

child has a predictive relation to later patterned use of drugs

remains untested. Further, longitudinal data will address the

question of whether sustained or increased substance use by parents is followed in time by decrements in their family management

practices.

There is a need for a model providing a unified explanation of

early drug sampling. As a preliminary step toward building such a

model, the four primary constructs discussed above (Monitoring,

Parent Drug Use, Peer Drug Use, and Child Drug Sampling) were

84
TABLE 9. Parent drug use as a disrupter of family management

practices

Parent Positive Problem

Drug Use Monitoring Discipline Reinforcment Involvement Solving

Cohort I

Parent composite -.24** -.06 -.15a -.31*** -.12

Cohort II

Parent composite -.10 -.16a-.09 -.10 -.14a

ap<.10

*p<.05

**p<.01

***p<.001

tested in a correlational structural equation model. The model

(shown in figure 2) was developed and tested with Cohort I and

subsequently replicated with Cohort II. Note the hypothesized

pattern of relations: Parent drug use is expected to have both

direct and indirect effects on the child's early initiation into

drug use. The first effect is direct, and the mechanism is

thought to be an increased availability of substances for children

whose parents use substances regularly, as well as possible modelling effects. The second effect is indirect, disrupting the parent's supervision practices and placing the child in a peer

context where he/she is exposed to drug use by near-age mates.

Exposure to drug use by parents and peers was hypothesized to be a

proximal effect on the child's early drug use, and parent monitoring, a more distal effect (although of considerable importance to

the applied issue of prevention). Parent monitoring was further

tested for having'both a direct and indirect impact on the child's

exploration with drugs. In Cohort I, the direct path coefficient

joining Parent Monitoring with Child's Drug Sampling was observed

to be nonsignificant. Dropping the effect coefficient did not

result in a statistically significant change in the chi-square

goodness-of-fit test, Therefore, the most parsimonious version,

as shown in figure 3, was replicated on Cohort II.

The replication of the model in figure 2 is not altogether perfect. In Cohort II, the effect coefficients emanating from Parent

Drug Use are not statistically significant, as is consistent with

the bivariate correlations reported above. It is also important

that the standardized factor loadings for the latent variable,

Parent Drug Use, are statistically nonsignificant. It may be that

the relatively skewed distributions in those two indicators (parent marijuana use and other drug use) are responsible for the

change in correlational structure across the two cohorts. The

importance of replicating structural models is underscored by this

example. Nevertheless, progress has been made towards supporting

85
FIGURE 2. Correlational model of drug sampling in middle childhood: Construction and

replication coefficients
a model including both parent drug use and parenting practices as

determinants of drug sampling in middle childhood. The model

accounted for 51 percent of the variance in drug use in Cohort I

and 44 percent of the variance in Cohort II.

A reasonable next step to take in analyzing the appropriateness of

the concurrent model for the observed data is to determine its

adequacy when the two samples are combined. Increasing the sample

size should theoretically increase the viability of the effect

coefficients relative to population values. The original model

developed in Cohort I was tested again, without the Cohort II

revisions, with the combined sample.

Increasing the sample size to 168 resulted in the model's showing

an adequate fit to the combined cohort data (chi-square=36.7,

df=32, p=.26). As can be seen in figure 3, all the effect coefficients are statistically significant, as well as the construct

indicators. For the two cohorts combined, the model accounts for

51 percent of the variance in the child's sampling of different

drugs.

DISCUSSION

A concerted effort was made to develop a model showing the interrelations between variables often studied in epidemiological studies of child drug use. These data are an improvement on such

studies in that they represent a number of measurement approaches

to both parenting practices and indices of drug exposure and the

child's antisocial behavior. These analyses revealed significant

correlations between the child's early drug use and several composite scores reflecting his maladjustment, including antisocial

behavior, coercive behavior with family members as observed in the

home, self-esteem, and depression. The patterns of correlations

were not entirely consistent across the two cohorts; however, the

child's association with deviant peers was found to be significantly related to early drug exploration and poor parent monitoring practices, which is consistent with the findings reported by

Dishion and Loeber (1985) on a sample of older adolescents.

Parent monitoring practices were significantly correlated, but of

a relatively low magnitude, with drug sampling across the two cohorts. Related to this issue of monitoring is the extremely high

correlation noted between the child's and parent's report of his

drug sampling in both cohorts (r=.84 and .88 in Cohorts I and II,

respectively). Obviously, early drug sampling is not exclusively

a clandestine activity but a process that seems to be initiated

with at least the partial awareness of parents. Thus, the effect

of poor monitoring practices may be instrumental in the child's

progression from exploration to patterned use. We assume that the

deviant peer group is the social context in which maladaptive

patterns of drug use are practiced. Parent monitoring is hypothesized to restrict the child's involvement in deviant social contexts. It is also likely that a high degree of parent involvement

87
FIGURE 3. Correlational model of drug sampling in middle childhood: Cohorts I and II combined
with the child has a positive effect in promoting prosocial

activities and increases the parent's sensitivity to the child's

whereabouts and needs.

The correlational data and the modelling analysis support the

hypothesis that parent drug use is related to the child's early

sampling of drugs. This finding is in some contrast to earlier

research with older adolescents (Dishion and Loeber 1985), where

the correlation between parent use of alcohol and the child's use

of marijuana and alcohol was low and generally nonsignificant

(table 1).

The implications of these results for both treatment and prevention of drug use in adolescence are of special importance here.

The correlation between the child's drug use and his generalized

score on antisocial behavior is supportive of a perspective that

ties these two outcomes together and poses similar, although not

exact, causal circumstances underlying both. That is, parenting

skills that are either omitted or disrupted set the child up in

two ways: (1) he or she is likely to be antisocial and engage in

behavior that elicits negative reactions by adults and peers

alike; and (2) through the lack of monitoring and by virtue of

being antisocial, the child is allowed to associate with a peer

group in which drug use is common. Given research reported by Bry

et al. (1982), it is clear that there is no single path toward

substance use. However, parental monitoring practices may be a

key variable underlying the child's early foray into sampling

substances.

It has been proposed that drug use represents the beginning point

on a developmental continuum. This assumption is supported in

part by longitudinal studies of delinquency (Loeber and Dishion

1983). It is also expected that parent training procedures would

be most useful as an intervention tool. This generates the emphasis on studying the very beginnings of substance use prior to

adolescence.

The next step in this line of research is completion of longitudinal research, and this is currently under way at OSLC. The following steps relate well to the task of early intervention in

substance abuse among the group of adolescents who are most at

risk.

IMPLICATIONS FOR TREATMENT

It is important to underscore the fact that longitudinal data

alone do not provide an adequate basis for attributing causality

to any identified determinant. The more rigorous approach to

determining the actual applied utility of an explanatory model is

to use the principles implied by the model in a randomized longitudinal experiment, in other words, a planned intervention. The

use of randomization is especially important in this context to

fully examine the effect of manipulating the hypothesized determinants. The family (mis)management processes are viewed as setting

89
the child at risk for developing maladaptive habits such as drug

use. The question remains: How would such a trial be carried out

practically?

Simply providing the child with information about substance abuse

would primarily alter the behavior of well-socialized children

from cohesive families, rather than those most at risk. Children

at high risk for heavy substance use would probably not give up

cigarette smoking when given health information. Similarly, simply giving information and training the child in self-control

techniques would probably not be effective for the subset of children most at risk for later substance abuse. Even at age 10, this

subset of most-at-risk children are already difficult to change,

whether by family, teachers, or therapist. A review of controlled

field trial studies by Kazdin (1985) showed that efforts to teach

self-control techniques to such samples did not produce consistent

generalization to natural settings. But still, both information

and teaching self-control techniques should be explored more

intensively.

Although it is likely that parents will still prove to be the most

effective agents for changing the behavior of their preadolescent

or adolescent children, there are recognized disadvantages to

using parents as agents of change. First, it is difficult to obtain parent cooperation in any kind of intervention. Second, even

if the parent agrees to participate, careful observation of their

interactions with parent trainers has demonstrated that much of

their efforts are resistive and noncompliant

1984). But in summary, the optimal strategy

to train parents before the child develops a

problem.

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Eugene, OR: Castalia Publishing Company, in press.

Pulkkinen, L. Youthful smoking and drinking in a longitudinal

perspective. J Youth Adolesc 12(4):253-283, 1983. 

Reid, J., ed.

Vol. 2. Observation in Home Settings. Eugene, OR: Castalia

A Social Learning Approach to Family Intervention:

Publising Company, 1978. 77pp.

Robins, L. Deviant Children Grow Up: A Sociological and

Psychiatric Study of Sociopathic Personality. Baltimore, MD:

Williams & Wilkins, 1966. 237pp.

Robins, L.N., and Przybeck. T.R. "Age of onset of drug use as a

factor in drug abuse and other disorders. In: Jones, C.C., and

Battjes, R.J., eds. Etiology of Drug Abuse: Implications for

Prevention. National Institute on Drug Abuse Research Monograph

56. DHHS Pub. NO. (ADM) 85-1335. Washington, DC: supt. of

Docs., U.S. Govt. Print. Off., 1985. pp. 178-192.

Robins, L.; Davis, D.; and Wish, E. Detecting predictors of rare

events: Demographic, family and personal deviance as predictors

of stages in the progression toward narcotic addiction. In:

Strauss, J.; Bubigan, H.; and Roff, M., eds. The Origins and

New York: Plenum Press, 1977. pp. 379-407

Course of Psychopathology: Methods of Longitudinal Research

Zucker, R.A. Parental influences on the drinking patterns of

their children. In: Greenblatt, M., and Schuckit, M.A., eds.

Alcoholism Problems in Women and Children. New York: Grune &

Stratton, 1976. pp. 211-239.

AUTHORS

Thomas J. Dishion, M.A., M.S.

Gerald R. Patterson, Ph.D.

John R. Reid, Ph.D.

Oregon Social Learning Center

207 East Fifth, Suite 202

Eugene, OR 97401

93
Pharmacotherapy of Concomitant

Psychiatric Disorders in

Adolescent Substance Abusers

Barbara Geller

INTRODUCTION

At the time of this writing there are no studies of the pharmacological treatment of adolescent substance abusers who also have

major affective or schizophrenic disorders. Therefore, the following is a review and discussion of drug treatment of these

disorders in nonabusing adolescents.

DIAGNOSTIC ISSUES OF AFFECTIVE DISORDER IN ADOLESCENTS

There has been a consensus among various investigators in the past

decade that major depressive disorder exists during the adolescent

years, evidenced by the increasing utilization of diagnostic criteria and assessment instruments that are similar to those used by

investigators of adult populations and, therefore, yield comparable data (Carlson and Cantwell 1980; Strober et al. 1981; Robbins

et al. 1982; Friedman et al. 1982; Geller et al. 1985a). The current Diagnostic and Statistical Manual (DSM-III) for psychiatric

disorders includes exactly the same criteria for affective disorder from age 6 through adulthood.

However, there has been less systematic investigation of the

diagnosis of mania during the pediatric years, despite over 300

reports of its existence (Youngerman and Canino 1978; Steinberg

1980; Jefferson 1982). Several authors have reported the misdiagnosis of an adolescent manic episode as schizophrenia (Campbell

1952; Horowitz 1977; Carlson and Strober 1978; Joyce 1984). The

latter may be due in part to the presence of other psychotic phenomenology (e.g., delusions, thought disorder) during adolescent

mania, and here the usefulness of a family history of a lithiumresponding parent has been noted as a diagnostic aid (Carlson and

Strober 1978; Strober and Carlson 1982).

An important issue is whether or not to assess affective disorder

in adolescents by administering the Kiddie-Schizophrenia and

Affective Disorders Schedule (KSADS), or other diagnostic instruments (Chambers et al. 1985; Geller et al. 1985a). to the mother

94
and the adolescent and arriving at a consensus diagnosis (similar

to assessments of children), or to administer the Schizophrenia

and Affective Disorders Schedule (SADS) to the adolescent only

(similar to adult assessments) (Friedman et al. 1982; Strober and

Carlson 1982). Studies of mother-child ratings of depression

among the 12-and-under age group report significant differences

(Weissman et al. 1980; Kazdin et al. 1983; Moretti et al. 1985).

Comparable studies of depression in teenagers are not available.

However, a recent study of mother-adolescent ratings of attention

deficit disorder with hyperactivity by Gittelman (1985) is relevant. In that study, a significantly higher percentage of attention deficit disordered adolescents was identified using combined

mother and adolescent ratings. Further studies of adolescent

affective disorder will be important, especially in cases in which

it is the patient's first episode, and prior course of illness and

previous response to treatment are not available as diagnostic

aids.

Although retrospectively 20 to 35 percent of adults report that

their first episode of affective disorder occurred during the

adolescent years (Loranger and Levine 1978; Strober and Carlson

1982), there are no large-scale studies of the course of affective

disorder during adolescence. However, there are retrospective

data that suggest that the course of illness of major depressive

disorder in adolescents may be chronic (of years' duration)

(Geller et al. 1985a; Beardslee et al. 1985), unlike the cyclic

acute (of months' duration) episodes in adults (Hamilton 1979).

One systematic study reported that the first manic episode during

adolescence is usually preceded by a depressive episode, and a bipolar course is predicted by a history of rapid onset, the presence of marked psychomotor retardation, and a switch to hypomania

with tricyclic antidepressant treatment (Strober and Carlson

1982). These studies of the course of adolescent affective disorder are crucial in evaluating outcomes in drug studies.

The incidence of delusional depression in adolescents has been

reported as 13 percent and 8 percent by investigators of inpatient

groups (Strober et al. 1981; Friedman et al. 1983). It was also

lower in the Inamdar et al. (1979) study, but it is doubtful that

their subjects fit the criteria for major depressive disorder,

since they were described as "transiently sad only in relation to

particular environmental events." The above reported incidences

are lower than the 9 to 60 percent observed in adults (Pope and

Lipinski 1978); however, this may be largely due to the misdiagnosis of psychotic depressed adolescents as schizophrenic (Carlson

and Strober 1978). The question of whether delusions need be mood

congruent remains controversial (Kantor and Glassman 1977).

In summary, the current hypothesis is that manic-depressive illness is the same disorder at all ages, and, therefore, studies to

examine external validating criteria (family history of affective

disorders, biological markers, course of illness, and response to

antidepressant medication) would be appropriate (Akiskal 1980).

95
PHARMACOLOGICAL ISSUES OF PSYCHOTROPIC DRUGS IN ADOLESCENTS

Pharmacological properties of psychotropic drugs commonly used in

adults have been little studied in adolescents. There are only

two reports on neuroleptics. Meyers et al. (1980) reported a

plasma level/response relationship of haloperidol in a 13-year-old

schizophrenic boy. That patient's therapeutic level was higher

than that reported in some adult studies (Mavroidis et al. 1985;

Davis et al. 1985). Geller et al. (1985b) reported a chlorpromazine-nortriptyline drug interaction similar to that reported for

adults on combined neuroleptic-tricyclic antidepressant therapy

(Loga et al. 1981). Two investigators have reported on the

pharmacology of tricyclic antidepressants in adolescents. PuigAntich (1984) found no plasma level/response relationship for

imipramine in adolescents. This was an unexpected finding,

because Puig-Antich et al. (1979) had previously reported such a

relationship in prepubertal children, and this relationship is

also reported in adults (Risch et al. 1981). Recently, similarities between the pharmacology of nortriptyline in adolescents and

adults have been reported with respect to the following: pharmacokinetic parameters (Geller et al. 1984); single dose kinetics

predicting steady state and dose (Geller et al. 1985c); and serial

monitoring and the time to achieve steady state (Geller et al.

1985d). The latter studies provide the basis for expecting that a

well-designed study would prove nortriptyline to be effective in

adolescents also.

There are as yet no studies during the teenage years of the administration of psychotropic drugs to substance-abusing adolescents,

and, therefore, little is known of substance interaction in drug

abuse during the teenage years. However, since these may be similar to interactions found in adults, mention of the adult findings

may be useful here. Acute ethanol ingestion may elevate tricyclic

antidepressant plasma levels, while chronic ethanol ingestion and

chronic ingestion of certain abused drugs can induce the hepatic

degradative enzymes and thereby decrease tricyclic antidepressant

plasma levels (Seixas 1975; Kalant et al. 1976; Sellers and

Holloway 1978; Sellman et al. 1975; Stevenson et al. 1972; Ciraulo

et al. 1982; Sandoz et al. 1983; Iber 1977; Khanna et al. 1976;

Linnoila et al. 1979; Linnoila et al. 1981; Moldeus et al. 1980).

Thus, plasma level monitoring would be crucial to avoid toxicity

in acute substance abusers and to avoid subtherapeutic plasma

levels in chronic substance abusers.

PHARMACOTHERAPY OF MAJOR DEPRESSIVE DISORDER IN ADOLESCENTS

Since the introduction of antidepressant medications in the

1950's, there have been numerous well-designed double-blind

placebo-controlled studies among adult samples (Klein et al.

1980). More recently, with advanced technology, many studies have

monitored the plasma levels of the tricyclic antidepressants

(Risch et al. 1981) or monoamine oxidase inhibition (Robinson et

al. 1978) to insure therapeutic dose during trials. Recognizing

the need to utilize power statistics to insure an appropriate

96
sample site and recognizing the high placebo response rate to

medications of all types, well-designed studies in adults have

begun with a placebo washout period of 1 to 2 weeks. Diagnostic

instruments and severity measures have been tested for interrater

reliability and clinical validity (Klein et al. 1980).

Despite these important advances in the design of studies of

tricyclic antidepressants and monoamine oxidase inhibition in

adult populations, the adolescent age group has been relatively

neglected. There are no adequately designed double-blind placebocontrolled studies of tricyclic antidepressants or monoamine

oxidase inhibitors for major depressive disorder during the

adolescent years. There are four double-blind placebo-controlled

studies of the drug treatment of depression during adolescence.

The first of these studies was performed by Lucas et al. (1965).

Fourteen subjects, 10 to 17 years of age, were studied, making

adolescent-specific issues difficult to identify. Dfagnosis was

made by clinical interview, and the diagnostic categories included

childhood depression, schizophrenia, personality disorder, and

psychoneurosis. Diagnostic criteria were not mentioned. Severity

measures were developed by the authors, but data on interrater

reliability or validity were not given. The subjects received

amitriptyline 30 to 75 mg daily. The reasons for the choice of

amitriptyline and for the dosage range were not presented. The

study was done prior to the availability of plasma levels. The

percent of responders and nonresponders was not stated. The second of these studies was performed by Frommer (1967). Forty-one

subjects, 9 to 15 years of age, were studied. Diagnosis by

clinical interview divided the sample into a phobic group and a

mood-disorder group. No criteria for diagnosis were given, and

response was not measured by severity scales but by clinical

interview. The two treatment regimes were either phenelzine 30 mg

daily plus chlordiazepoxide 20 mg daily, or phenobarbitone 60 mg

daily and an inert placebo. The phenelzine-chlordiazepoxide group

had a 56-percent improvement; the phenobarbitone group had a 19-

percent improvement.

These two studies were both performed prior to the advent of

Research Diagnostic Criteria (RDC) and DSM-III criteria, and from

the article it remains unknown whether the subjects mentioned

would have met current criteria for major depressive disorder.

Further, the group included subjects who were 9 to 12 years old;

therefore, this study was not adolescent specific. Also, using

phenelzine without monitoring monoamine oxidase inhibition does

not permit determining whether the amount of medication the children were receiving was adequate to expect response.

More recently there have been two other studies. Kramer and

Feiguine (1981) reported a study of 20 subjects, 13 to 17 years of

age, who were diagnosed with adolescent depression. The criteria

for the diagnosis are not stated. The children were rated for

severity on a psychiatric rating scale that the authors developed;

data on interrater reliability or validity were not given. The

subjects had the Minnesota Multiphasic Personality Inventory

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(MMPI) and the Depression Adjective Checklist administered at

baseline and after 6 weeks of either active or placebo drug. All

these subjects were inpatients who, by clinical interview prior to

admission, were felt to be significantly depressed. They were

kept drug free for approximately 5 days on a unit where various

forms of milieu therapy were routinely used. Each subject received amitriptyline 200 mg per day for a period of 6 weeks if

they were on active drug. The results of this study show that on

all measures, except the Depression Adjective Checklist, there

were no significant differences between active and placebo groups.

On the Depression Adjective Checklist, the active group was

significantly more improved. Both groups, however, showed significant improvement and, apparently, were no longer in need of psychiatric care at the end of the trial. Even if we assume that all

children on active medication were receiving an adequate amount of

medication, the results of this study have several problems. An

n=20 is, by power statistics, inadequate to test the difference

between an active and a placebo medication. Further, three subjects were later identified as not being depressed. The drug-free

period lasted only 5 days. Without an adequate placebo washout

phase, the distribution of placebo responders between the two

groups cannot be known. Here again, the reason for the choice of

amitriptyline and the rationale for the dosage were not stated.

Ryan et al. (in press) reported an abstract of a study of 38

subjects. These subjects were diagnosed with major depressive

disorder, utilizing research diagnostic criteria assessed by the

KSADS. The KSADS was also used as the severity measure. The

children received a fixed dose of imipramine, 5 mg/kg per day,

unless their EKG did not permit the full dosage. It was noted at

the end of the study that only 44 percent had improved; further,

there was no plasma level/response relationship in this group. As

noted above, these were unexpected findings, since the same group

of investigators had found from retrospective data analysis a significant plasma level/response relationship of imipramine in prepubertal children similar to that in adult groups. Puig-Antich

(1984) speculated that, possibly due to pubertal hormones, these

subjects may not have responded. However, hormonal imbalance at

other times of life, such as post partum, is not associated with a

lower response to antidepressant medication. Further, Puig-Antich

had speculated that maybe adolescents have atypical depressions

such as those reported by Quitkin et al. (1982) and, therefore,

would do better on monoamine oxidase inhibitors. However, if the

subjects met the RDC criteria for major depressive disorder and

were atypical, they may have been more similar to the group reported by Akiskal (1981) who had a good response to tricyclic

antidepressants.

In summary, subjects were not identified using current criteria

for major depressive disorder in three studies (Lucas et al. 1965;

Frommer 1967; Kramer and Feiguine 1981), and delusional subtypes

could not be identified from material given in the reports. This

is important, because delusional subtypes in prepubertal subjects

(Chambers et al. 1982) and in adults are significantly less likely

to respond to conventional doses of tricyclic antidepressants, as

98
discussed elsewhere in this review. It is of note that in two of

these four studies, the authors reported less than 50-percent

improvement (Frommer 1967; Puig-Antich 1984), and in the Kramer

and Feiguine (1981) study, both active and placebo patients

responded.

The first of the five open-design studies was performed by Frommer

(1968). Clinically diagnosed as phobic depressed, 190 subjects, 4

to 16 years of age, were studied. Criteria were not given, and

assessment instruments were not used. Amitriptyline, in unreported dosage, was administered, and a 73-percent response rate was

stated. Again, the wide age range does not permit specific knowledge of how the adolescents responded. In the second study, reported by Stack (1971), 289 subjects, 5 to 14 years of age, were

studied. They were divided into four groups, one of which was

"organic depressed" and will not be discussed here. The other

three were simple, phobic, and mixed depressions. Diagnosis was

made clinically, no criteria were given, and no assessment or

severity instruments were used. Subjects received either amitriptyline, nortriptyline, or imipramine up to 75 mg per day, or phenelzine up to 45 mg per day. The response rate reported was 67 to

94 percent. Again, the basis for the choice of drugs and the

rationale for the doses are not stated. Without monitoring the

plasma levels for the tricyclic antidepressants or monoamine oxidase inhibition for phenelzine, it cannot be known if the difference between responders and nonresponders was an issue of adequate

dose. The third study, reported by Abe (1979), included 24 subjects 9 to 17 years of age. They were diagnosed as paranoid

phobic depressives by clinical interview without criteria being

specified, and no assessment or severity measures were used.

These subjects received sulpiride in a dose of 50 to 100 mglday

(no rationale for the choice of drug or dose was reported), and

66-percent improvement was noted.

Minuti and Gallo (1982) reported a study of 20 subjects, 4 to 15

years of age, who were diagnosed by clinical interview as depressed or as having a behavior disorder. A severity measure used

to rate them during the time they were on medication was a fouritem target symptom scale that the authors developed and for which

reliability and validity are not reported. The subjects received

a mean maprotiline dose of 24 to 32 mg per day (rationale for drug

choice or dose was not given), and it was noted that subjects

"improved." In the Abe (1979) and Minuti and Gallo (1982) studies, it is not clear why drugs newer to the market were being

studied prior to better-known medications, especially for pediatric subjects. Also, the age range of the subjects mixed teenagers with prepubertal subjects; therefore, the results for the

teenagers themselves cannot be known.

Geller et al. (1985b) reported an open pilot study of nortriptyline in eight adolescents 13 to 16 years of age. These subjects

were diagnosed with major depressive disorder, nondelusional type,

by RDC and DSM-III criteria and were assessed by the KSADS. The

severity measure used during the study was the Children's

99
Depression Rating Scale (CDRS). These subjects received nortriptyline in a dose kinetically determined to obtain plasma levels

between 60 and 100 mg/ml, similar to the adult therapeutic range

(Asberg et al. 1971). In this study, six of the eight subjects

had a full response on the CDRS. Plasma-level monitoring was performed weekly during the 8-week study and indicated good compliance. The rationale for the choice of nortriptyline was its

safety in the geriatric population and its kinetic properties,

which permit determining at baseline what dose to administer to

obtain a plasma level optimal for safety and efficacy. Weekly

Asberg Side Effects monitoring showed only minimal and transient

side effects.

In summary, there is a need for adequately designed double-blind

placebo-controlled studies of tricyclic antidepressants and monoamine oxidase inhibitors for major depressive disorder in the

adolescent age group.

Pharmacotherapy of adult delusional depression is considerably

less well studied than the nondelusional type. This is in part

due to the lack of recognition that delusional depressives might

be a subtype with a poor response to conventional doses of tricyclic antidepressants prior to the critical literature review of

Kantor and Glassman (1977). A number of open studies (Glassman et

al. 1977; Davison et al. 1977; Friedman et al. 1961; Hordern et

al. 1963; Avery and Lubrano 1979; Minter and Mandel 1979; Kaskey

et al. 1980; Charney and Nelson 1981; Moradi et al. 1979; Frances

et al. 1981; Nelson and Bowers 1978; Fink et al. 1965) and one

double-blind placebo-controlled study (Spiker et al. 1985) support

the need for combined therapy of delusional depression; other open

studies do not (Simpson et al. 1976; Stewart et al. 1980; Quitkin

et al. 1978).

The only study of adolescent delusional depression was an open

design reported by Geller et al. (1985b) of six postpubertal subjects, 12 to 16 years of age, who were diagnosed and assessed utilizing the KSADS and CDRS and who fit DSM-III and RDC criteria for

major depressive disorder, delusional type. In this report,

chlorpromazine (50 to 100 mg daily) alone was ineffective after 2

weeks. Nortriptyline was then added pharmacokinetically to produce plasma levels between 60 and 100 mg/ml, in the adult optimal

therapeutic range (Asberg et al. 1971). for an d-week combined

therapy phase. Plasma levels were monitored weekly. Combined

therapy produced a full response in five of the six subjects.

Side effects were monitored by the Asberg Side Effects Scale and

the Abnormal Involuntary Movements Scale (AIMS) and were minimal

and transient.

PHARHACOTHERAPY OF MANIA IN ADOLESCENTS

Since the introduction of lithium in the 1950's, its usefulness in

the treatment of acute manic episodes and the prevention of recurrences has been well established (American Journal of Psychiatry

1985). The relationship of lithium plasma levels to response is

100
also well studied (Cooper and Simpson 1978). Since the 1950's,

there have been more than 300 reports of the use of lithium in

children and adolescents, many of whom were diagnosed manicdepressive (Schou 1971; Youngerman and Canino 1978; Jefferson

1982; Steinberg 1980). However, there are no studies of plasma

level/response and no well-designed double-blind placebocontrolled studies of adolescents.

The following is a review of the five more systematic studies of

the use of lithium for adolescent mania. The first of these studies was by Annell (1969). Twelve subjects, 9 to 18 years of age,

were studied. They were diagnosed as two manic, five catatonic,

two delinquent, one suicidal, and two hyperactive using clinical

interview; no criteria were stated. No diagnostic or severity

measures were used. They were administered lithium to achieve a

plasma level of 0.6 to 1.2 mEq/L per day, and 11 of the 12 responded; the one nonresponder was one of the hyperactive children.

A second report was by Horowitz (1977) of eight teenagers, 15 to

18 years of age, who were diagnosed with primary affective psychosis by clinical interview. All eight responded when lithium was

administered to achieve a plasma level of 0.5 to 1.2 mEq/L.

Brumback and Weinberg (1977) studied six children 4 to 13 years of

age. Although there were few adolescents in the sample, this

study is important, because criteria were used. This is the first

report of criteria for juvenile mania used by investigators performing a drug study. The Weinberg criteria for childhood mania

were used as a severity measure to assess the children. The children received lithium to achieve a plasma level of 0.6 to 1.5

mEq/L. While receiving lithium, five of the six children sustained a worsening of the depression to a point of clinical significance. Two of the five children whose depression worsened

while they were on lithium had a good and sustained response when

a tricyclic antidepressant was added to the lithium. Another two

of these five children who received a tricyclic antidepressant in

addition to the lithium had a worsening of their mania. Therefore, only two of the six children had a good and sustained response, and those two only after a tricyclic antidepressant was

added to their regime.

DeLong reported (1978) on 12 subjects 4 to 14 years of age.

Again, although there were few adolescents in this sample, four of

these subjects were on a double-blind placebo-controlled trial for

a 3-week period. Their diagnosis was manic-depressivelike illness

based on clinical interview, and their behavior was assessed by a

modified Connors Parent Questionnaire. They received lithium to

achieve plasma levels of 0.5 to 1.2 mEq/L. The subjects were all

reported to have had a good response in terms of stabilization of

their mood. Two of the 12 were noted to have decreased motivation

to achieve in usual areas of activity and 1 of the 12, to have a

decreased interest in learning. Hassanyeh and Davison (1980)

reported on seven teenagers, 13 to 15 years of age, three of whom

were diagnosed manic and four of whom were diagnosed depressed as

assessed by the Weinberg criteria. Six of these subjects were

reported to respond to lithium at a plasma level of 0.5 to 1.0

101
mEq/L; however, three of the six also received electroconvulsive

therapy (ECT).

The problems with all the above studies are similar to the problems with the studies of major depressive disorder in this age

group. The age range of the subjects in three of these studies

also included prepubertal children, which makes it difficult to

define adolescent-specific issues. Only two of these studies,

Brumback and Weinberg (1977) and Hassanyeh and Davison (1980),

used criteria to establish the diagnosis of mania. In two of the

studies, additional treatment with either a tricyclic antidepressant or ECT was administered, making it difficult to assess the

effect of lithium. It is of note here that plasma levels were

monitored as is necessary to avoid serious toxicity with lithium,

and the range at which response occurred is similar to that

reported for adult subjects.

There are as yet no studies of whether or not lithium will be

useful on a maintenance basis during adolescence. The need for

these studies is evidenced by reports, such as those by Strober

and Carlson (1982). that an adolescent presenting with bipolar

illness will have a "malignant" course, It is not known whether

maintenance lithium or lithium plus other modalities would provide

a more favorable prognosis for these children. It is also not

known whether a more favorable prognosis would be available if

plasma levels were held between 1 and 1.5 mEq/L. This is mentioned because children and adolescents have a higher renal clearance than adults and, therefore, might need not only higher mg/kg

doses to achieve similar plasma levels, but might, because of the

rapid clearance, need to be maintained at higher plasma levels in

order to achieve consistent response.

DIAGNOSTIC ISSUES OF SCHIZOPHRENIC DISORDERS IN ADOLESCENTS

Many reports of "childhood schizophrenia" or "childhood psychosis"

are equivalent to DSM-III childhood autism or DSM-III childhood

onset pervasive developmental disorder (Green et al. 1984). It is

yet unclear what subset, if any, of children with childhood autism

or childhood onset pervasive developmental disorder are manifesting an illness similar to adult onset schizophrenia. Therefore,

it is not possible to evaluate treatments of "childhood schizophrenia" and know whether or not we are talking about the same

illness as adult onset schizophrenia. Multiple studies of neuroleptics in the childhood autism or childhood onset pervasive

developmental disorder group suggest that there is no medication

that has been found effective in well-designed double-blind

placebo-controlled studies (Coleman and Gillberg 1985). The phenomenology of schizophrenia defined by DSM-III criteria has not

been studied during the adolescent years. We do not know whether

adolescents having their first episode of schizophrenia would be

different from adults in their phenomenology, the way manic episodes occurring during adolescence have been reported to be worse

in terms of psychotic features and thought disorder (Carlson and

102
Strober 1978), or whether the phenomenology would be similar to

that of adults (e.g., focal delusions).

PHARMCOTHERAPY OF SCHIZOPHRENIC DISORDERS IN ADOLESCENTS

The introduction of neuroleptics in the 1950's was followed by

numerous double-blind placebo-controlled studies of their usefulness for acute schizophrenic episodes and for maintenance to prevent acute episodes in adults (Baldessarini 1977). Plasma level/

response studies have been inconclusive (Sakalis et al. 1972; Van

Putten et al. 1981; Mavroidis et al. 1985; Davis et al. 1985).

Many chronic schizophrenics continue to require custodial care

despite these advances. In part due to the diagnostic issues of

schizophrenia during the pediatric years discussed above, there

are few studies of schizophrenia during adolescence.

There are four reported studies of adolescent schizophrenia in

which the children are not reported to be presenting autistic or

pervasive developmental disordered features. However, this issue

was not specifically addressed in these papers. The first of

these was reported by Shaw et al. (1963). Ninety-one subjects, 7

to 15 years of age, were studied in a double-blind crossover

design. However, it was stated that the time they spent on each

medication was variable. These children were diagnosed using

clinical interview without assessment criteria and were called

"disturbed children." No severity criteria or scales were mentioned. Eight different drugs were used. The authors concluded

that the drugs were useful if careful selection was noted. Lewis

and James (1973) reported on 22 subjects, 4 to 14 years of age,

who were diagnosed by clinical interview. Ten were reported to be

neurotic, four, psychotic, and eight, behaviorally disordered.

The severity measure used was a lo-point scale developed by the

authors for which reliability and validity were not reported.

Subjects received either chlorpromazine 2.5 mg/kg or haloperfdol

.05 mg/kg. Eight of the 22 were reported to have responded;

however, none of the four psychotic children responded. Pool et

al. (1976) reported on 75 subjects, 13 to 18 years of age, who

were studied in a double-blind placebo-controlled design that

lasted for 4 weeks, after a 5-day drug-free period. Their diagnosis, made by clinical interview, was adolescent schizophrenia.

Outcome measures of severity were the Brief Psychiatric Rating

Scale (BPRS), the Clinical Global Ratings of Improvement (CGI),

and the Nurses' Observation Scale for Inpatient Evaluation

(NOSIE). Subjects received either loxapine 87 mg daily (average)

or haloperidol 10 mg daily (average) and also received milieu

treatments. Of the subjects on loxapine, 87.5 percent responded;

70 percent of the subjects on haloperfdol responded; and 36.4

percent of the subjects on placebo responded. Over half of the

subjects on active medication had significant sedation and extrapyramidal side effects. Realmuto et al. (1984) reported on 21

subjects, 11 to 18 years old, who were studied in a single-blind

design. Their diagnosis, based on clinical interview, was schizophrenia. Severity measures were the BPRS and CGI; diagnosis was

made by DSM-III criteria, On the average, the subjects received

103
either thiothixene 0.22 mg/kg or thioridazine 0.26 mg/kg. It was

reported that none of the subjects had a good response, and 50 to

75 percent were sedated. The authors stated that they felt that

their subjects were similar to "process" schizophrenia in adult

patients with unremitting courses.

Issues that need to be addressed are: (1) to differentiate adulttype schizophrenia in teenagers from the autism spectrum; (2) to

differentiate schizophrenia during the teenage years from affective disorder (especially mania and delusional depression); (3) to

perform dose/plasma level/response studies and see if it is possible to obtain optimal therapeutic response without sedation; and

(4) to perform adequately designed double-blind placebo-controlled

studies.

ADOLESCENT AGE-RELATED SIDE EFFECT ISSUES

There are several issues specific to teenagers that need attention

in prescribing psychotropic drugs. One of these is the additive

effects of marijuana and tricyclic antidepressants on heart rate.

Although there is only one report of the combination of marijuana

and nortriptyline (Hillard and Vieweg 1983) in which the marijuana

possibly contributed to a serious tachycardia, all tricyclic antidepressants may elevate the heart rate (Glassman 1984). and marijuana is known to do the same (Meyer 1978). This, therefore, is

an important issue to address. There has been some concern about

the effect of lithium on bone growth during the formative years

(Birch 1980). In adults, it is known that lithium deposits in

bone; however, radiographic studies of the hands of adults who had

been on lithium for years, compared to age- and sex-matched controls, showed no difference in bone density (Birch 1980). It is

not known whether this would also be found in teenagers before

bone growth is complete. There is a question of neuroleptic

impairment of cognition due to sedation (Erickson et al. 1984).

since over half of the adolescents in the two studies in which

this was mentioned were excessively sedated (Realmuto et al. 1984;

Pool et al. 1976). There is a recent report that chlorpromazine

administered for over 6 months reduces plasma testosterone and

luteinizing hormone response to luteinizing releasing hormone in

adolescents (Apter et al. 1983). Although this effect is also

observed in adults, its significance and reversibility in adolescents would need further study. Finally, there is the question of

the long-term effects of lithium on renal functioning. There is

one report of four children who were maintained on lithium at

therapeutic plasma levels who were not noted to have changes in

renal function during the 3- to 4-year period (Khandelwal et al.

1984). However, this was a study of a small number of subjects,

and further studies in this area are needed.

ISSUES OF DRUG STUDIES IN ADOLESCENT SUBSTANCE ABUSERS

One of the main issues is that all adolescents with a history of

substance abuse (whether or not it was substantiated by blood or

104
urine studies at the time of admission) would need a detoxification period, specified in the protocol so that comparable data

with other studies could be obtained. There is, at present, insufficient information on how long after detoxification a psychiatric diagnosis could reliably be made, In this regard, it would

be useful to identify which substances have been abused, so that

the detoxification period would be based on their known wfthdrawal

effects and withdrawal syndromes. The episodic nature of manicdepressive illness dictates that it may be difficult to distinguish a first episode of manic-depressive illness precipitated by

drugs from drug-induced behaviors (Horowitz 1975). It will be

useful through the initial detoxification stage, and in order to

stabilize medication in adolescents who are known to be substance

abusers, to hospitalize them in locked units with care in monitoring what may be obtained on the ward in the way of illicit drugs.

A greater problem for these patients would be outpatient compliance during the maintenance medication phase. Since both lithium

and tricyclic antidepressants are commonly given for a period of 6

months to a year after the person has recovered from the initial

episode (the optimal length of time for teenagers with various

subtypes of affective disorders has never been studied) (American

Journal of Psychiatry 1985), this will be a crucial period if

adolescents are similar to adults, who are likely to relapse if

the maintenance period is too short.

CONCLUSIONS

There are no studies of depressed, affectively disordered, or

schizophrenic teenagers who are also substance abusers and few

adequately designed studies in adults (Kline et al. 1974; Ciraulo

and Jaffe 1981; Viamontes 1972; Ditman 1966). To make matters

more complicated, there are no adequately designed double-blind

placebo-controlled studies of tricyclic antidepressants or other

antidepressants in adolescents with major depressive disorder, or

of lithium in adolescents with mania or bipolar disorder, and only

one reasonably well-designed study of adolescent schizophrenia

(Pool et al. 1976). However, in the latter study, the drugs were

felt to be too sedating in 50 to 75 percent of the subjects to be

clinically useful. Further, it is not possible, at present, to

tell a drug-induced behavior disorder that will be self-limiting

from a drug-induced precipitation of an early or first episode of

manic-depressive illness or schizophrenia.

Although there is currently a consensus among various investigators on the existence of major depressive disorder in adolescents

and agreement that it can be diagnosed using instruments and criteria similar to those used in studies of adults, there are no

data on whether or not tricyclic antidepressants will be effective

treatment for depressed teenagers.

For the manic phase of affective disorder or for adolescents who

switch between mania and depression, there are few diagnostic

studies. There are no well-designed, double-blind placebocontrolled studies, and only two drug studies in which criteria

105
for mania are given. Lithium's effectiveness at the same blood

levels as those in adults is unclear, since several studies combined lithium therapy with tricyclic antidepressants or ECT to

obtain response.

There are too few reports to say whether or not there is a consensus on the existence of schizophrenia during adolescence, which

differs from the childhood autism spectrum, and, if there is

adult-type schizophrenia in adolescents, whether it will respond

to neuroleptics without producing unacceptable side effects.

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ACKNOWLEDGMENTS

Supported in part by National Institute of Mental Health grant

MH40273.

AUTHOR

Barbara Geller, M.D.

William S. Hall Psychiatric Institute

PO Box 202

Columbia, SC 29202

112
Treatment Validity: An Approach

to Evaluating the Quality of

Assessment

Steven C. Hayes

INTRODUCTION

The purpose of treatment research is to identify specific interventions with a beneficial impact for specific types of clients

with specific types of problems (Beutler 1979; Paul 1969). Ideally, a client coming to see a clinician will be more likely to

receive effective therapy because of treatment research.

When treatment research does have such an impact on others it has

a degree of external validity (Campbell and Stanley 1963). In the

context of treatment research, external validity refers to the degree to which the results of a study can be applied elsewhere, to

other clients treated by other therapists. The promise of external validity forms the primary practical basis for conducting

treatment research and, indeed, justifies its Federal funding.

Methodologists have written volumes on the methods available for

achieving internally valid research. External validity is often

virtually ignored, even though an internally valid piece of treatment research without external validity has no applied importance.

This chapter examines research methodology from the viewpoint of

what we want treatment research to do. It asks the question, "If

external validity were the primary guide, would currently popular

research practices need to be modified?"

EXTERNAL VALIDITY AS A HATTER OF MATHEMATICAL NECESSITY

The dominant model of external validity has prevented a proper

concern for the relevance of external validity to the design of

treatment research. According to this model, a correctly designed

study possesses external validity as a matter of mathematical

necessity. Every beginning researcher learns the model--typically

as a theory of proper research method; some students even confuse

it with the scientific method itself. The model is fundamentally

flawed as a guide to the external validity of treatment research

and is never truly followed by treatment researchers, despite

mighty efforts to do so. Furthermore, even if the model could be

113
followed in the real world it still could not deliver the kind of

external validity needed from treatment research.

The dominant model of external validity draws from sampling theory

and probability theory and is closely related to theories of internal validity in group comparison designs. According to the

model, we must randomly select from a known population and randomly assign to groups or conditions. If variability between subjects is low enough (relative to variability between groups), we

conclude that we have an effect. This effect then should also

apply to other random samples from the same population, at some

level of probability. As a matter of mathematical necessity, the

resulting study possesses a degree of external validity.

The mathematical necessity model of external validity has a long

history and powerful intellectual support. At least since the

time of R.A. Fisher, researchers have designed experiments with

one eye on random selection and random assignment. Because both

internal and external validity seemingly flow from the same probabilistic source, few special considerations need apply to external

validity. A properly crafted design necessarily yields both types

of validity.

Unfortunately, no one can implement this model in the world of

treatment research. The problem of drug abuse presents an especially difficult environment for its implementation.

Problems With the Mathematical Necessity Model

We can break down the preliminary issues into four areas: known

populations, random selection, random assignment, and application

to additional samples. Each presents major obstacles to treatment

research. Since the model requires all its elements to maintain

its mathematical integrity, a weakness in even one area seriously

undermines its precision. If the mathematical necessity model is

unrealistic, alternative methods for ensuring external validity

must be found.

Known populations. Treatment researchers can easily name the

populations they seek to study: agoraphobics, alcoholics, depressives, and so on. These populations definitely exist, and we can

describe their defining characteristics in detail (e.g., all people with a given degree of addiction to a given drug). A "known

population" in a statistical sense is not, of course, simply these

conceptually known populations. Theoretically, a known population can be defined as the population for whom the initial probability of being sampled is above zero. If individuals meeting the

conceptual category are totally unknown to the researcher, their

probability of being sampled is initially zero. In the perfect

case, all members of the conceptual population are known and

equally likely to be selected. In this case, the known population

is the same as the conceptual population.

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In treatment research, conceptual populations are virtually never

known populations. Some individuals may have a problem, but it

may not be detected either by others or by themselves. Others may

know they have a problem but fail to seek treatment. Still others

may seek treatment in a manner prohibiting their identification.

In the real world populations are detected by their contact with

certain cooperative individuals or institutions. The events

producing either the contact or the cooperativeness of the institution can distinguish this population from the conceptual population in important ways. For example, we may have access to poor

people entering a county hospital, but not to middle class people

treated by a private practitioner.

The area of drug abuse shows this problem clearly. The very

nature of drug abuse leads individuals to avoid contact with

authorities. Most drug abuse will never be detected. It is possible, of course, to redefine the conceptual population to reflect

these realities. We could study drug abusers who are in treatment, for example, with the rationale that even if this population

is unrepresentative of drug abusers, the consumers of treatment

research could only apply its results to individuals in treatment

anyway.

This strategy still does not yield a known population matching the

conceptual population. For example, drug abuse has recently become much more common in middle and upper socioeconomic groups.

Professionals may frequently contact these individuals and may

seek guidance from the research literature. Unfortunately, these

populations are obviously underrepresented in the populations

available for research. Should a private practitioner seeing an

upper middle class, suburban professional who abuses cocaine rely

on data collected from studies of unemployed, undereducated,

inner-city cocaine abusers? Perhaps, but this reliance cannot be

justified by the mathematical necessity model of external validity, since one of its major precepts has now been violated.

Generalization to the suburbanite does not derive from mathematical necessity.

Random selection. Even if it were possible to specify a known

population matching a conceptual population, we still would have

the problem of random selection. Random selection occurs when the

probability of a single selection is 1/n for each member of the

population, where n equals the total known population. If the

probability of selection is higher or lower than 1/n for given

subjects, the sample will be biased. In a sense, you can think of

this as altering the known population. Subjects can be more or

less known--more or less visible in the population. When a given

subject is more likely to be selected, everyone else is slightly

less likely to be selected and vice versa.

In the real world, subjects are selected for practical reasons in

treatment research. A given hospital may allow access to a researcher, while another may not. Any characteristic leading people to use that particular hospital now also distorts the sample.

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For example, the hospital may draw its clients from a particular

region, may enjoy a good reputation among particular religious or

ethnic groups, or may be known to use treatment modalities that

are attractive to certain kinds of people. Members of the conceptual population who are without these characteristics are thus

less well-known. Once again, it is possible to redefine the known

population. We might, for example, define the population as all

persons in a given hospital. Rarely would anyone want to generalize the results of their research to such a population, however.

Thus, this maneuver seemingly meets the letter of the mathematical

necessity model but does not increase its usefulness.

Even with the population of people in a given hospital, random

selection is rarely possible. Agreeing to participate in research

is a significant behavioral act. Clients willing to be subjects

surely differ from clients unwilling to be subjects. Researchers

sometimes make mighty efforts to show that the demographic characteristics of the two groups are similar. However, drawing the

implication that the two groups are thus functionally similar is

not justified by sampling theory. We do not know whether other

unmeasured characteristics (e.g., attitudes, cognitive style, personality) distinguish the groups, and we do not know if these

characteristics alter the applicability of treatment research from

one to the other. Demographic characteristics are far too crude

for this purpose. We do know the groups are different, but we do

not know if the difference is important. Based on mathematical

necessity, we can only generalize to the population of persons

with a particular disorder in this institution who are willing to

participate in research of exactly this kind. No one is interested in generalizing to such an odd population.

Random assignment. When a sample has been selected, subjects are

randomly assigned to groups. This part of the model is more feasible than other parts, but even here trouble arises. Subjects

decline assignment to particular conditions. Subjects may drop

out of the study more in one condition than in another. These

problems are well-known, of course, and attempted solutions are

common. For instance, researchers will often conduct a statistical test to see if dropout rates differed. For this purpose, however, statistical inference is not a great aid. Even without a

difference in dropout rates, dropouts can bias a sample. Suppose

we are comparing two treatments. One treatment works differently

with cooperative and uncooperative people. Cooperative people

respond to the treatment, but the treatment is absolutely iatrogenic for uncooperative persons. The second treatment is moderately effective for both cooperative and uncooperative people.

Imagine all uncooperative people drop out of the study, thus the

dropout rates are likely to be equal in both groups. The first

treatment may now look more effective with this sample but not

with the original sample.

Applicability to nonrandom samples. When you put together these

three problems--known populations, random selection, and random

assignment--it becomes clear that the mathematical necessity model

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of external validity does not exist in the world of treatment

research.

theory.

I am not attacking sampling theory or probability

If the model could be implemented, studies would indeed

possess a kind of external validity. Ironically, even then the

kind of external valfdfty such studies would possess would not be

of use to practitioners and most consumers of treatment research.

If the model were followed, research results would necessarily

apply only to other random samples from the same population. The

model can promise no more. The model does not promise that every

subgroup in the sample will respond in the same manner as the entire group. A given treatment can work well with the population

overall and be fatrogenic with a subpopulation. The effects of

the treatment on nonrandom samples are unknown. Clinicians, however, never randomly sample from treatment populations. How an

individual client ends up being treated by a given clinician is

definitely nonrandom. Clients seek out particular clinicians for

all kinds of nonrandom reasons: reputation, location, sex, race,

fees, availability, hours, and so on. How are we to know whether

the nonrandom characteristics causing an individual to be treated

by someone do not also cause them to be in a subgroup for whom the

overall results will not apply? We cannot know beforehand.

In summary, the mathematical necessity model collapses completely

when examined as a means to ensure the external validity of research. We do not have a clear known population. Even if we did,

we cannot randomly select. Even if we could, we often cannot randomly assign. Finally, even if all of this were not true, we cannot apply the results to nonrandom samples even though these are

the only kinds of samples clinicians ever treat.

ALTERNATIVES TO THE MATHEMATICAL NECESSITY MODEL

The mathematical necessity model is the only one to promise external validity as an inherent possession of a well-designed study.

Every other approach to external validity relies on logical generalization (Hersen and Barlow 1976). The principle of logical

generalization says that: if a given treatment is shown to be

successful with a given client, it is more likely to be successful

with another to the extent that the two clients are similar. This

principle makes no mathematical claims. It is not based on sampling theory or probability theory but is simply logical, based on

our experience with the world.

Logical generalization can be found both in group comparison

strategies and in single-case designs. It is most obvious in the

latter, because group comparison strategies often are rationalized

in terms of sampling and probability theory, and it is easy to

miss that the mathematical necessity model of external validity is

not being used.

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Homogeneous Groups

One alternative strategy is the homogeneous group strategy. Subjects are selected according to a particular set of well-defined

characteristics. If a given treatment works with this homogeneous

group, then it seems more likely to work with others with the same

set of characteristics. Note that the principle involved here is

logical generalization. It is not necessary to pretend that the

homogeneous group is a random sample from a known population.

The homogeneous group strategy is reasonable and deserves greater

use, although it is difficult to implement and has certain inherent limitations. Difficulty in implementation arises because even

simple group comparison research can require large numbers of subjects. A small set of carefully defined subject characteristics

can quickly make a large group impossible to collect; therefore,

the typical compromise is to limit the subject selection criteria

to a few gross characteristics. Unfortunately, this undermines

the principle of logical generalization supporting the strategy in

the first place. If the group is not very homogeneous, how can I

have confidence that my clients are like those in the group?

There are other difficulties. Some of the most important populations are difficult to reach. While it may be very important, for

example, to do some research on upper middle class professionals

who abuse cocaine, these are the very people we may not be able to

find in large numbers.The problems of random assignment also

remain in this type of research.

Even when we can generate large homogeneous groups, we know that

there are surely subgroups within the groups. Some subjects may

improve and others may not. How are we to know whether our clients are like the successes or the failures? I will return to

this critical issue shortly.

Homogeneous group research shows that logical generalization can

be used to construct alternative research strategies. Most often,

however, the group nature of the research disguises this principle. Researchers often act as if the mathematical necessity model

of external validity applies to homogeneous group research simply

because subjects were randomly assigned to groups, as far as that

was possible. This confusion of issues has unfortunate side effects since failure to see the principle of logical generalization

restricts its use in other ways.

Correlational Analyses of Factors Related to Outcome

Another group comparison strategy often recommended is also based

on logical generalization. It is possible in very large group

studies to correlate various subject characteristics post hoc with

improvement. Even if the original sample is not a random sample

from a known population, it is logical to believe that if improvement is correlated with certain subject characteristics then clients who share those characteristics are likely to respond

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similarly. Correlational strategies occur in two forms. In one,

particular characteristics are used to block subjects into various

groups, arranged along a continuum. For example, high and low

socioeconomic status subjects might be compared. In a second type

of strategy, no groups are formed, but the various characteristics

are examined for linear or other relationships with outcome.

Post hoc correlational strategies are well-known and have a long

tradition in clinical science. For example, a review of research

in depression by Bielski and Friedel (1976) suggested tricyclic

medication is most helpful given higher social class, insidious

onset, anorexia, weight loss, middle and late insomnia, and

psychomotor disturbance. It is likely to be least helpful given

neurotic, hypochondriacal, and hysterical traits, multiple prior

episodes, and delusions (Paykel et al. 1973).

The difficulty with correlational strategies is that if we include

more than a few subject characteristics we quickly require either

absolutely enormous groups or often will be basing our correlations on very small numbers of similar subjects. Correlations

based on small sets are notoriously unreliable, and indeed correlational research of this sort is known for the variability in

the results obtained across studies.

In addition, we must decide beforehand exactly what subject characteristics will be measured for all subjects. This is troublesome, because some of the most important variables are probably

not the obvious demographic variables or universal measures usually examined in research of this kind. Post hoc correlational research-tends to rely on measures such as the Minnesota Multiphasic

Personality Inventory (MMPI) (Shealy et al. 1980; Strassberg et

al. 1981), locus of control (Poole et al. 1981; Woodward and Jones

1980), self-efficacy measures (DiClemente 1981; Williams et al.

1984), or demographic characteristics (Dumas and Wahler 1983;

Elsworth et al. 1979) to predict patient outcome. It is easy to

see why. These are the types of measures commonly collected at

the beginning of treatment and can easily be examined for post hoc

correlations with outcome.

Unfortunately, research of this sort has often failed to find consistent or strong correlations between these measures and outcome.

It is not uncommon to see studies reporting correlations that

account for 5 to 10 percent of the variance in outcome (Luborsky

et al. 1979). The larger correlations sometimes seen are rarely

cross-validated in subsequent research. Despite the large number

of studies being reported of this type, there is little evidence

that they are leading to greater external validity for the output

of treatment research. Why are they not leading to increasingly

sophisticated rules of generalization?

Probably the most difficult problem is the weakness of the correlational strategy in determining individual successes and failures. There are three kinds of variability in any treatment

research study. Some variability is due to inconsistent

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measurement. This is false variability because it exists only in

the data, not in the phenomenon being measured. Other variability

is caused by extraneous factors. Extraneous factors are those

that are not manipulated systematically and are allowed to vary.

Variability due to extraneous factors, such as maturation or coincidental experiences, is actual variability in the phenomena.

Finally, there are various kinds of treatment-related variability.

Treatment effects can be produced by nonspecific or specific components of treatment, The effects produced by specific components

may be due to the theoretical variables the researcher meant to

manipulate or to other specific variables unintentionally

manipulated.

All treatment research seeks to distinguish variability due to

treatment from the other kinds. Some types of treatment research

also seek to distinguish particular subcomponents of treatmentrelated variability from each other, In group comparison research, these distinctions are made at the level of the group.

Consider a typical group comparison study in which an experimental

and a control group are measured pre and post. We can distinguish

treatment-related variability from other kinds by using the variability between subjects in the two groups as a kind of rubber

ruler against which treatment differences can be measured. We

assume that inconsistent measurement and extraneous factors are

operating but are influencing both groups equally. If variability

between subjects within the groups is large, these nontreatment

sources of variability are also large; thus, only large mean difference between the groups are thought to be statistically significant. If the variability within the groups is very small, even

small differences between the groups is probably due to treatmentrelated variability.

This is an eminently logical model with which I have no quarrel,

Note, however, that the correlational studies correlate improvement of individuals with characteristics of these same individuals. This is troublesome because in the great majority of group

comparison studies all three sources of variability are confounded

at the level of the individual. If a given person improves from

pre to post we cannot say, for that individual, that improvement

is due to inconsistent measurement, extraneous factors, or

treatment-related variability of various kinds. It is only at the

level of the group that the three types of variability are distinguished. Thus, correlational strategies of this kind correlate

subject characteristics with improvement due to all three sources

of variability. It is no wonder that correlational strategies so

seldom lead to large or replicable correlations.

One improvement is to identify treatment responsiveness and differential treatment effects at the level of the individual--that

is, to use "single-case" experimental designs (Barlow and Hersen

1985; Barlow et al. 1984). "Single-case" is a bit of a misnomer.

The issue is one of level of analysis and not one of number. A

single-case approach will often require just as many subjects as

the previous approach, but since individual assessment results

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will now be correlated with individual treatment effects, stronger

external validity for these correlations seems likely. Seeing the

important role of sensible analyses at the level of the individual

also opens up the possibility of contributions to the research

literature by a large series of smaller n designs, not just

through a smaller series of large n designs.

Single-case analyses can be built into most group comparison designs. Consider a typical two group design with an experimental

and control group. Adding the needed dimension of intensive

analysis can be accomplished with a minimum of three steps:

repeated measurement, establishment of intrasubject variability,

and within-subject comparisons. For example, at a mfnimum subjects in the experimental group could be exposed to a baseline

phase, while measures were repeatedly taken. If the data were

relatively stable (Hayes 1981), this could be followed by a treatment phase in which repeated measurement continued. The resulting

"A/B" design is probably the lowest level single-case design, but

it does begin to increase the precision of the identification of

individual successes and failures. Repeated measurement gives

some indication within subject of the degree of variability due to

measurement inconsistency and extraneous factors. If change is

noticeable after the implementation of treatment, improvement is

probably either due to treatment or to a coincidental extraneous

factor. The strength of the analysis can be increased by adding

intrasubject replication of the apparent treatment effects (e.g.,

through an A/B/A/B design in this example). By using single-case

designs for individual subjects in addition to the usual pre/post/

followup measurement, the researcher can: (a) still analyze in a

pre-post fashion, if desired; (b) identify at the level of the

individual the successes and failures that seem probably due to

treatment in each group; and (c) begin to correlate subject

characteristics with success and failure of individuals due to

treatment. Some subjects, for example, may have improved or

deteriorated significantly but in such a way that it cannot be

said with confidence that treatment was the cause. Others may

have shown ambiguous results. By considering these subjects

separately from subjects showing clear effects due to treatment,

the relationship between individual subject characteristics and

individual treatment responsivity can better be determined. Thus,

single-case analyses can be incorporated within group comparison

designs to increase the analytic power of the research.

Other Uses of Single-Case Designs

Single-case designs can also be used by themselves and gradually

collected into series of studies encompassing many subjects. The

details of conducting single-case experimental research are well

known (Barlow and Hersen 1985; Barlow et al. 1984). I will not

review them here. There are several aspects to the proper use of

single-case designs that seem worth mentioning.

First, as emphasized earlier, the issue of number must be distinguished from the issue of level of analysis. We cannot know how

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clients will respond to treatments until the treatments are used

with many clients. This raises the unsolved question of how to

collapse studies using single-case analyses into a series of

studies. We may need a kind of meta-analysis for single-case

data, though hopefully these techniques will be more practical and

straightforward than the procedures available for group studies.

This also implies that we should fund research programs using this

approach, not just specific studies.

Second, single-case research is best done in an analytical

fashion. Client and treatments should be described carefully.

When we identify successes and failures due to treatment, we

should then attempt to determine why these persons succeeded or

failed. The best way to do this is to treat the failures and attempt to find a successful intervention based on hypotheses about

the source of the failure. We should seek to identify (in a conceptually consistent manner) dimensions relating to success and

failure. In a sense, the purpose of this research would be to

identify functionally homogeneous groups, rather than to rely on

the structural characteristics of client variables to determine

homogeneity.

Third, the research strategy encouraged by single-case research is

fundamentally different from that supported by the group comparison model. Single-case researchers must constantly interact with

their data and allow it to modify the design as additional information arises. Federal grant agencies must take care not to tie

single-case research into a straightjacket. For example, it is

foolish to insist that the length of phases be specified a priori

(e.g., based on number of assessment sessions), since only stable

data will allow the observation of subsequent effects, and the

actual achievement of stability cannot be specified beforehand.

Again, funding research programs rather than specific studies

seems advisable. Methodological modifications, however, should

not be arbitrary. It will be necessary to develop separate standards for the specification of research strategy in single-case

research.

Finally, single-case research quickly confronts the researcher

with how little we know about behavior and its measurement. Often

the results of single-case research will be ambiguous. We must be

prepared to deal with that eventuality. In many cases, it will

not be clear how to analyze single-case data, although usual statistical procedures now appear often to be appropriate (Huitema

1985). If a researcher can produce a series of organized singlecase studies, hopefully it will lead to clear and powerful demonstrations of experimental control as the components of the

analysis come together. In this case, ambiguity is not a difficulty. Once again, emphasis on research programs seems warranted.

OTHER DIMENSIONS OF EXTERNAL VALIDITY

I occasionally ask students why they would ever replicate a study.

The usual answer is "to see if you do the same thing if you get

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the same results," but of course that cannot be correct. In a determined world. if you do the same thing you have to get the same

results. The purpose of replication is to see if the description

of the study is enough to lead you to do the same thing. If so,

then you will get the same results.

In the same way, external validity tests the validity of our

formulations, not our results. What we give away in a piece of

research is a verbal description of what is important to produce

particular ends. How can we make that more likely? One way,

already mentioned, is to include an intensive analysis of the individual in the study so that successes and failures due to treatment can be identified at the level of the individual. There are

other considerations as well.

Treatment Integrity

Often we describe our treatments post hoc and may fail to determine whether we actually followed our own advice. This is an

example of how internal and external validity can become seriously

disconnected. We can do a study and be absolutely certain that

our treatment produced an effect. Its internal validity can be

unquestionable. If we cannot describe our treatment with precision, however, the study cannot have external validity because we

have no verbal formulations to give away,

There are several aspects to a solution to this problem. First,

we must measure the behavior of treatment provlders and determine

whether they are actually followfng a given protocol. Careful

assessment of the independent variable is just as important as

assessment of the dependent variables. (Peterson et al. 1982;

Yeaton and Sechrest 1981). If we did not do what we said we did,

then how can others expect the same results? Second, we can test

the degree to which our protocol is effective In generating the

appropriate clinical behavior. For example, if we have a therapist manual developed before intervention, we can test to see if

the results of reading the manual are behavior consistent with the

protocol. If not, our manual is inadequate, because when we give

it to other researchers it will also fail to produce consistent

treatment. If additional training is required, this should be

specified and tested to see if others can produce the same therapist behavior based on the training procedure specified. Thfrd,

we must specify the conditions under which treatment was applied

and check to see if the descriptions are, in fact, accurate.

Finally, we must measure client compliance wfth treatment and the

presence of possible extraneous factors. Essentially we must

measure the variables influencing clients much more. Client failure to follow a treatment is a very different issue than treatment

failure when followed. The same advice applies to control conditions. If a control subject seeks out other treatment resources,

formally or informally, this is a very different subject than a

control subject continuing the usual routine. Monitoring of this

sort should continue throughout the study. For example, extended

followups are of little intellectual use if we do not know what is

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happening during the followups. Presumably failures and successes

in maintenance are caused by particular events. If we are not

measurfng the events impfnging on our clients during this time we

will not have a clue about why some succeed and others do not.

Principles of Treatment

Imagine the task you would have if you attempted to describe every

event that has happened over the last hour around you. If every

detail had to be specified, it could take you many months just to

describe most of the major events in exact detail: every sound,

every sight, every smell, every taste, every feeling, every behavior, and so on. Clearly, it is also impossible in a research

project to specify every treatment event in precise detail. In

verbal psychotherapy, for example, a therapist varies in tone of

voice, posture, gestures, expressions, motions, dress, a thousand

other variables. How can we "give away" treatment knowledge if we

cannot be encyclopedic?

One major solution is to develop principles of intervention that

underlie successful techniques. Rather than describe techniques

one at a time, we need at least some research that will sift out

their essential components and describe them in theoretically

meaningful ways. Principles are much easier to give away than

idiosyncratic details. Many researchers have complained that

applied psychology is becoming more and more technically oriented

in its research (Deitz 1978; Hayes et al. 1980). The problem with

technical research is that we develop knowledge with less and less

of an interest in external validity. Even if a technique can be

described in full detail, if we do not know the principles involved, how can we generalize to other problems or populations.

Must we have a separate effort for every kind of client, and every

specific problem?

The kinds of principles that relate specific client, therapist,

situational, and treatment characteristics will most readily

emerge from careful experimental analysis of these interactions.

Single-case research often promotes this kind of work since failures are followed by an attempt to determine and correct the

source of the failure for that client. Again, it is important

that we follow the leads our data gives us. Too many limits

should not be placed on design modifications. The inductive,

technique-building approach used when single-case designs are

being applied to small numbers of subjects to analyze a phenomenon, dictates that the data guide the researcher as it comes in.

Treatment Utility

I have been emphasizing that for research to be generalizable to

the clinical situation we will need to know more about how client,

therapist, and situational variables interact with treatment.

Most of this work will be done post hoc, as a matter of careful

specification of these variables. Some of it can also be done

a priori. In these studies, factors thought to interact with

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treatment are systematically manipulated in the study. If a relatfonship is predicted a priori and is successfully demonstrated,

then some degree of robustness (external validity) in our conceptualization has already been shown. Thfs has been termed "treatment utility" (Hayes et al. 1986).

There are a number of examples of treatment validity research

addressing the question of the value of client classification,

although they are perhaps surprisingly rare in the psychotherapy

literature given their obvious importance (Hayes et al. 1986). An

example of a treatment validity study is provided by McKnight et

al. (1984). Three subjects each were obtained who were depressed

and had: (a) poor social skills but few irrational cognitions;

(b) irrational beliefs but adequate social skills; or (c) problems

in both areas. After a baseline phase, all subjects received both

social skills training and cognitive therapy in randomly alternating sessions (what is known as an Alternating Treatments Design)

(Barlow and Hayes 1979). Subjects with only social skills problems improved most following social skills training, while the

reverse was true for subjects with problems only in the cognitive

area. Subjects with problems in both areas improved as rapidly in

either situation. Thus, the suspected relationship between these

patient and therapy types was confirmed.

CONCLUSION

Essentially, the treatment validity approach tests our view of

functionally homogeneous groups. Since it does this a priori, is

experimental and not just correlational, and concentrates on a

single dimension or small number of dimensions, it does not fall

prey to the same problems of the homogeneous group and correlational approaches. It is also well suited for either group

comparison or single-case designs.

In summary, consideration of the issue of external validity shows

that both the kinds of questions we are asking in treatment research and the various methods we use to answer these questions

seem out of line with the needs of treatment research consumers.

This chapter provides several alternatives that might bring

treatment research into better coordination with the needs of

clinicians.

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In: Franks, C.M., ed. Behavior Therapy: Appraisal and Status.

New York: McGraw-Hill, 1969. pp. 29-62

Paykel, E.S.; Prusoff, B.A.; Klerman, G.L.; Haskell, D.; and

DiMascio. A. Clinical response to amitriptyline among depressed

women. J Nerv Ment Dis 156:149-165, 1973.

Peterson, L.;Homer,A.L.; and Wonderlich, S.A. The integrity of

independent variables in behavior analysis. J Appl Behav Anal

15:477-492. 1982.

126
Poole, A.O.; Dunn, J.; Sanson-Ffsher, R.W.; and German, G.A. The

rapid smoking technique: Subject characteristics and treatment

outcome. Behav Res Ther 20:1-7, 1981.

Shealy, R.C.; Lowe, J.D.;and Ritzler, B.A. Sleep onset insomnia:

Personality characteristics and treatment outcome. J Consult

Clin Psychol 48:659-661, 1980.

Strassberg, D.S.; Reimherr, F.; Ward, M.; Russell, S.; and Cole,

A. The MMPI and chronic pain. J Consult Clin Psychol 49:220-

226, 1981.

Williams, S.L.; Oooseman, G.; and Kleifield, E. Comparative

effectiveness of guided mastery and exposure treatments for

intractable phobias.

Woodward, R.,

J Consult Clin Psychol 52:505-518, 1984.

and Jones, R.B. Cognitive restructuring treatment:

A controlled trial wfth anxfous patfents. Behav Res Ther

18:401-407, 1980.

Yeaton, W.H., and Sechrest, L. Critical dimensions in the choice

and maintenance of successful treatments: Strength, integrity,

and effectiveness. J Consult Clin Psychol 49:156-167, 1981.

AUTHOR

Steven C. Hayes, Ph.D.

Department of Psychology

University of Nevada

Reno, NV 89557-0062

127
Adolescent Drug Use:

Suggestions for Future Research

Norman A. Krasnegor

INTRDOUCTION

The purpose of this paper is to provide suggestions for research

initiatives in the field of adolescent drug abuse treatment. The

recommendations given are predicated upon a biobehavioral perspective that focuses upon developmental psychobiology and child

development. These disciplines are viewed as a relevant framework

for asking questions that can lead to the knowledge base necessary

for establishing effective intervention strategies for the prevention and treatment of this public health problem.

ADOLESCENCE: A TIME OF CHANGE

Human development is one of the most complex processes in

nature. From birth, babies present themselves to the world as

being at once precocial regarding their cognitive and sensory

faculties (Gottlieb and Krasnegor 1985) and altricial regarding

almost all their others. This latter state of affairs makes

children almost totally dependent for their well-being upon the

largess of their caregivers. Traditionally, parents in our

society in their role as caregivers provide the means to sustain

their offspring until they attain independence. Along this

developmental trajectory, all children and parents (caregivers)

who survive encounter that enigmatic aspect of ontogeny termed

"adolescence."

This period is one of the least understood phases of development.

It is a time of enormous change biologically and psychologically

for the individual. Beginning usually anywhere from the 10th to

12th postnatal year of life, the period spans the teenage years

and concludes by the start of the third decade of life. Adolescence is marked by a spurt of bodily growth that dramatically

alters the individual's appearance. It is a time when endocrine

surges trigger the onset of puberty (menarche and breast development in girls and spermatogenesis, facial hair, and voice changes

in boys). Further, it is an epoch during which children experience and exhibit mood swings that operationally affect how they

128
behave toward others and vice versa. It is a time, too, when

cognitive and perceptual shifts often lead to confusion for the

adolescent and his/her parents about issues of responsibility,

conformity, and independence. As if these factors were by themselves not complex enough, one must add to the picture the variance associated with the timing of development. Thus some

children are early and others are late "bloomers," a factor which

can have multiplicative effects in its deleterious impact upon the

behavioral development of children. In short, adolescence is

synonymous with upheaval and biobehavioral modifications which, if

successfully completed, transform the child into an adult.

RISK-TAKING BEHAVIOR

From the behavioral perspective, adolescence is associated with

experimentation by boys and girls in the realms of social relationships, diet, rest/activity cycles, ideas, dating, and roles.

All such activities, except possibly at the extremes of each

dimension listed, are both expected and normal. Institutions

become interested when adolescents exhibit behavior which exceeds

normative expectations and causes harm to themselves and others.

That interest becomes galvanized into action when the behavior in

aggregate entails costs, either economic or societal, that are

unacceptable. It is in this domain that teenage drug use resides.

Even though for many, if not most teenagers, drug use is just

another form of experimentation that, in the natural history sense

(Vaillant 1966), has no measurable consequence for the individual,

society still has a legitimate interest. The reason is that the

residual number of children who do not spontaneously stop but go

on to have drug-using lifestyles is measurable and growing

(O'Malley, this volume). More important, there is extant a growing trend in our teenage population of risk-taking behavior which

deserves further examination. This rubric subsumes a class of

consummatory behaviors whose incidence and prevalence are increasing and, therefore, are associated with unacceptable costs both

economically and socially. The list is familiar to most who have

examined the epidemiological characteristics of what pediatricians

have termed the "new morbidity" in children (Haggerty et al. 1975;

Haggerty 1986). Specifically, the domain includes teenage smoking, drinking, drug use, pregnancy, eating disorders (anorexia and

bulimia), and accidental injury. Viewed from this broader perspective, drug use can be seen as being only one of a number of

risks to which teenagers subject themselves.

Some behavioral biologists have suggested that many of the behaviors involved in the risks teenagers take may have a common neurobiological basis. Weisz and Thompson (1983), for example, have

argued that substances (e.g., drugs, alcohol, food, etc.) which

act to reduce the effects of stress or the aversiveness of stimuli

may have a common linkage to the endogenous opioids. The opioid

system itself has a hypothetical function of being involved in

adaptive behaviors such as learning, responsiveness to stress,

conditioned fear, and defensive behavior (Krasnegor 1979).

129
Parallel with these issues, one must comment upon the upheavals

that are occurring in American families, the milieu in which child

rearing traditionally takes place.

FAMILY TRENDS AND CHILD DEVELOPMENT

In the past 15 years, the rate of divorce has dramatically increased in the United States to the point where the probability of

that outcome is nearly one in two. Thus the number of children

who have and are experiencing the concomitant emotional and physical stresses associated with the breakup of families and altered

living arrangements is also increasing. Coupled with that observation is the trend for children to be raised by a single-parent

head of household (Hofferth 1985). Demographers have estimated

that, if current trends continue, the proportion of children

raised in one-parent families will increase, as will the number of

childhood years spent in such families (Radish et al. 1984).

Further, these same researchers indicate, based on projected data,

that one-third of the childhood years of whites and three-fifths

of the childhood years of blacks born in 1980 may be spent with

only one parent.

In addition, with the advent of the shift in women's roles from

primarily being housewives to entering the world of work, many

children are being cared for by people other than their parents

(Presser 1982). Many younger children are looked after in day

care centers or, in the case of teenagers, left on their own

recognizance (latch-key children). A recent conference sponsored

by the National Institute of Child Health and Human Development

(NICHD) on the impact of divorce, single parenting, and stepparenting on children attests to the importance that public health

officials and researchers attach to this topic for development of

our children (Hetherington and Arasteh, in preparation). This

topic will undoubtedly be a fruitful area of research for developmentalists for the rest of this century and is pertinent to the

specific issue of initiation of drug use dependence.

THE DEVELOPMENT OF CONTROL

Given these factors and the potential for turbulence on any or all

of the multiple dimensions that comprise the biopsychosocial

framework for adolescent development, it is not surprising that

today's teenagers are confronted by very different stressors than

were their parents. In general, the milieu for child rearing is

giving two different messages to our children. On the one hand,

parents by their own choices in lifestyle are saying that children

have to be more independent and thereby take more personal responsibility for "growing up." On the other hand, children are being

told that they do not have the authority to engage in behaviors

(smoking, drinking, intercourse, etc.) which adults reserve for

themselves. At issue in this dilemma is the concept of control.

Useful questions on this issue relate to: (1) Who is in control

of whom? (2) Where does control reside (internally or externally)? and (3) How does one attain control?

130
In the often confusing time of adolescence, children are confronted by the problem of dealing with the demands made by caregivers about routines such as going to school, studying, chores,

and interpersonal relationships, requirements which often conflict

with their own perceived agenda of important activities. In this

context, control is associated with learning discipline (i.e., the

ability to deal effectively with conflicts).

The locus of control is another dimension on which this concept

requires clarification, as it affects the behavioral development

of adolescents. Particularly around the time of puberty, the concept of self at the emotional, perceptual, and cognitive levels

undergoes change. This process entails a redefinition of where

the sources of control reside. The teenager is experienced with

the external controls impinging from the larger social environment

that can be superficially compressed along the dimension YES----

MAYBE ----NO. What they begin to experience in psychological and

emotional terms is the struggle at the cognitive level between

their own goals and desires that originate from "within" and the

conflicting demands for adherence to the expectations of significant others who can enforce compliance through the application of

sanctions.

Successful mastery of such control issues in part helps to define

the transition from adolescence to adulthood. Failure to attain

mastery is frequently signaled by the extremes associated with

risk-taking behaviors. That is to say, children may engage in

escape or avoidance behavior to keep from having to resolve conflicts, particularly those having to do with control. The use of

drugs is one high-probability behavior that is likely to be used

by teenagers as a coping mechanism to reduce stress. Alternatively, such behavior may be a way for adolescents to say, "I'm a

grown-up."

RESEARCH PRIORITIES

Based on the observations made above, priorities for treatment

research emerge that fall within the bounds of developmental

psychobiology and behavioral pediatrics.

Psychobiology of Risk-Taking Behavior

Regarding developmental psychobiology, it would seem prudent to

investigate at the basic level the role of endorphins in the onset

of risk-taking behavior. Specifically, it is recommended that

research be undertaken to study the development of the endorphin

system early in life. In particular, it would be useful to study

the effects of stress on the endorphin system in organisms at the

onset of puberty to determine whether environmental stressors at

this "critical period" lead to increased probability of drug use

during that and subsequent periods of the life cycle. The research initiative should employ a primate model in the context of

a behavioral pharmacological approach. Major independent variables could include chronic stress tasks that have high demand

131
characteristics (e.g., vigilance, avoidance/escape, etc.).

Dependent measures could include rate and amount of selfadministration of drugs with concomitant assessment (before,

during, and after) of the endogenous peptides system. Some work

in progress that would be useful to guide researchers is that of

Dr. Seymour Levine (in press), of Stanford University, who is

studying the effects of separation, stress on the endorphin system

in juvenile squirrel monkeys.

Locus of Control

A second area of importance is work to gain an understanding of

"locus of control." In particular, studies directed at gaining

basic knowledge of how this behavioral domain develops normally in

children are necessary. Along these same lines, studies of atrisk adolescents who fail to develop locus of control could help

in determining parameters of such learning that are impaired.

Knowledge gained could aid in the design of behavioral treatment

strategies to shape effective learning of control and thereby

reduce the chances of risk-taking behavior.

Screening

A third recommended initiative could be launched in the domain of

behavioral pediatrics (Krasnegor et al. 1986) regarding primary

prevention of drug abuse. This would entail developing psychometric and biochemical indices to predict those children who are

at risk (Kellam et al. 1979). If such screening procedures could

be successfully developed, they could be used by pediatricians and

family practitioners to provide anticipatory guidance to parents.

These specialists are the professionals most likely to see such

children prior to the onset of drug use. Early detection and

intervention might well prevent those at risk from initiating use.

Family Therapy

Research should be continued and broadened into family therapy.

Since the statistics cited above indicate that the family is

changing, more information is needed about whether such changes

are affecting development in those dimensions which would influence deviance from expected behavioral norms. Also, the work

described by Patterson and his colleagues (this volume) provides

an excellent example of the type of empirical work that should be

expanded so that effective therapeutic modalities can become

available to deal with the scope of the problem presented by

adolescent drug abuse.

Skills Training

Finally, research on how to teach children basic decision-making

skills and an understanding of the relationship between behavior

and consequences needs to be expanded (Botvin and Wills 1985).

This domain includes developing educational packages on assertiveness to be taught to at-risk children. Also needed are effective

132
training packages to teach children how to differentiate between

the immediate and long-range consequences of their behavior, particularly as such consequences affect their health. Research

should be targeted on developing materials that can be used by

health educators and health care providers.

CONCLUSION

In summary, these recommendations focus upon a series of basic and

applied areas of research deemed necessary for the development of

primary and secondary prevention of drug use among our nation's

children. The knowledge gained from such initiatives should provide public health officials, physicians, educators, and parents

with the basic tools to effectively help treat this growing public

health problem.

REFERENCES

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Haggerty, R.J.; Roughman, K.; and Pless, I.B., eds. Child Health

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Levine, S. Psychobiological consequences of disruption in mother/

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321.

AUTHOR

Norman A. Krasnegor, Ph.D.

Chief, Human Learning and Behavior Branch

National Institute on Child Health

and Human Development

National Institutes of Health

Bethesda, MD 20892

134
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Plckens, Ph.D., eds.

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.

82 OPIOIDS IN THE HIPPOCAMPUS. Jacqueline F. McGinty, Ph.D., and

David P. Friedman, Ph.D. eds.

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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

IN PRESS

80 NEEDLE-SHARING AMONG INTRAVENOUS DRUG ABUSERS: NATIONAL AND

INTERNATIONAL PERSPECTIVES. Robert J. Battjes, D.S.W.. and Roy W.

Pickens, Ph.D., eds.

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.

82 OPIOIDS IN THE HIPPOCAMPUS. Jacqueline F. McGinty, Ph.D., and

David P. Friedman, Ph.D. eds.

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National Institute on Drug Abuse

NIH Publication No. 94-3712

Formerly DHHS Publication No. (ADM) 88-1523

Printed 1988

Reprinted 1994