RESEARCH ANALYSIS

and

UTILIZATION SYSTEM

Prevention Research:

Deterring Drug Abuse

Among Children and

Adolescents

U. S. DEPARTMENT OF HEALTH AND HUMAN SERVICES

Public Health Service • Alcohol, Drug Abuse, and Mental Health Administration

Prevention Research:

Deterring Drug Abuse Among

Children and Adolescents

Editors:

Catherine S. Bell, M.S.

Robert Battjes, D.S.W.

Division of Clinical Research

National Institute on Drug Abuse

NIDA Research Monograph 63

A RAUS Review Report

DEPARTMENT OF HEALTH AND HUMAN SERVICES

Public Health Service

Alcohol, Drug Abuse, and Mental Health Administration

National Institute on Drug Abuse

5600 Fishers Lane

RockviIle, Maryland 20857
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 Institute

Troy, New York

Richard E. Belleville, Ph.D.

NB Associates, Health Sciences

Rockville, Maryland

Gilbert J. Botvin, Ph.D.

Cornell University Medical College

New York, New York

Joseph V. Brady, Ph.D.

The Johns Hopkins University School of Medicine

Baltimore, Maryland

Theodore J. Cicero, Ph.D.

Washington University School of Medicine

St. Louis, Missouri

Sidney Cohen, M.D.

Los Angeles, California

Reese T. Jones, M.D.

Langley Porter Neuropsychlatric Institute

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

NIDA Research Monograph Series

Jerome Jaffe, M.D.

ACTING DIRECTOR, NIDA

Jock Durell, M.D.

ASSOCIATE DIRECTOR FOR SCIENCE. NIDA

EDITOR-IN-CHIEF

Eleanor W. Waldrop

MANAGING EDITOR

Parklawn Building, 5600 Fishers Lane, Rockville, Maryland 20857
Prevention Research:

Deterring Drug Abuse Among

Children and Adolescents
ACKNOWLEDGMENT

This monograph is based upon papers and discussion from the RAUS

review on prevention research which took place on April 5 and 6,

1984, at Rockville, Maryland. The review meeting was sponsored by

the Office of Science and the Division of Clinical Research,

National Institute on Drug Abuse.

COPYRIGHT STATUS

The National Institute on Drug Abuse has obtained permission from

the copyright holders to reproduce certain previously published

material as noted in the text. Further reproduction of this

material is prohibited without specific permission of the copyright

holders. 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.

Opinions expressed in this volume are those of the authors and do

not necessarily reflect the opinions or official policy of the

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

Department of Health and Human Services.

DHHS publication number (ADM)85-1334

Printed 1985

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
Foreword

In 1983 a Research Analysis and Utilization System (RAUS) review

entitled "Preventing Adolescent Drug Abuse: Intervention Strategies" (Research Monograph 47) considered a variety of prevention

approaches. As an outgrowth of that meeting, it was determined

that two closely-related approaches, social skills and social

inoculation, warranted more intensive review. These school-based

strategies, developed first in smoking prevention and later applied

to other substances, had been studied extensively by a number of

investigators funded by the National Institute on Drug Abuse (NIDA)

and other components

preliminary results.

"Prevention Research:

of the Public Health Service with encouraging

Deterring Drug Abuse Among Children and

Adolescents" was, therefore, selected as a subject for a comprehensive RAUS review in 1984. It focused on social skills and

social inoculation approaches and also 'included a contrasting

cognitive-developmental approach. The meeting was designed to

thoroughly review these promising smoking prevention strategies,

consider their appropriateness for transference to other substances, and clarify future research directions:

Charles Gruder served as the scientific moderator of the meeting.

Catherine Bell and Robert Battjes were the NIDA staff responsible

for organizing the meeting. Jacqueline Ludford, Chief, Research

Analysis Branch, Office of Science, is the RAUS coordinator for

NIDA.

Jerome H. Jaffe, M.D.

Acting Director

National Institute on Drug Abuse

Preface

On April 5-6, 1984, the National Institute on Drug Abuse (NIDA)

hosted a review meeting under the aegis of the Research Analysis and

Utilization System (RAUS) on "Prevention Research: Deterring Drug

Abuse Among Children and Adolescents." This meeting shared the

goals of all RAUS reviews, namely the evaluation of federally funded

research, dissemination of conclusions from the evaluation,

provision of feedback to NIDA planners, and identification of high

priority targets for future research.

This conference can perhaps best be understood in context--it

followed a 1983 RAUS conference which also reviewed adolescent drug

abuse prevention research (Preventing Adolescent Drug Abuse:

Intervention Strategies, NIDA Research Monograph 47). In the final

chapter of the monograph reporting on the 1983 review, Leukefeld and

Moskowitz noted: "In sum, research on preventive interventions is

in its infancy due to theoretical and methodological inadequacies"

(p. 253). With respect to the dissemination and implementation of

existing preventive interventions, they reported that, on the one

hand, conferees desired to begin implementing promising prevention

programs, but, on the other hand, they were reluctant to recommend

any particular program for dissemination.

It seems appropriate to take these conclusions as the starting point

for the present report on the 1984 RAUS review, which looked more

closely at selected promising prevention approaches. How far have

investigators come, i.e., are we closer to the ultimate goals of

implementation and dissemination? Do investigators and observers

still agree that the research base is inadequate and further research is required? Are research recommendations the same or have

they changed?

The chapters in this monograph provide a thorough review of research

data on the most promising preventive intervention approaches. This

information will go a long way toward answering our questions.

Moreover, this process has aided in the identification of new

directions for future research.

Charles L. Gruder, Ph.D.

Professor and Chairman

Department of Psychology

University of Illinois

at Chicago Circle

vii

Contents

Foreword

Jerome H. Jaffe. . . . . . . . . . . . . . . . . , . . . . v

Preface

Charles L. Gruder. . . . . . . . . . . . . . . . . . . . . vii

Overview of Drug Abuse Prevention Research

Catherine S. Bell and Robert J. Battjes. . . . . . . . . . 1

Personal and Social Skills Training: Cognitive-Behavioral

Approaches to Substance Abuse Prevention

Gilbert J. Botvin and Thomas A. Wills. . . . . . . . . . . 8

Social and Personal Skills Training Programs for Smoking

Prevention: Critique and Directions for Future Research

Russell E. Glasgow and Kevin D. Mc Caul. . . . . . . . . . 50

What We Know About the Social Influences Approach to

Smoking Prevention: Review and Recommendations

Brian R. Flay. . . . . . . . . . . . . . . . . . . . . . . 67

The Social Influences Approach to Smoking Prevention and

Progress Toward an Integrated Smoking Elimination

Strategy: A Critical Commentary

Harry A. Lando . . . . . . . . . . . . . . . . . . . . . . 113

A Cognitive Developmental Approach to Smoking Prevention

Kathleen Glynn, Howard Leventhal, and Robert Hirschman . . 130

The Cognitive Developmental Model and Other Alternatives

to the Social Skills Deficit Model of Smoking Onset

William 3. McCarthy. . . . . . . . . . . . . . . . . . . . 153

Methodological Issues in Research on Smoking Prevention

Anthony Biglan and Dennis V. Ary . . . . . . . . . . . . . 170

Priorities in Research in Smoking Prevention

Thomas D. Cook . . . . . . . . . . . . . . . . . . . . . . 196

Future Directions in Drug Abuse Prevention Research

Robert J. Battjes and Catherine S. Bell. . . . . . . . . . 221

Participants . . . . . . . . . . . . . . . . . . . . . . . . . 229

List of Monographs . . . . . . . . . . . . . . . . . . . . . . 230

ix

Overview of Drug Abuse

Prevention Research

Catherine S. Bell, M.S., and Robert J. Battjes, D.S.W.

Public concern over the issue of drug abuse among children and

adolescents has stimulated a major effort on the part of researchers

and clinicians to identify effective ways of deterring or delaying

onset of this behavior. Traditional health education approaches had

proven largely unsuccessful in reducing rates of drug abuse. Thus

new approaches were sought to address this problem. Encouraging

results have been reported from research studies based on psychosocial models of behavior. Originally applied to the prevention of

tobacco use, these interventions are currently being adapted to

other drug abuse behaviors (e.g., alcohol and marijuana use), and

preliminary findings are most promising.

OVERVIEW

Although the purpose of this monograph is to identify and delineate

the currently available research knowledge relevant to deterring

adolescent drug abuse in general and cigarette smoking in particular, it is appropriate first to provide the context within which

the chapters were developed.

In 1982 the National Institute on Drug Abuse (NIDA) established the

Prevention Research Branch in the Division of Clinical Research.

The mandate of this unit includes two areas of research: etiology

and preventive interventions. The former seeks to expand understanding of antecedent factors which inhibit or contribute to the

risk of drug abuse in later life. Etiological research findings are

intended to assist in the development or refinement of preventive

interventions. The second major area, preventive intervention

research, examines the efficacy of a wide variety of strategies to

deter or delay the onset of drug abuse behaviors. This research

largely focuses on youth; however, other groups at above average

risk for drug abuse are also included in the research mandate.

Etiological research has long been an integral part of NIDA's drug

abuse research program, whereas preventive intervention research has

emerged as a priority area only within the past few years.

1
In establishing the Prevention Research Branch, NIDA demonstrated

its commitment to expand the Institute's prevention program and

recognized the importance of a close linkage between research and

application. In order to stimulate investigator-initiated grant

applications in priority areas, the Branch has issued a number of

research grant announcements:

Drug Abuse Prevention Research Announcement

Family Therapy and Prevention Research Announcement

New Investigator Research Award in Prevention

Community Prevention Research in Alcohol and Drug Abuse

Prevention of Alcohol, Drug, and Mental Health (ADM)

Disorders at the Worksite

To insure that interventions designed to prevent tobacco use had

been thoroughly tested, that they were appropriate for transference

to other drugs of abuse, and to identify potential problems, provide

solutions, and direct future research, NIDA held a 2-day working

conference on April 5 and 6, 1984.

This meeting was part of NIDA's Research Analysis and Utilization

System (RAUS). RAUS reviews are designed to serve four functions:

Collect and systematically classify the findings of all

intramural and extramural research supported by NIDA;

Evaluate the findings in selected areas of particular

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

of scientific peers;

Disseminate findings to researchers in the field and to

administrators, planners instructors, and other interested

persons;

Provide a feedback mechanism to NIDA staff and planners so

that the administration and monitoring of the NIDA research

program reflect the very latest knowledge gleaned from

research in the field.

This monograph is a product of that conference. The participants

included representatives of three major psychosocial intervention

approaches: social skills, social inoculation, and cognitivedevelopmental. Discussants included social scientists with broad

behavioral and clinical experience in the related fields of smoking

cessation, stress management, and alcohol and drug abuse.

As a complement to this meeting, NIDA sponsored a conference

entitled "Etiology of Drug Abuse: Implications for Prevention" on

April 24 and 25, 1984. Research Monograph 56 reports the findings

of that conference (Jones and Battjes 1985).

SCIENTIFIC BACKGROUND

During the past 20 years, Americans have become increasingly aware

2
of and concerned about the level of drug involvement among youth.

At the end of the 1960s. the use of illicit drugs among teenagers

and young adults was recognized as a major epidemic. Large segments

of the nation's youth had begun to experiment with marijuana,

psychedelics, and psychoactive drugs such as phencyclidine (PCP).

Moreover, misuse and abuse of prescription drugs (e.g., tranquilizers and stimulants> was on the increase. By the mid-1970s.

illicit drug experimentation seem to have become synonymous with

other "rites of passage" into adulthood.

Although rates of drug use for most substances declined during the

late 1970s and early 198Os, drug use among adolescents and young

adults continues to be a significant problem. As measured by NIDA's

High School Senior Survey, in 1984, 19% of the respondents reported

having smoked cigarettes daily, 5% were drinking alcohol daily, and

39% had five or more drinks in a row at least once in the past 2

weeks. Approximately 25% of high school seniors reported current

use of marijuana. Moreover, 62%, or roughly two-thirds of the

respondents, had tried an illicit drug (Johnston et al. 1985).

Table 1 provides an overview of trends in 30-day prevalence of 16

types of drugs and table 2 provides annual prevalence.

EARLY PREVENTIVE INTERVENTIONS

Historically, drug abuse prevention programs were founded on the

theoretical assumption that children and adolescents used drugs

because they were ignorant of the consequences of such use. Failure

to recognize negative consequences resulted, according to this

theory, in neutral or even favorable attitudes regarding experimentation and/or regular use.

During the 196Os, drug education programs focused on providing

information. These programs frequently contained "fear arousal

messages" regarding the health and social consequences of such use.

Perhaps of more significance, youth reported that the messages

themselves lacked credibility.

By the 197Os, social scientists had begun to address interpersonal

and intrapersonal factors that influenced drug abuse behaviors among

children and adolescents (Goodstadt 1975). Correlational studies

found drug abuse was associated with attitudes, beliefs, and values,

as well as other personality factors such as feelings of selfesteem, self-reliance, and alienation. One prevention approach

which evolved from this research was affective education. Rather

than focusing on drug abuse behaviors, affective education focused

on the factors associated with use, attempting to eliminate the

reasons for using drugs by creating a school climate which was

supportive of students' social and emotional needs. These programs

frequently focused on training the students in effective decisionmaking skills. Specific techniques included: (1) values clarification; (2) analysis of consequences of behavioral choices; and

(3) identification of alternative behaviors consistent with one's

values and beliefs regarding drug abuse.

3
TABLE 1

Trends in Annual Prevalence of Sixteen Types of Drugs

NOTES. Level of significance of difference between the two most recent classes.

s = 05, ss = 01, sss = 001

VA indicates data not available

aData based on four questionnaire forms. N is four-fifths of N indicated.

bAdjusted for underreporting of anyl and butyl nitrites (see text).

cData based on a single questionnaire form. N is one-fifth of N indicated.

dAdjusted for underreporting of PCP (see text).

eOnly drug use which was not under a doctor’s orders is included here.

fAdjusted for overreporting of the non-prescription stimulants.

4
TABLE 2

Trends in Lifetime Prevalence of Sixteen Types of Drugs

NOTES. Level of significance of difference between the two most recent classes.

s = .05, ss = .01, sss = 001.

NA indicates data not available

aData based on four questionnaire forms. N is four-fifths of N indicated

bAdjusted for underreporting of amyl and butyl nitrites (see text).

cData based on a single questionnaire form. N is one-ftfth of N indicated.

dAdjusted for underreporting, of PCP (see text).

eOnly drug use which was not under a doctor’s orders is included here

fAdjusted for overreporting of the non-prescription stimulants.

5
Other prevention approaches gained prominence in the 1970s. These

programs focused on alternative activities to drug use. Some of

these programs involved youth in community projects to reduce

alienation, while others provided alternative opportunities for

recreation, socialization, and informal education.

The effectiveness of affective education and alternative approaches

to drug abuse has not as yet been demonstrated. While a significant

number of programs have been evaluated (see for example Berberian et

al. 1976; Goodstadt 1980; Schaps et al. 1981; Battjes 1985), the

vast majority of studies have suffered from methodological and

design flaws. It should be noted, however, that several of the

studies indicate little or no effects for selected prevention

approaches (Blum et al. 1978; Schaps et al. 1984).

PSYCHOSOCIAL PREVENTIVE INTERVENTION APPROACHES

Etiological research directed toward identifying and understanding

the antecedents and correlates of drug abuse behavior has contributed significantly to the development of a new generation of

preventive intervention approaches. The approaches that are

addressed in this monograph have been variously titled "saying no"

programs, peer resistance strategies, life skills training, and

social inoculation. To maintain a consistent thread among a

significant number of interventions reviewed in this monograph, the

term social skills training will be applied to those preventive

interventions that are broadly focused on enhancement of general

personal and social competence skills (e.g., Botvin, Wills, Schinke,

Pentz). Social inoculation training will be used for those programs

that focus on skills training to resist peer and other social

pressures (e.g., Johnson, Flay, Perry). The term cognitivedevelopmental training will be applied to those studies that focus

on the physiological reaction to smoking experimentation (e.g.,

Leventhal and Glynn).

The chapters that follow address issues that have arisen as a

consequence of current research experiences in the area of

psychosocial prevention approaches to drug abuse among school-age

children and adolescents. Botvin and Wills examine the results of

"broad-spectrum" social skills approaches. Flay provides an

analysis of the effectiveness of the social influences approach.

Glynn, Leventhal, and Hirschman discuss a model of the natural

history of cigarette smoking known as the cognitive-developmental

approach. Biglan examines the methodological issues related to

design and analysis of preventive intervention research strategies.

Each of these papers is followed by a discussion chapter developed

by Glasgow and McCaul, Lando, McCarthy, and Cook, respectively.

REFERENCES

Battjes, R.J. Prevention of adolescent drug abuse. Int J

Addictions, 20: 1113-1135, 1985.

Berberian, R.M.; Gross, C.; Lovejoy, J.; and Paparella, C. The

effectiveness of drug education programs: A critical review.

Health Educ Monogr, 4: 377-398, 1976.

6
Blum, R.H.; Garfield, E.F.; Johnstone, J.L.; and Magistad, J.G.

Drug education: Further results and recommendations. J Drug

Issues, 8: 379-426, 1978.

Goodstadt, M.S. Drug education--A turn on or a turn off? J Drug

Educ, 10:89-99, 1980.

Goodstadt, M.S. Impact and roles of drug information in drug

education. J Drug Educ, 5: 223-233, 1975.

Johnston, L.D.; O'Malley, P.M.; and Bachman, J.G. Use of Licit and

Illicit Drugs by America's High School Students: 1975-1984.

National Institute on Drug Abuse. DHHS Pub. No. (ADM) 85-1394.

Washington, D.C.: Supt. of Dots., U.S. Govt. Print. Off., 1985.

Jones, C.L., and Battjes, R.J., eds.

Implications for Prevention.

Etiology of Drug Abuse:

National Institute on Drug Abuse

Research Monograph 56. DHHS Pub. No. (ADM) 85-1335.

Washington, D.C.: Supt. of Docs., U.S. Govt. Print. Off., 1985.

Schaps, E.; Di Bartolo, R.; Moskowitz, J.; Palley, C.S.; and

Churgin, S. A review of 127 drug abuse prevention program

evaluations. J Drug Issues, 11: 17-43, 1981.

Schaps, E.; Moskowitz, J.; Malvin, J.; Schaeffer, G. The Napa Drug

Abuse Prevention Project: Research Findings. National

Institute on Drug Abuse Prevention Research Report. DHHS Pub.

No. (ADM) 84-1339. Washington, D.C.: Supt. of Docs., U.S.

Govt. Print. Off., 1984.

AUTHORS:

Catherine S. Bell, M.S.

Robert J. Battjes, D.S.W.

Division of Clinical Research

National Institute on Drug Abuse

5600 Fishers Lane

Rockville, Md. 20857

7
Personal and Social Skills

Training: Cognitive-Behavioral

Approaches to Substance Abuse

Prevention

Gilbert J. Botvin, Ph.D., and Thomas A. Wills, Ph.D.

This chapter reviews the empirical evidence on the efficacy of

substance abuse prevention efforts which teach generic personal

and social skills. This type of substance abuse prevention

strategy is part of a new generation of primary prevention

programs which have proven effective in reducing the initiation

of one or more forms of substance use (see Flay's chapter in this

volume for a review of studies testing other recently developed

substance abuse prevention strategies). The cognitive-behavioral

approaches reviewed in this chapter are based on the postulate

that the most effective approach to substance abuse prevention

utilizing school-based programs with general population groups is

to influence basic personal and social competence skills that

appear to be causal factors for several different types of

substance use and abuse.

This chapter begins with a review of the theoretical

considerations that led researchers to focus on teaching students

generic personal and social skills. Four current intervention

models and reported results on the effectiveness of these

approaches for preventing cigarette smoking and other forms of

substance use are described. Particular attention is given to

the process evaluations used in these studies, because one of the

major contributions of these researchers has been to develop and

adopt methods for assessing the personal and social competence

factors that are hypothesized to be the mediators of program

impact on substance use outcomes. The two final sections

summarize the accomplishments of these programs, discuss

methodological issues and potential limitations, and suggest some

topics that seem likely to be productive for further research in

this area:

BACKGROUND

Despite some awareness of the adverse consequences of substance

use, a significant number of teenagers begin using psychoactive

substances each year. Although for some persons use may be

discontinued after a brief period of experimentation, initiation

of tobacco, alcohol, or drug use may lead to patterns of use

8
which result in both psychological and physical dependence. In

view of the difficulty and cost of treating individuals who have

already developed substance abuse problems, the prospect of

developing effective substance abuse prevention strategies has

held a great deal of appeal over the years. While it seems

evident that effective treatment programs will continue to be

necessary, the development of effective prevention programs would

clearly represent a major advance in the battle that has been

waged against substance abuse for years.

Significant progress has been made in recent years which provides

preliminary support for the efficacy of several new substance

abuse prevention models. This new generation of programs differs

from traditional prevention approaches by incorporating a more

complete understanding of the basic causes of smoking, alcohol,

and drug use/abuse. Perhaps more importantly, these programs

have been subjected to carefully designed evaluation studies,

which provide evidence of their effectiveness.

Psychological Inoculation Studies

The most significant breakthrough concerning substance abuse

prevention first occurred in adolescent cigarette smoking. Evans

and his colleagues at the University of Houston (Evans 1976;

Evans et al. 1978) are credited with conducting the pioneering

work in the development and testing of a strategy for countering

social influences to smoke. In addition to using the social

learning theory (Bandura 1977), Evans' work was strongly

influenced by the persuasive communications theory of McGuire

(1964, 1968). As such, a central feature of the prevention

approach developed by Evans involved showing students films

depicting the kinds of social pressures to smoke that they would

likely encounter as they progressed through junior and senior

high school. The main purpose of this approach was to “inoculate”

students against such pressures. A further purpose of these

films was to demonstrate specific tactics for resisting these

pressures to smoke.

Other investigators have elaborated on this model. The work of

McAlister and his colleagues (McAlister et al. 1979, 1980; Perry

et al. 1980; Telch et al. 1982) and studies conducted in

Minnesota (Arkin et al. 1981; Hurd et al. 1980; Luepker et al. in

press; Murray et al. 1980), Canada (Flay et al. 1983), and

Southern California (Flay et al. in press; Johnson et al. 1981)

placed more emphasis on the actual training of students in how to

resist social pressure to smoke.

this type of intervention,

Results from studies testing

reviewed by Flay (this volume), show

that this approach appears to be effective for reducing the

incidence of new cigarette smoking in school-age populations.

Cognitive-Behavioral Programs

Other researchers in this area have examined

strategies having

prevention

a somewhat broader focus. Instead of utilizing

9
a substance abuse prevention strategy that teaches knowledge and

skills directly related to resisting offers of substance use

(i.e., strategies which are specific to substance use), these

strategies target general factors thought to be linked to

subsequent substance use by teaching broad-based personal and

social skills. Refusal skills and pressure resistance tactics

are also taught as part of this strategy. Thus, skills and

knowledge specific to substance abuse prevention are taught

within the framework of programs designed to enhance general

personal and social competence. This approach evolved from a

theoretical model which posits that- prevention can be achieved by

teaching persons to deal more effectively with general life

problems e.g., interpersonal relationships,

performance demands) and to co

social coping,

effectively with specific

temptations to use substances Wills and Shiffman, in press).

Although many of the techniques used in these programs were

initially developed for remediation of existing deficits,

recently these techniques have seen wide application in

competence enhancement with normal populations (Pentz and Tolan

submitted for publication).

THEORETICAL RATIONALE

Substance Use and Adolescent Development

The initiation of substance use is primarily an adolescent

phenomenon, occurring within the context of great physical and

psychological change. Adoption of one substance typically leads

to experimentation with other psychoactive substances, and

research with adolescents has shown a predictable sequence of

initiations: individuals begin with tobacco and alcohol,

progress later to marijuana, and may eventuslly go on to use other

drugs such as depressants or opiates (Hamburg et al. 1975; Kandel

1978). For this reason, tobacco (nicotine) is frequently viewed

as a "gateway" drug that greatly increases the probability of

regular and/or problematic use of other substances.

Psychological variables such as low self-esteem, depression, and

poor coping skills are notably significant for predicting

subsequent progression to problematic drug use (Kandel et al.

1978), and for this reason investigators have given extensive

consideration to the psychological factors that are implicated in

adolescent drug use.

During adolescence, individuals typically experiment with a wide

range of behaviors and lifestyle patterns as part of the natural

process of separating from parents, developing a sense of

autonomy and independence, and acquiring some of the skills

necessary for functioning effectively in the adult world.

Profound cognitive changes occur during the beginning of

adolescence which significantly alter the adolescent's view of

the world and the manner in which he/she thinks. Also, due to

what has been characterized as "adolescent egocentrism" (Elkind

1978), adolescents tend to have a heightened sense of selfconsciousness concerning their appearance, personal qualities,

10
and abilities. Furthermore, as students approach adolescence,

there appears to be a progressive decline in the impact of

parental influence and a corresponding increase in the impact of

influence from peer networks (Utech and Hoving 1969; Glynn 1981).

This has profound consequences for substance use. Whereas

parents and general adult networks tend to hold values that

discourage substance use (at least by teens), peer networks may

indirectly or directly encourage substance use (Wills and Vaughan

1984). Finally, in a process termed “adolescent invulnerability"

(Urberg and Robbins 1983), teens perceive that they are not

susceptible to the hazards presented by risk-taking and

health-compromising behaviors.

These and other developmental changes occurring during this

period increase adolescents’ risk of yielding to various direct

and indirect pressures to smoke, drink, or use drugs. The

combination of adolescent egocentrism and the increased reliance

on the peer group tend to promote substance use in some

individuals. At the same time, the cognitive developments

occurring prior to and during this period can serve to increase

vulnerability to substance use influences by undermining

knowledge related to the potential risk of using these

substances. For example, adolescents’ increased cognitive

sophistication may enable them to discover inconsistencies or

logical flaws in the arguments being advanced by adults

concerning the potential risks of substance use, or may enable

the adolescents to formulate their own counter-arguments and

construct rationalizations for ignoring these risks-particularly

if substance use is perceived as having social or personal

benefits. Thus, a recognition of the developmental tasks,

issues, changes, and pressures motivating adolescent behavior is

necessary to fully understand the etiology of substance

use/abuse.

Initiation and Early Stages of Substance Abuse

For most individuals, initial experimentation and the subsequent

development of regular patterns of use typically occur during the

pre-adolescent and adolescent period (Millman and Botvin 1983).

The initial use of most substances tends to occur in social

situations, with solitary use being relatively uncommon

(Friedman et al. in press).

Evidence from a variety of sources suggests that social,

attitudinal, and personality factors may all promote the

initiation of substance use (Blum and Richards 1979; Braucht et

al. 1973; Jessor 1976; Wechsler 1976). Social influences can

originate from substance use by family members (particularly

parents and older siblings) and friends, as well as from the

portrayal of substance we in the popular media as something that

is both acceptable and an important part of popularity, sex

appeal, sophistication, success, and good times. On an

individual level, a number of psychological factors have been

associated with substance use. For example, some of the

11
psychological characteristics that have been associated with

substance use/abuse include low self-esteem, a greater need for

social approval, high anxiety, low assertiveness, an external

locus of control, and an impatience to assume adult roles (Botvin

and McAlister 1981; Millman and Rotvin 1983).

Researchers have also found that substance users differ from

nonusers along several behavioral dimensions, suggesting a

difference with respect to value orientation. For example,

individuals who use drugs tend to get lower grades in school, are

less likely to participate in organized extracurricular

activities such as sports or clubs, and are more likely than

nonusers to engage in antisocial behaviors such as lying,

stealing, and cheating (Demone 1973; Jessor et al. 1972; Wechsler

and Thum 1973). Finally, evidence from a variety of sources

indicates that certain substances tend to be used together; for

example, adolescents who use opiates are also likely to drink

excessively and to smoke.

As Jessor (1982) has noted, the association between several types

of health-compromising behavior is perhaps one of the clearest

facts to have emerged from the past decade of research. The

significance of this observation is that a number of problem

behaviors appear to be caused by the same underlying factors.

For this reason, as well as for practical reasons, it has been

suggested that prevention programs should be developed which

target the underlying determinants of several theoretically and

empirically related problem behaviors (Botvin 1982; Swisher

1979). This postulate is the basis for the generic substance

abuse prevention programs, which aim at increasing students'

general personal and social competence, thereby affecting the

factors that underlie many types of substance use and

health-compromising behavior.

Theoretical Foundations

All of the newer psychosocial prevention strategies have common

theoretical roots based largely on social learning theory

(Bandura 1977) and problem behavior theory (Jessor and Jessor

1977). From this perspective, substance use is conceptualized as

a socially learned, purposive, and functional behavior which is

the result of the interplay of social-environmental and personal

factors. Substance use behavior, like other types of behavior,

is learned through a process of modeling and reinforcement which

is mediated by personal factors such as cognitions, attitudes,

and beliefs.

This modeling and reinforcement process can occur in several

ways. Some individuals may seek out other individuals who smoke,

drink, or use drugs-or may be motivated to engage in those

behaviors themselves-as a way of coping with expected failure or

as an alternative way of achieving some desired goal (i.e., some

adolescents who are not doing well academically may begin to use

drugs as an alternative means of achieving popularity, social

12
status, or self-esteem). Similarly, the use of tobacco, alcohol,

and certain other drugs may be used in an attempt to cope with

tension or anxiety, particularly social anxiety.

Other individuals may begin smoking, drinking, or using drugs

after repeatedly observing high status role models engaging in

these behaviors or as the result of persuasive appeals made by

advertisers or peers. Differential susceptibility to social

influence appears to be mediated by personality-with individuals

who have low self-esteem, low self-confidence, low autonomy, and

an external. locus of control being more likely to succumb to

these influences (Bandura 1969; Rotter 1972).

An argument, supporting broader-based prevention programs, is

that successful prevention strategies must not only provide

students with the skills necessary to resist social pressure to

use substances, but must also reduce potential motivations to

engage in tobacco, alcohol, or drug use. The former might be

accomplished by increasing students' refusal skills. The latter

might be accomplished by improving students' general personal and

social competence. A potential limitation of pressure-resistance

prevention models is that, although students might learn refusal

skills, they might have little motivation to apply these skills.

In fact, Friedman et al. (1983), in an empiric study of

students who began smoking in social situations, found that the

majority had knowingly entered the situation with the specific

intent of smoking. For these reasons, cognitive-behavioral

prevention models combine training in the use of refusal skills

with interventions intended both to improve general coping skills

and indirectly modify psychological factors related to substance

use.

Personal and Social Competence

The acquisition of adequate social skills appears to play an

important role in both psychological adjustment and psychosocial

development. Basic interpersonal skills are necessary for

confident, responsive, and mutually beneficial relationships, and

are perhaps among the most important skills that an individual

must learn. A lack of social competence may lead to rejection

and social isolation, which may in turn result in poor

psychological adjustment.

Individuals generally begin the acquisition of basic social

skills during childhood, and as they mature their social skills

generally increase. By the time individuals become adolescents,

many have acquired a repertoire of social skills such as

initiating and maintaining conversations, communicating

effectively, giving and receiving compliments, refusing

unreasonable requests, expressing feelings, etc. Social skills,

like other behaviors, are learned through a combination of

modeling and reinforcement and the development of these skills is

dependent upon having the opportunity to observe and practice

them. In addition to acquiring general social skills, it is

13
important that adolescents learn the kind of refusal skills that

will enable them to resist peer pressure to engage in behaviors

that they might otherwise choose to avoid.

Social skills may represent the largest collection of skills

which individuals need to develop in order to function

effectively as adults. However, it is also necessary to acquire

personal skills relating to effective and responsible decision

making, techniques for coping with stress and anxiety, and basic

principles of personal behavior change and self improvement.

Information and Knowledge

Available evidence indicates that teaching only about the extreme

negative consequences of substance abuse is of marginal value as

a prevention strategy. This does not mean that information and

howledge cannot play an important role in substance abuse

prevention. Certain types of knowledge about the use of tobacco,

alcohol, and drugs may be a useful component of substance abuse

prevention programs. For example, since adolescents typically

overestimate the prevalence of smoking and drinking, correcting

normative expectations of high substance use might help to reduce

the perceived social support for these behaviors.

Furthermore, information and knowledge included in prevention

programs should be selected with an understanding of cognitivedevelopmental factors. Since adolescents tend to have a

"present-time" orientation, the perceived short-term social

benefits of smoking, drinking, or drug taking may override

concerns for potential negative consequences (particularly more

distant long-term ones). Consequently, focusing on some of the

more immediate consequences of use, which may serve as social

liabilities (e.g., nicotine stains on teeth, bad breath, etc.),

might be a somewhat more meaningful deterrent than providing

information on long-term consequences.

Another important issue concerning information and knowledge is

its perceived credibility. Factual information about the

potential hazards of drug use, for example, may be ignored when

presented by teachers, but taken seriously when presented by peer

leaders. Moreover, the manner in which information is presented

can either enhance or detract from its credibility. For example,

information presented in an obviously one-sided and biased manner

is likely to be viewed with more suspicion than information that

is presented in a balanced and neutral manner.

INTERVENTION STRATEGIES AND EVALUATION RESULTS

Research on generic personal and social skills training

approaches to substance abuse prevention has been conducted

primarily by four research groups around the country during the

past few years. This includes research by Pentz (initially at

the University of Tennessee and more recently at the University

of Southern California), research by Schinke and his colleagues

14
(at the University of Washington), research by Wills (initially

at the American Health Foundation and more recently at Cornell

University), and research by Botvin (at Cornell University).

While each of these research groups developed substance abuse

prevention programs independently, there are many existing

commonalities in terms of both method and rationale. However, a

number of important differences exist within the approaches

utilized by these research groups. Moreover, in spite of the

fact that all of these intervention approaches have similar

roots, the case for each type of intervention strategy is argued

somewhat differently. A discussion of the work conducted by

these four research groups follows. Each section contains a

summary of the rationale used for that particular intervention

strategy, a general description of the intervention program, and

a summary of the results of evaluation studies conducted with

each intervention strategy.

Social Assertiveness Skills Training (Pentz)

The research being conducted by Pentz (1983, in press) tests a

prevention approach that is based on a social competence model of

substance use. Substance use in early adolescence, according to

this model, is a joint product of social influences (e.g.,

parental smoking, peer smoking) and poor social assertiveness

skills that are relevant for dealing with situations in which

individuals may experience social pressure to smoke, drink, or

use drugs. Pentz's model is derived from social learning theory

(Bandura 1977) and problem behavior theory (Jessor and Jessor

1977), and is based on several empirical findings. First, a

number of studies have found substantial correlations between

self, peer, and parental substance use. Second, other

researchers have reported associations between substance use and

such variables as high anxiety, depression, low self-esteem, and

low self-efficacy, suggesting that students who are prone to

substance use are relatively low in social competence. Third,

problem behaviors such as school failure, delinquency, and

aggression have been found to be correlated with substance use.

According to Pentz (1983), these findings suggest that students

with low social competence may be more susceptible to frequent

use of drugs or alcohol as a means of relieving social anxiety.

It is also hypothesized that students with low social competence

are less able to deal with various kinds of explicit social

pressure to smoke, drink, or use drugs. Adolescents who

experience a delay in the development of social competence are

viewed by Pentz as being prone to delinquency, aggressiveness,

academic or social withdrawal, and substance use.

The intervention approach developed by Pentz (1983) is,

therefore, based on the assumption that the initiation of

substance use can be deterred by increasing social competence and

self-efficacy. Social competence is essentially conceptualized as

assertiveness (i.e., the ability to disagree, to refuse, to make

15
requests, and to initiate conversations). Self-efficacy is

defined as "the conviction that one can successfully execute

behaviors necessary to produce desired outcomes" (Pentz, in

press). It is assumed that in early adolescence, intentions to

experiment with drugs may be offset by the development of

self-efficacy and prosocial skills.

The content and techniques incorporated into the prevention

program are derived from cognitive-behavior therapy and, more

specifically, from assertiveness skills training see Pentz

1983). The intervention program consists of seven 55-minute

sessions which are conducted by a trained teacher paired with a

program assistant, and facilitated by peers working in subgroups

of four in the classroom. Skills for dealing with several social

situations are demonstrated and taught through modeling,

rehearsal, and feedback to participating students. The social

situations covered include everyday situations with teachers,

parents, and peers.

One evaluation study of this approach has been conducted so far

(Pentz, in press). Evaluation measures included a set of

self-report items on recent use of cigarettes and alcohol, a

self-efficacy scale, and a role-play measure of social

competence. The smoking and drinking self-report items are scored

for frequency of use in the past month, amount of use and number

of days used in past month, and number of times abused in the

last 6 months. The self-efficacy scale is composed of 18 items

which tap perceived efficacy in both familiar and unfamiliar

interpersonal situations with teachers, parents, and peers. The

role-play measure of social competence involves presenting

students with 12 audiotaped social situations to which they must

respond. Responses are audiotaped and subsequently coded on a

5-point scale of social competence.

Also included was a teacher rating scale in which students were

rated by classroom teachers on a 10-point scale ranging from very

unassertive to very aggressive,

appropriate assertive behavior.

with the midpoint representing

Students were classified into

three groups (unassertive,

these teacher ratings.

assertive, aggressive) on the basis of

(e.g.,

Several items relevant to school behavior

semester grade point average, truancy, absence) were

derived from students' self-reports and from school records. In

addition, a 50-item inventory of attitudes towards substance use

was completed by students.

The evaluation study involved 1,193 students from 8 schools in

rural and suburban Tennessee, ranging from 6th through 9th

grades. Classrooms were randomly assigned to one of three

experimental conditions: full intervention (seven sessions of

instruction, modeling, and behavioral rehearsal), partial

intervention (two sessions of instruction only), or full control.

Half of the schools involved in the study were in rural areas and

half were in suburban areas.

16
Outcome results indicated several significant findings. The

intervention program increased social competence (as indexed by

the role-play measure), self-efficacy (as indexed by the

questionnaire measure), and grade point average. This effect was

more profound in the full intervention group, in comparison to

the instruction-only or control group. An interaction effect was

found between social skills training and initial behavioral

style-the intervention program had its greatest effect on those

students who were assertive or aggressive at baseline. These

students showed the largest increases in social competence and

improvements in student-teacher relationships, family

cohesiveness, and rebelliousness.

A similar interaction effect was also found for substance use.

Students in the full intervention group who had been assertive or

aggressive at baseline showed the greatest decrease in onset

rates for substance use, compared with either the

instruction-only or the control group. Results for social

competence measures were maintained over all follow up

measurements in this study; results for drug use measures

decreased somewhat over time, so that by the 6 month follow up

the full intervention and instruction-only groups showed similar

levels of drug use. Data presented by Pentz (in press) indicate

that the effect of the intervention occurred primarily for

alcohol use (beer, wine, and hard liquor); no effects were noted

for cigarette smoking.

Interactions with age of intervention suggested that the

intervention program had its greatest effect on self-efficacy,

social competence, and drug use for the 6th and 9th grade

students. It is noteworthy that these represent crucial

transition periods for adolescents. These intervention effects

were maintained through the 6 month follow up. Interactions with

rural versus suburban residence suggested that in rural areas

drug use was related primarily to social competence; whereas in

suburban areas, substance use was affected by a broader range of

variables, including drug use influences (e.g., higher peer and

parental drug use, more negative social attitudes).

In sum, social competence training, in interaction with grade

level and personality style (aggressive versus nonassertive),

produced increases in social competence and school grades, and

decreases in drug use. To a lesser extent, environmental

characteristics appeared to moderate program effects, so that

social competence training had a greater effect on drug use among

rural students compared with suburban students. The results also

indicated that the intervention program wae most effective for

drug abuse prevention when conducted just before periods of

crucial transition for adolescents (e.g., beginning of junior

high school or beginning of high school).

The results reported by Pentz show some potential benefits of

her intervention program as a substance abuse prevention

strategy, although these benefits appear to be modest. However,

17
it is puzzling that no effects were obtained for cigarette

smoking, in contrast to results from most other studies; possibly

this is a consequence of the population characteristics of

students in rural/suburban Tennessee, where the study was

conducted. Perhaps more informative was Pentz's analyses of the

etiological determinants of substance use (conducted with control

group data). The results of these analyses (which have not been

included here) generally appear to support her hypothesized

causal model of substance use, and also were consistent with the

theoretical rationale for the intervention program.

Cognitive-Behavioral Skills Training (Schinke)

Schinke and his colleagues at the University of Washington have

conducted a series of studies examining the extent to which a

cognitive-behavioral intervention program is capable of

preventing or reducing cigarette smoking among adolescents. The

intervention strategy developed and tested by Schinke and his

colleagues is derived from their extensive research in the area

of pregnancy prevention (Gilchrist and Schinke, in press; Schinke

1982; Schinke et al. 1980; Schinke and Gilchrist 1977). Schinke

and colleagues view cigarette smoking, like engaging in sexual

intercourse without the use of contraceptives, from both a

developmental and social learning theory perspective.

Adolescence is a time for acquiring adult skills, exploring

options, and taking risks. Instead of letting adolescents

flounder through the adolescent years, learning skills in a

chaotic, hit-or-miss fashion, it is argued that adolescents

should be deliberately and systematically taught the skills

necessary to enjoy happy, healthy, and prosperous lives (Schinke

and Gilchrist 1984). The cognitive-behavioral approach is

designed to enable adolescents to acquire both the personal and

social competence skills necessary for them to "handle current

problems, anticipate and prevent future ones, and advance their

mental health, social functioning, economic welfare, and physical

well-being" (Schinke and Gilchrist 1984).

Schinke's approach recognizes the fact that adolescents are

frequently influenced or pressured into participating in

peer-sanctioned behaviors such as smoking, drinking, and sexual

intercourse. Although adolescents may possess knowledge

concerning the health risks associated with engaging in these

activities, the perceived social benefits of engaging in these

behaviors may override this knowledge. Adolescents who have not

acquired appropriate cognitive and behavioral skills not only are

unable to make well-informed and well-reasoned decisions

concerning such situations, but also will be likely to lack the

ability to successfully implement a decision that goes against

group norms.

The general approach advocated by Schinke and his colleagues

involves the acquisition of decision-making and problem-solving

skills which might enable adolescents to more fully utilize the

18
information at their disposal and be better prepared to make

decisions involving health-compromising behaviors. In addition,

adolescents are taught interpersonal skills so that they can

communicate effectively and assertively.

This approach emphasizes the development of cognitive and

behavioral skills which are flexible and not situation-specific.

On a cognitive level, students are taught decision-making and

problem-solving techniques which will better prepare them to

avoid peer pressure situations without alienating friends.

Students are also taught specific self-instruction techniques

that are designed to provide them with a framework for guiding

themselves through high-risk situations. Finally, students are

taught basic interpersonal skills designed to enable them to

implement specific decisions or act in a way which is consistent

with what they want.

The main components of this intervention strategy include:

(1) providing accurate information which can be immediately

personalized; (2) teaching students how to handle a diverse range

of problem situations through a systematic stepwise problem

solving strategy, as well as techniques such as brainstorming

which can help individuals develop potential solutions; (3)

conveying self-instructional techniques designed to help

individuals exercise self-control over their behavior (i.e., the

verbal mediation of behavior through covert instruction); (4)

teaching adaptive coping strategies for relieving stress,

anxiety, and pressure involving both covert cognitive coping

skills and overt relaxation training techniques; and (5)

developing important verbal and nonverbal assertive skills.

Classes or small groups provide opportunities for modeling,

reinforcement, feedback, and the vicarious learning of important

personal and social skills.

Adult group leaders teach students systematic decision-making

procedures for handling difficult situations. Case examples from

personal experiences of students are used to master the various

steps of defining a problem clearly, generating possible

solutions, selecting one solution, and planning its

implementation. Students are also taught important assertive

communication skills through role plays designed to provide them

with practice in sticking to tough decisions, dealing with risky

situations and influential people, and using self-control. A

combination of modeling, feedback, reinforcement, and coaching is

utilized to teach these skills. Homework assignments are

employed to give students additional practice and to increase the

likelihood that these decision-making skills will be utilized in

various life situations.

To date, Schinke and his colleagues have completed three studies

applying this general prevention model to adolescent cigarette

smoking. The cognitive-behavioral intervention strategy used in

these studies was essentially the same as the one specified

above. However, it does not appear to have included the stress

19
management component.

The first of these studies (Schinke and Blythe 1981) was

conducted with 6th graders (N = 28) from two classes within the

same school. Students were randomly assigned to experimental and

control groups. All students were pre- and posttested by

questionnaire for smoking knowledge and three measures related to

problem solving and decision making (perspective taking,

means/end thinking, and anticipation of consequences). In

addition, students were videotaped in order to assess specific

interpersonal (assertive) skills in eight face-t-face

interactions involving saying "no" to offers of cigarettes,

extolling the wisdom of not smoking, and pointing out the hazards

of tobacco use. A 6-month follow up was conducted in which

enhanced self-reports of weekly and monthly cigarette smoking

were collected using the bogus pipeline technique; students also

completed questionnaires designed to measure their attitudes

toward nonsmoking, intentions to smoke in the future, and the

number of refusals to smoke when offered.

The cognitive-behavioral intervention program consisted of eight

60-minute sessions conducted in small groups. The program

provided students with: general health information concerning

the advantages and disadvantages of smoking; problem solving and

decision making skills; and cognitive-behavioral strategies for

resisting peer pressure to smoke. Students were also taught

self-instruction techniques to help them exercise control over

their own behavior and set and achieve specific goals

(particularly goals related to resisting peer pressure to smoke).

Finally, students were taught assertive communication skills

(e.g., maintaining eye contact, appropriate facial expressions,

hand gestures, loudness of voice, assertive statements). All of

these skills were taught using a combination of modeling, role

playing, feedback, and reinforcement.

The intervention program was conducted by graduate interns who

provided students with feedback, reinforcement, and coaching.

Additionally, students took turns in different roles and as

coaches. Extended practice in the form of behavioral homework

assignments was also part of the program (e.g., gathering

antismoking information, observing cigarette smoking in public

places, leaving situations where others were smoking, and asking

people not to smoke).

Two-tailed t-tests were used to compare the treatment and control

groups at the posttest in terms of gain scores for smoking

knowledge, problem solving and decision making, and videotaped

social interaction measures. Both groups were also compared by

t-test for the various follow-up measures. Results yielded

significant differences between the two groups, indicating that

the students in the treatment group had significantly greater

increases in smoking knowledge, problem solving and decision

making skills, and assertive skills (higher rates of eye contact,

greater use of "I" and "no," and more requests that peers not

20
smoke).

Six-month follow up data indicated significantly less cigarette

smoking for the prevention condition, both in terms of cigarettes

smoked in the past week and past month. In addition, the

students in the prevention condition had more positive attitudes

toward nonsmoking, fewer intentions to smoke, and more refusals

of cigarettes. Follow up smoking data were collected using the

“bogus-pipeline” procedure. Although not explicitly stated, it

appears that conventional self-report procedures were used to

collect pre- and posttest smoking data. No pre- or posttest data

are presented for any of the variables reported at the 6-month

follow up. However, the authors state that “between condition

analyses of pretest data on young peoples’ self reported

cigarette use and their reports of family members’ smoking were

nonsignificant" (p. 34).

A second study (Schinke and Gilchrist 1983) was conducted with

6th grade students (N = 56) from two schools who were randomly

assigned to four conditions of a Solomon (1949) four-group

research design: pretest and intervention, intervention only,

pretest only, and neither the pretest nor the intervention

program. All students were posttested after 2 months, and follow

up data were collected after 6 months. As in the previous study,

the intervention program consisted of eight l-hour sessions

conducted twice a week by two group leaders. The intervention

program was essentially the same as in the first study, involving

a combination of information, the acquisition of decision-making

and problem-solving skills, self-instruction and self-management

skills, and assertiveness skills training.

The intervention material was delivered through the use of

audiovisual aids, handouts, class discussion, modeling, behavior

rehearsal, and extended practice. With respect to the latter,

students participated in outside homework assignments in which

they were asked to gather additional information about cigarette

smoking, observe cigarette smoking in public places, leave places

where other individuals were smoking, refuse to smoke, ask peers

not to smoke, and proselytize the advantages of not smoking to

classmates and adults.

The same type of multiple assessment measures used in the

previous study (Schinke and Blythe 1981) were used in this study

to compare the various treatment and control groups. Data were

analyzed using analyses of covariance, with pretest scores being

used as covariates. Once again, at the posttest students

participating in the intervention program were found to be more

knowledgeable about smoking hazards, were more skilled in

decision making and problem solving, and their performance on

videotaped interactions indicated a greater degree of

assertiveness.

No data were presented concerning smoking behavior either at the

pre- or posttest. At the 6-month follow up, the students who

21
participated in the prevention program reported more instances of

refusing cigarettes and fewer intentions of ever smoking.

Enhanced self-report data indicated significantly less tobacco

use among the students participating in the prevention program.

In terms of the proportion of students smoking, 8% of the

students in the prevention program and 37.5% of the control

students reported smoking in the past month.

A third and larger study (Schinke and Gilchrist, in press)

examined the effectiveness of this type of prevention strategy

with 234 middle and lower middle class white students in 6th

grade. All students were pretested and randomly assigned

by classroom to the following conditions: cognitive-behavioral

skills building, attitude modification, and control. Group

leaders were pairs of social workers randomly assigned to each of

the two treatment conditions.

As in the previous studies, students in the prevention condition

participated in eight l-hour class sessions, which provided

training in the use of self-management skills, problem-solving

and decision-making skills, and interpersonal (assertive) skills.

To facilitate learning assertiveness skills, students watched

videotapes of peers who avoided smoking under difficult

circumstances. Students subsequently discussed the use of

specific skills and practiced them in role-play situations.

One interesting difference between this study and the previous

ones was that the students assigned to the attitude modification

condition were provided with the same health information about

cigarette smoking as the students participating in the

cognitive-behavioral program. In addition, the students in the

attitude modification condition learned the merits of nonsmoking

through oral quizzes and contests modeled after TV game shows,

participated in anti-smoking skits, and made public commitments

not to smoke.

Students were assessed on the same kind of mediating variables

included in the two previous studies. Saliva samples were

collected along with enhanced self-reports of smoking behavior.

Data were analyzed by means of analyses of covariance, with

pretest scores being used as covariates for the analysis of

posttest and follow up data. Results indicated that in the

skills training and attitude modification conditions, students

were more knowledgeable about smoking effects than the control

students. The skills training group scored better on problem

solving and decision-making skills than either group, and

performed better on all measures of assertive communication

skills. Cigarette smoking from posttest to 6-month follow up and

from 6-month follow up to 12-month follow up for the skills

building condition were significantly lower than for the attitude

modification condition and than for the control condition.

Comparison of saliva thiocyanate (SCN) level&indicated that the

three conditions did not differ over any measurement period.

22
In summary, the work by Schinke and his colleagues has

consistently demonstrated the effectiveness of an eight session

cognitive-behavioral approach to smoking prevention when

conducted with outside professionals. Moreover, this approach

has produced significant increases in several measures of

problem-solving and decision-making skills, smoking knowledge and

attitudes, several in vivo measures of interpersonal assertive

skills, and intentions to smoke in the future. Although these

studies have generally involved relatively small sample sizes,

they have nonetheless included random assignment of individuals

(in two studies) and classes (in one). However, lack of

sufficient detail in the research reports of these studies

concerning the measures used to assess cigarette smoking make

comparison with other prevention studies difficult.

Decision Skills Curriculum (Wills)

Wills (in press) has been conducting a program of research that

has not only tested the effectiveness of a substance abuse

prevention program, but has also examined the relationship among

stress, coping, and substance use in adolescents. While it is

recognized that substance use initiation is a multifactorial

process that involves availability of substances,

substance-related knowledge and attitudes, and social influences

from parents and peers (Bentler and Speckart 1979; Botvin and

McAlister 1981), a major focus of Wills’ research has been on the

psychosocial stress factors that may predispose adolescents to

begin using substances such as tobacco and alcohol. This focus

was suggested in part by a body of research, derived largely from

studies of adults (see Leventhal and Cleary 1980), suggesting

that smoking serves a direct stress-reduction function. Another

focus of Wills’ research has been on the measurement of coping

patterns relevant for substance use in early adolescence.

Epidemiological research (e.g., Kandel 1978 has suggested that

poor coping in several life domains (e.g., parental

relationships, school performance, coping with negative emotions)

is a common underlying factor in the predictive patterns observed

for many different types of substance use.

Wills has utilized several different measures of stress and

coping in both his etiologic and intervention research.

Questionnaires were used to assess subjective symptoms of stress

(e.g., tension, difficulty in relaxing), occurrence of recent

events (during the previous week) that could evoke stress, and

occurrence of major life events during the past year that could

objectively be classified as stressful. Measurement of coping

was based on a coping inventory (Bugen and Hawkins 1981) that

asked subjects to indicate their frequency of doing various

things when they had a problem at school or at home. Factorial

analyses of this generalized coping measure indicated major

dimensions termed decision-making (which reflected an active,

problem-solving approach to coping) and cognitive coping (which

represented a more cognitive or emotion-focused approach to

dealing with problems). Other coping factors reflected social

23

485-051 0 - 85 - 2
support from peers and from parents: involvement in entertaining

or diverting activities, physical exercise, and meditation or

prayer. Also used in this research were several relevant

psychological variables including health locus of control

(Wallston et al. 1978), assertiveness, and generalized

self-regard.

Multivariate analyses of data from several cohorts of inner-city

7th graders indicated that stress measured by all three methods

significantly increased the probability of involvement in

substance use (both smoking and alcohol), as did external locus

of control and low self-esteem. The use of both decision-making

and cognitive coping methods significantly decreased the

probability of substance use. General involvement in

entertainment activities and peer networks was positively

associated with substance use, whereas social support from

parents and other adults was negatively associated with substance

use. Because Wills found that these psychosocial variables were

significant correlates of substance use among adolescents, he

included them as process variables in his intervention research

to examine their role as mediators of the impact of his substance

abuse prevention program.

Based on a psychosocial model of substance abuse described

elsewhere (Wills and Shiffman, in press), a substance abuse

prevention program termed the Decision Skills Curriculum

(Spitzhoff et al. 1981) was developed. The intervention program

was designed to affect mediating variables relevant for

deterrence of smoking initiation (i.e., decision-making ability,

locus of control, knowledge about negative consequences of

smoking, and assertiveness skills).

The prevention curriculum consisted of eight modules, and was

taught in the first project year in consecutive sessions over a

2-week period. The curriculum was taught by project staff (two

health educators), while the regular classroom teachers observed

and assisted where necessary with exercises and activities. The

curriculum began with a values-clarification module which

included a values-clarification exercise focused on leisure

activities. The next two modules contained material on decisionmaking. First, decision making was introduced as a systematic

process for dealing with general problems of adolescence. Next,

the decision-making skills taught were applied to everyday

decisions and to substance-related decisions in role-play

exercises using prepared scenarios.

Following these modules were two on social influence, applying

this concept both to general influences (especially media

advertising about smoking) and to specific influences such as

peer pressure for substance use. In the first of these modules,

instruction was given on counteracting adverse social influences,

using both cognitive and direct-action approaches. Following

from the latter concept was a module on assertiveness, which

began by introducing the distinction between aggressive,

24
assertive, and passive behavior. This concept was then applied in

role-play exercises involving both general assertiveness

situations (e.g., being served in a department store) and

substance use situations (e.g.,

group setting).

being offered a cigarette in a

Two modules on stress management were also included which dealt

with both short- and long-term issues. The first module taught

an approach for dealing with stressful situations based on the

cognitive modification approach of Meichenbaum (1977). This

approach uses a four-step process of preparing for and coping

constructively with stressful situations such as test-taking or

new social encounters. The other module presented ways of

incorporating stress-management techniques into one’s lifestyle,

focusing on progressive muscle relaxation. Other activities such

as meditation and physical activity (e.g., running) were

discussed as positive ways of using leisure time and dealing with

periods of stress.

A final module on the health consequences of smoking provided

cognitive material on both short- and long-term physiological

effects of cigarette smoking. This module included a lecture

section, a biofeedback demonstration on the physiological effects

of nicotine (using pulse rate, blood pressure, and hand tremor),

and a discussion of the psychological and economic benefits of

nonsmoking.

In addition to the curriculum, a health screening examination was

conducted in the treatment schools by auxiliary medical

personnel. This examination was designed to increase general

health awareness and sense of personal responsibility for health.

The procedure included measurements of height and weight (with

computation of a relative weight index), body fat (measured by

the skinfold thickness of triceps), blood pressure, and

cardiovascular fitness (measured by the Harvard Step Test).

Students participated voluntarily in the examination and received

feedback on their relative health status through comparison with

normative data from national health statistics. The activity was

presented as a positive experience, wherein students could

receive individualized information about themselves.

The intervention program was conducted with the entire seventh

grade (N = 800) in three New York City junior high schools. Two

of the schools (School El and School E2) were assigned to the

experimental condition, receiving the Decision Skills Curriculum

and associated educational activities; the other school was

assigned to the control condition. Baseline data indicated that

the schools were closely matched on rates of regular smoking.

The intervention program consisting of eight sessions was first

implemented immediately after completion of the baseline survey

in Fall 1981. A follow up program, which was based on the

original curriculum and composed of six sessions, was implemented

with the same population during their 8th grade year. Evaluation

25
data were obtained by a questionnaire which was administered in

school classrooms by project staff at the beginning and end of

each school year. The questionnaire included measures of smoking

and alcohol use as well as the measures of stress, coping, and

locus of control discussed above. Self-report data for cigarette

smoking were collected using the bogus pipeline procedure.

Preliminary analyses of data on substance use and process

variables indicated that the overall effect for the intervention

was moderated by school differences. Thus, further analyses were

performed at the school level, contrasting each of the two

experimental schools with the control school. It is evident from

the data on smoking incidence that the intervention was effective

in school El. In this school, there was a 42% reduction in new

experimental smoking at the end of 7th grade (approximately four

months after the conclusion of the intervention and a 39%

reduction in regular experimental smoking at the beginning of the

8th grade (10 months after the conclusion of the intervention).

For school E2, however, there was no significant effect on

smoking, even though the identical intervention had been

implemented in both of the experimental schools. Data for

alcohol use (defined by the heavy drinking measure) were mixed,

showing a nonsignificant reduction in school El and an increase

in school E2.

Data on the process variables were consistent with the outcome

data on substance use. The process data were analyzed through

analysis of covariance, with the baseline measure as the

covariate. Data collected at the end of the 7th grade indicated

that in school El there were significant increases in

decision-making skills and internal health locus of control, and

significant decreases in stress and in substance use as a coping

strategy. Other changes for cognitive coping, social support, and

substance-related assertiveness were in the same direction but

were nonsignificant. Data collected at the beginning of the 8th

grade (10 months after the conclusion of the intervention)

indicated that changes in the coping patterns along the

dimensions of decision making, cognitive coping, and social

support, as well as for internal health locus of control, were

maintained over time in school E1. In contrast, no significant

desired changes were noted for school E2. Indeed, some changes

in a nondesirable direction (increased stress and tendency to use

substances as a coping strategy) were found for this school.

These data indicate that the intervention program was

differentially effective in the two experimental schools. In one

experimental school, it affected the process variables in the

predicted direction and produced a significant reduction in

smoking initiation, while it was not effective in the other

experimental school. Because no systematic data on school

atmosphere were collected, interpretation of these results is

somewhat speculative. However, anecdotal evidence obtained from

the project staff suggest the presence of several salient

characteristics which distinguished the two treatment schools

26
from one another, and may have accounted for the observed

differences in outcome results. These include the level of

support and cooperation by the principal, school discipline, and

the relationship between teachers and administrators.

The results of this study illustrate the necessity of having a

number of different schools in any given study. Results may be

markedly affected by the atmosphere of individual schools, which

can vary greatly even within an apparently homogenous population.

It is noteworthy that in Wills’ study the schools were matched on

rates of regular smoking at baseline so that differential results

cannot be attributed to differences in baseline smoking.

Life Skills Training (Botvin)

Research by Botvin and his colleagues has involved the

development and testing of a broad-spectrum prevention strategy

called Life Skills Training (LST). The main purpose of this

approach is to facilitate the development of generic life/coping

skills as well as skills and knowledge more specifically related

to resisting social influences to smoke, drink, or use drugs. A

central feature of the LBT program is the teaching of several

cognitive-behavioral skills found to be effective when used to

remediate psychological or behavioral deficits. However, within

the context of this program, all students are taught these skills

in order to enhance their ability to, for example, cope more

effectively with anxiety or to function more competently in

social situations.

Some of the general cognitive-behavioral techniques incorporated

into the LST Program include cognitive strategies for enhancing

self-esteem (e.g., goal setting, behavior change techniques,

increasing positive self statements); techniques for resisting

persuasive appeals (e.g., identifying persuasive appeals,

formulating counter-arguments); techniques for coping with

anxiety (e.g., relaxation training, mental rehearsal); verbal and

nonverbal communication skills; and a variety of social skills

(e.g., initiating social interactions, conversational skills,

heterosocial ("dating") skills, complimenting, verbal and

nonverbal assertive skills). These skills are taught using a

combination of instruction, modeling, rehearsal, feedback and

reinforcement, and extended practice through homework

assignments.

In addition to providing students with general life skills, this

prevention strategy also involves teaching students skills and

knowledge more specifically related to the problem of substance

abuse. For example, in addition to teaching students general

assertive skills (i.e., the use of “no” statements, requests, and

the assertive expression of rights), students are taught how to

use these skills to resist direct interpersonal pressure to

smoke. Thus, students are not only taught a wide range of

personal and social skills in order to improve their general

competence and reduce potential motivations for substance use,

27
but are also taught how to apply these skills in situations in

which they may experience social pressure to smoke, drink, or use

drugs.

The LST program is composed of three major components. The first

component (Substance-Specific Component) contains material

similar to that contained in many of the newer psychosocial

smoking prevention programs (e.g., Evans et al. 1978; Hurd et al.

1980; McAlister et al. 1979). Elements of this component

include: material describing the short- and lone-term

consequences of substance abuse; information about prevalence

rates among both adults and adolescents in order to correct

normative expectations; information and class exercises

demonstrating the immediate physiological effects of cigarette

smoking using biofeedback-type apparatus; material concerning

media pressures to smoke or drink; and techniques for resisting

direct peer pressure to smoke, drink, or take drugs.

The second component (Personal Skills Component) contains

material: concerning decision making that has been designed to

foster the development of critical thinking and responsible

decision-making; designed to provide students with techniques for

coping with anxiety (i.e., cognitive and behavioral self control

strategies); and designed to provide students with the basic

principles of personal behavior change and self improvement.

The third component (Social Skills Component) contains material

designed to improve general interpersonal skills. Elements of

this component include: material concerning effective

communications, general social skills (e.g., initiating social

interactions, conversational skills, complimenting); skills

related to male/female relationships among adolescents; and both

verbal and nonverbal assertive skills.

The initial pilot research with this psychosocial prevention

strategy (Botvin et al. 1980) tested its short-term effectiveness

for preventing the onset of cigarette smoking when implemented by

members of the project staff.

9th, and 10th graders (N = 281)

This study was conducted with 8th,

from two different schools in

suburban New York. Both schools were comparable with respect to

socioeconomic status (SES) and baseline smoking rates. Schools

were randomly assigned to experimental and control conditions.

One school participated in a 10 session prevention program (LST)

and the other served as a no-contact control group. All students

were pretested and posttested by questionnaire with respect to

self-reported smoking status, knowledge about cigarette smoking

(e.g., the immediate effects of cigarette smoking, smoking

prevalence among adults and adolescents), psychosocial knowledge,

locus of control, self-esteem, social anxiety, decision making

autonomy, and the need for group acceptance. Three months after

the first posttest, data were once again collected concerning

self-reported smoking status.

The results of this study indicated that significantly fewer

28
students in the experimental group (4%) began smoking (one or

more cigarettes per month) than in the control group (16%) at the

time of the initial posttest. The two groups were also compared

in terms of the hypothesized mediating variables mentioned above.

Both groups were compared by means of a two-way analysis of

variance (sex X treatment condition) conducted using change

scores. Significantly greater increases were found for the

treatment group with respect to smoking knowledge, and

significantly greater decreases were found with respect to need

for group acceptance and social anxiety (for males only). All of

these changes were in a direction consistent with nonsmoking.

Follow up data collected three months after the initial posttest

(Botvin and Eng 1980) indicated that there still were fewer

students in the experimental group beginning to smoke than in the

control group (6% vs. 18%). Overall, the LST prevention strategy

produced a 75% reduction in new cigarette smoking over the three

months between the pretest and posttest which decreased over the

three months between the posttest and the follow-up to a 67%

reduction. Although this pilot study was extremely encouraging,

interpretation of these results is limited by the fact that

conventional self-report data were used (i.e., self-report data

were not collected using the bogus pipeline procedure) leaving

open the possibility that these results may have been biased by

under-reporting.

The second study (Botvin and Eng 1982) with this approach

involved testing the efficacy of the LST prevention program when

implemented by older (11th and 12th grade peer leaders. The

program was tested on 7th graders (N = 426) from two public

junior high schools in suburban New York City. Schools were

randomly assigned to experimental and control conditions.

Furthermore, saliva samples were collected prior to

administration of the self-report questionnaire using the “bogus

pipeline” procedure to enhance the quality of the self-report

data (Evans et al. 1977) and to provide an objective measure of

smoking status (saliva thiocyanate). In addition to data on

smoking behavior, students were assessed in terms of their

smoking knowledge, advertising knowledge (i.e. knowledge

concerning how advertisers attempt to influence consumer

behavior), locus of control, self-esteem, social anxiety, and

decision-making autonomy.

Once again the results indicated that there were significantly

fewer new smokers in the experimental group (8%) than in the

control group (19%). These results were corroborated by the

results of the saliva thiocyanate (SCN) analysis, conducted on a

30% subsample. These analyses showed a significant increase in

SCN levels (indicating increased smoking) for the students in the

control group and no significant increase for the students in the

experimental group. The cognitive and personality variables were

analyzed by means of a one-way analysis of covariance, with

pretest scores being used as covariates. Significant differences

consistent with nonsmoking were found between the experimental

29
and control groups for smoking knowledge, psychosocial knowledge,

advertising knowledge, social anxiety, and decision-making

autonomy. Discriminant function analyses were computed to

determine the extent to which new smokers could be differentiated

from students who remained nonsmokers using the three knowledge

variables and two psychological variables for which significant

changes were evident. The results of the classification analysis

indicated that 73% of the students were correctly classified when

the monthly measure of smoking status was used as the criterion

variable and 86% of the cases were correctly classified when the

weekly measure of smoking status was used as the criterion

variable.

One year later these two groups of students were posttested again

and the two groups compared in terms of smoking status. Although

the experimental and control groups still differed with respect

to all new smoking (24% vs. 32%), this difference was no longer

significant. However, when more regular cigarette smoking (one

or more times per week) was examined, significant differences

were evident between the experimental group (11%) and the control

group (25%). This study demonstrated a 58% reduction in new

smoking at the initial posttest and a 56% reduction in regular

smoking at the one year follow up.

The results of this study were particularly encouraging for a

variety of reasons. First, the comparison of the treatment and

control groups with respect to both enhanced self-reports of

cigarette smoking and SCN levels indicated that the prevention

program was able to significantly reduce new cigarette smoking.

Second, the results of the one-year follow up indicated that the

initial reductions in new experimental smoking produced at the

end of the prevention program (without any additional

intervention activities) resulted in significant reductions in

regular smoking (using the weekly measure) at the time of the

one-year follow-up. Finally, both the finding that the

prevention program produced significant changes consistent with

non-smoking on five of the seven hypothesized mediating variables

at the time of the initial posttest, and the results of the

discriminant function analysis, provide support for the construct

validity of this type of prevention program.

The third study with this prevention approach (Botvin et al.

1983) was designed to provide a "real-world" test of this smoking

prevention strategy when implemented by regular teachers under

typical classrooms conditions. Additional objectives of this

study were to test the effects of two different program

scheduling formats and the extent to which booster sessions could

enhance program effects. Seven suburban New York schools (N =

902) were randomly assigned to one of three conditions: (1) LST

prevention program conducted once a week for 15 weeks (weekly

scheduling format); (2) LST program conducted several times a

week for about 5 weeks (intensive scheduling format); and (3) a

control condition. Two schools were assigned to each treatment

condition and three schools were assigned to the control group.

30
As in the previous study, saliva samples were collected using the

bogus pipeline procedure in order to enhance the quality

self-report data. All students were pretested and posttested by

questionnaire for self-reported smoking status and on several

hypothesized mediating variables, including smoking knowledge,

psychosocial knowledge, assertiveness, locus of control, social

anxiety, self-esteem, self-confidence, self-satisfaction, smoking

assertiveness (tendency to refuse offers to smoke cigarettes),

decision-making autonomy, and smoking attitudes.

Comparison of the combined experimental group and the control

group revealed significant differences in the proportion of new

smokers (6% vs. 13%). No significant differences between the two

scheduling formats were apparent at the initial posttest. The

impact of the prevention program on mediating variables was

determined using analyses of covariance, with pretest scores

being used as covariates. Significant treatment effects were

found for smoking knowledge, psychosocial knowledge, general

assertiveness, locus of control (for the intensive scheduling

format only), smoking assertiveness, decision-making autonomy,

and smoking attitudes (for the intensive format only). A sex by

treatment interaction was found for social anxiety, selfconfidence, and self-satisfaction. All of these effects were in

a direction hypothesized to be consistent with nonsmoking.

At the one-year follow up, comparison of the combined

experimental group indicated that the program resulted in

significantly fewer new smokers using the monthly recall measure

(15% vs. 22% the weekly measure (8% vs. 15%), and the daily

measure (6% vs. 11%). Results also indicated that the intensive

approach was more effective for all measures (monthly, weekly,

and daily) of smoking status. Finally, the results indicated

that providing students with additional “booster” sessions in the

eighth grade can help to maximize the effectiveness of the

prevention program. The booster program consisted of eight

sessions and was designed to reinforce the material covered in

the seventh grade program. The best nonbooster group had an

onset rate for regular smoking of 5% (compared to a 15% rate for

the controls), while the booster group had an onset rate of only

2%. Despite the relatively low number of schools per condition,

additional statistical analysis of the smoking data from this

study indicate the presence of strong treatment effects which are

independent of any unmeasured “school” effects (see Botvin et al.

1983). However, one limitation of this study is that since only

once school received the additional booster sessions, the booster

effects reported were confounded with school effects.

Therefore, based on the most inclusive measure of new smoking

(monthly smoking), the prevention program resulted in a 50%

reduction in new cigarette smoking at the end of the first year

(6.5% vs. 13%). Although both scheduling formats for

implementing the LST program produced essentially the same

results at the end of the first year differences emerged at the

one-year follow up. The intensive scheduling format resulted in

31
a 55% reduction in new cigarette smoking at the end of the second

year (10% vs. 22%), while the less frequent (weekly) scheduling

format was not significantly lower than the control group (19%

vs. 22%). For the students receiving additional booster sessions,

new regular smoking was reduced by 87% at the end of the second

year (2% vs. 15%). Once again, treatment effects were evident

for several of the hypothesized mediating variables at the

one-year follow up, including smoking knowledge, psychosocial

knowledge, locus of control, self-satisfaction, smoking

assertiveness (for the intensive format only) and smoking

attitudes (for the intensive format only).

Research is currently underway to test the impact of the LST

prevention strategy on alcohol and marijuana use. Since tobacco,

alcohol, and marijuana use not only appear to be promoted by the

same etiologic factors but also occur at roughly the same point

in the developmental sequence of substance use behavior, it was

hypothesized that this type of broad-spectrum prevention strategy

would also have an impact on alcohol and marijuana use. A

secondary goal was to test the relative effectiveness of this

type of prevention program when implemented by either older (10th

and 11th grade) peer leaders or by regular classroom teachers.

The study includes 1311 7th grade students from 10 suburban New

York junior high schools. The students in these schools are

predominantly from white middle-class families. Two schools were

randomly assigned to each of the following five conditions: (1)

teacher-led LST program, (2) peer-led LST program (3)

teacher-led LST program plus booster sessions, (4) peer-led

LST program plus booster sessions, and (5) control. The LST

prevention program was conducted in 20 sessions over a four month

period. The booster program consisted of eight sessions in the

eighth grade and five sesions in the ninth grade conducted over a

three to four week period each year.

Saliva samples were collected at both the pretest and posttest

followed by the administration of a questionnaire containing

several items on self-reported behavior, knowledge, and attitudes

concerning smoking, drinking, and marijuana use. Assertiveness,

locus of control, social anxiety, self-esteem, smoking

assertiveness, and decision making independence were also

assessed by questionnaire. Approximately four months after the

pretest, all students were posttested by questionnaire and saliva

samples were once again collected.

Results of the first year of this study (Botvin et al. 1984)

indicate that the prevention program had a significant impact on

tobacco, alcohol, and marijuana use at the posttest. The

students in the peer-led condition reported drinking

significantly less alcohol per occasion than either the students

in the control condition or the teacher-led condition. Perhaps

most dramatic was the impact of the prevention program on

marijuana use. Not only were there significantly fewer students

reporting marijuana use on both the monthly and the weekly recall

32
measures, but the magnitude of these differences was quite

substantial. Comparing the proportion of students reporting

marijuana use in the peer-led condition with the control

condition, the prevention program reduced marijuana use by 71%

(2% vs. 7%) using the monthly recall measure and by 83% (1% vs.

6%) using the weekly recall measure.

As was the case in the previous studies, significant changes were

also evident with respect to several hypothesized cognitive,

attitudinal, and personality mediating variables in a direction

consistent with non-substance use. Comparison of the peer-led

LST condition, teacher-led LST condition and the control

condition for the hypothesized mediating variables using analysis

of covariance revealed significant treatment effects for several

of these variables. For the peer-led condition, significant

treatment effects were found for smoking knowledge, drinking

knowledge, marijuana knowledge, smoking attitudes, drinking

attitudes, marijuana attitudes, locus of control, and smoking

assertiveness. Treatment effects were found for only three of

these variables in the teacher-led condition. These included

significant increases in both smoking knowledge and marijuana

knowledge and an unexpected increase in social anxiety.

Overall, the research conducted with the Life Skills Training

approach has indicated that it is an effective substance abuse

prevention strategy.

pilot) study using the Life Skills Training prevention strategy

Although the results of the very first

produced promising results, interpretation of these results was

seriously limited due to the reliance on conventional

self-reports of smoking status. However, subsequent studies with

this prevention strategy have all utilized enhanced self-report

data and in one case included saliva thiocyanate levels as an

additional dependent variable) and have all indicated that the

LST program is capable of producing initial reductions of 50% or

more in new cigarette smoking among junior high school students.

These initial reductions in relatively infrequent experimental

smoking have been found to result in reductions in regular

smoking of approximately the same magnitude one year later

without any addition&L intervention activities. Still, it is

evident that some erosion of the original effects of the

prevention program occurs over time, suggesting the need for

continued intervention. Furthermore, this type of prevention

program has been found to be effective when implemented by

members of the project staff, by older peer leaders, and by

classroom teachers. The results of one study suggest that

booster sessions may be able to facilitate the maintenance of

initial program effects and may even enhance them. In the most

recent study conducted, this type of prevention program has also

been found to have a significant impact on both drinking and

marijuana use.

Finally, the studies conducted thus far have indicated that this

prevention approach can produce significant changes consistent

33
with non-substance use on such hypothesized mediating variables

as knowledge and attitudes relating to smoking, alcohol, and

marijuana use; assertiveness; locus of control; social anxiety;

self-satisfaction; self-esteem; and decision-making autonomy.

All of these changes have been in a direction consistent with the

theory underlying this prevention model suggesting that substance

abuse may be prevented through a strategy which enhances the

development of generic personal and social life/coping skills as

well as teaches information and skills related more directly to

social influences to smoke, drink, or use drugs. However, many

of these measures provide only a relatively indirect assessment

of the extent to which the LST program increased life/coping

skills. Furthermore, there have been differences across studies

in the measures used to assess specific variables. Thus, it is

difficult to draw any firm conclusions about the construct

validity of this prevention model at this point.

GENERAL DISCUSSION

Four substance abuse prevention models and a total of nine

reported evaluation studies have been reviewed in this paper.

These models were selected for review because they represent

broader-based approaches to substance abuse prevention than

prototypic inoculation/pressure resistance approaches. These

four prevention models all have similar theoretical roots and

utilize intervention techniques derived largely from

cognitive-behavior therapy. Substance abuse prevention is

approached indirectly through interventions designed to enhance

generic personal and social skills, although the specific

application of these skills to resisting substance use pressure

is also included in most cases.

Despite these important similarities, differences exist

concerning the range of personal and/or social skills included in

these programs. All four prevention programs include components

dealing with assertiveness; three of the prevention approaches

include material dealing with both decision making/problem

solving and information related to substance use; two programs

include components dealing with anxiety/stress reduction; and one

program includes a component dealing with general social skills.

Differences also exist in characteristics of the intervention

program such as target age group, program length, frequency of

sessions, the primary provider, and whether or not booster

sessions are included. Four of the studies reviewed in this

paper were implemented with 7th graders; three were implemented

with 6th graders; one was implemented with 6th, 7th, 8th, and 9th

graders; and one was implemented with 8th, 9th, and 10th graders.

Program length ranged from as few as seven sessions to as many as

20 sessions. Some of these intervention programs were conducted

at a rate of one class session per week, while others were

conducted at a rate of two or more classes per week. All of the

studies conducted so far, with the exception of two (Botvin and

Eng 1982; Botvin et al. 1984), used adult primary providers. In

34
some cases these adults were teachers and in other cases they

were outside health professionals (i.e., project staff members,

graduate interns, social workers). The majority of the

intervention studies have not included booster sessions.

Finally, the evaluation studies conducted thus far have major

differences in terms of design, objectives, populations,

dependent measures, sample size, and length of follow up (see

table 3). Five of the nine studies reviewed simply tested the

effectiveness of the intervention program. However, the other

four studies were designed so that they could provide information

on issues relating to the content of the intervention program

(Pentz, in press; Schinke and Gilchrist, in press), scheduling

format (Botvin et al. 1983), the relative effectiveness of peers

versus teachers as primary providers (Botvin et al. 1984), and

the effectiveness of booster sessions (Botvin et el. 1983; Botvin

et al. 1984). Some of the studies reviewed were pilot studies

involving a small number of students from 1 or 2 schools, while

others were larger scale studies involving 800 to 1,000 students

from 7 to 10 schools.

Accomplishments

Differences such as those mentioned above make the task of

drawing conclusions about these prevention models somewhat

complicated. However, some things can be said concerning these

approaches as a whole. First, all of the evaluation studies have

produced evidence that these prevention models are capable of

having an impact on one or more substance use behaviors. The

most common behavioral outcome is in terms of the effect of this

generic type of prevention approach on cigarette smoking. In

fact, all of the evaluation studies reviewed, except one (Pentz,

in press), produced a significant treatment effect on cigarette

smoking. Two studies (Pentz, in press; Botvin et al. 1984) have

reported an impact on alcohol use and one study (Botvin et al.

1984) has reported an impact on marijuana use.

Second, the magnitude of the reported effects appears to be

relatively large. In general, these studies have demonstrated

that generic skills approaches to substance abuse prevention can

produce about a 50% reduction in the incidence of substance use

behavior. Two studies produced reductions in smoking initiation

of 75% to 80% (Botvin et al. 1980; Schinke and Gilchrist 1983),

and one study (Botvin et al. 1983) reported an 87% reduction in

the initiation of regular smoking for students who participated

in additional booster sessions. Overall, these effects are

comparable to or greater than those reported in the studies

evaluating the efficacy of the inoculation/refusal skills

approaches.

Third, a major distinguishing feature of the evaluation studies

reviewed in this chapter is that they have attempted to measure

the impact of broad-based intervention programs on presumed

mediating variables. All of these intervention approaches have

35
produced measurable effects on a spectrum of hypothesized

mediating variables. Although the impact on specific mediators

has not been completely uniform across studies (see Glasgow, this

volume), the observed effects have all occurred in the

hypothesized direction and in a manner consistent with behavioral

effects. This is clearly an important step toward understanding

why these programs are effective. However, much more research is

necessary in order to be able to confidently draw conclusions

about how and why these programs work.

Fourth, several of these studies have produced results indicating

that broader-based generic approaches may be more efficient since

they can have an impact on several related behavioral domains at

the same time. For example, Botvin et al. (1984) reported

significant effects on smoking, alcohol use, and marijuana use.

Pentz (in press) reported that her intervention program had a

positive effect on students' academic performance. Schinke and

his colleagues have found that an approach similar to the one

wed in preventing cigarette smoking was also effective as a

strategy for changing variables related to the prevention of

teenage pregnancy.

Fifth, these studies provide information concerning the

conditions under which this type of prevention approach can

be effective. These studies indicate that generic personal and

social skills substance abuse prevention programs can be

effective whether the primary providers are project staff, social

workers, graduate interns, peer leaders or classroom teachers.

These approaches have also been found to be effective with rural,

suburban, and urban students. One study suggests that a more

intensive programming format-involving frequent sessions over a

relatively short time span--may be more effective than spacing

sessions out over a somewhat longer time span, and that booster

sessions may help maintain and even enhance program effects.

Methodological Issues and Potential Limitations

Despite the emphasis on evaluation which has characterized both

the inoculation/refusal skills substance abuse prevention

approaches and the broader personal and social skills training

approaches discussed in this chapter, researchers working in this

area recognize the need to continue to strengthen the

methodological rigor of their studies. Interpretation of the

results of the studies reviewed in this chapter is limited by

some of the same methodological problems found in the evaluation

studies testing the effectiveness of the inoculation/refusal

skills approaches reviewed by Flay (this volume). However, as a

group, the studies conducted with more generic skills training

approaches have a number of important strengths.

One of the most important methodological issues relates to the

quality of self-report data and the collection of biological

samples (e.g., SCN). Concerns about the validity of self-report

data have been raised previously (e.g., Evans et al. 1977). The

36
extent to which the quality of outcome data are suspect obviously

limits the interpretability of individual evaluation studies.

All the studies reviewed in this chapter; except for the pilot

study conducted by Botvin and his colleagues (Botvin et al. 1980)

and the study conducted by Pentz (in press), have collected

biological samples and have utilized enhanced self-reports as the

primary dependent measure. One study (Botvin and Eng 1982)

included the analysis of SCN levels in addition to the analysis

of self-report data, and found evidence of program effects on

both measures. Thus, confidence can be reasonably high that the

data utilized in these studies are valid.

Another important methodological issue concerns both the method

of assignment and the unit of analysis. All of these studies have

used random assignment. However, the unit of assignment has

varied from schools to classes to individuals. The majority of

studies have used the school or classroom as the unit of

assignment while conducting analysis on the individual level,

confounding potential school or classroom differences with

treatment effects. To some extent, this type of threat to

internal validity has been mitigated in several of these studies

(Botvin et al. 1983; Botvin et al. 1984; Pentz, in press; Schinke

and Gilchrist; in press) by the assignment of two or more units

to each condition. Although researchers working in the area of

substance abuse prevention are cognizant of this problem, efforts

to solve it have generally been hampered by the need for a large

number of schools or classrooms,

Two other problems which can compromise internal validity and

hinder the interpretability of the results of these studies are

pretest nonequivalence of conditions and differential attrition.

These two issues have generally not been directly addressed in

the research reports of these studies. However, examination of

the data presented in the reports of these studies indicates that

pretest non-equivalence of experimental conditions has not

generally been a problem. The issue of attrition is somewhat

more complicated. While few of the reports of these studies

provide data on attrition, it is obvious that attrition has

occurred in virtually all of these studies. However, more

serious than the actual amount of attrition is the extent to

which there is differential attrition among experimental

conditions. Unreported attrition analysis recently conducted on

the Botvin et al. (1983) data indicated that although attrition

was more likely to occur among smokers; there was no evidence of

differential attrition across conditions. The results of similar

analyses for the other studies reviewed in this chapter are not

available, leaving open the question of whether or not

differential attrition compromised the internal validity of any

of these studies.

Notwithstanding the presence of some methodological shortcomings,

it is important to recognize that the research conducted with

generic personal and social. skills training approaches (as well

as the research conducted with the inoculation/refusal skills

37
approaches) has become progressively more rigorous. Pilot

studies have generally involved a small number of schools and

been less methodologically sophisticated. ‘Encouraged by initial

successes and cognizant of the shortcomings of earlier studies,

more recent studies have been larger and better designed. It is

also important to recognize that, despite the increased

methodological rigor of the most recent studies, the results

obtained are quite similar to the results obtained in the earlier

studies. This consistency of results across studies (particularly

with successive studies testing the same intervention model)

provides considerable cause for optimism.

Summary

A total of nine evaluation studies have been conducted with four

prevention models which focus on teaching generic personal and

social skills. All of these approaches have produced

demonstrable effects for one or more substance use behaviors, and

the magnitude of these effects generally appears to be large.

Although methodological problems may exist in some of these

studies, the magnitude of the effects obtained and their

consistency across studies provide strong support for the

efficacy of these approaches.

Finally, a major strength of the research conducted in this area

is that all of these studies have assessed the impact of the

prevention programs on presumed mediating variables, and have

been able to demonstrate effects on a number of these variables

consistent with the behavioral results. Thus, while these

studies collectively provide evidence for the effectiveness of

generic personal and social skills training substance abuse

prevention models, only preliminary data are available' concerning

how and why these programs work.

RECOMMENDATIONS FOR FUTURE RESEARCH

The results of research with these kind of generic personal and

social skills training approaches to substance abuse prevention

are extremely encouraging. However, a number of important issues

need to be examined further.

First, most of the research conducted thus far with this type of

prevention strategy has focused on cigarette smoking. Although

some studies more recently have examined the extent to which the

broader personal and social skills training approaches impact on

other substances, more research should be conducted to increase

our understanding of their effectiveness as alcohol and drug

abuse prevention strategies.

Second, future studies should continue to give high priority to

process analysis, assessing the impact of these prevention

programs on the specific skills, knowledge, attitudes, etc.

hypothesized to play a role in substance abuse prevention. For

example, if the prevention program includes a component designed

38
to teach students techniques for coping with anxiety, an effort

should be made to determine the extent to which these skills are

both learned and utilized. These efforts will provide additional

information concerning how and why these prevention programs

work; and will also enable investigators to refine the

theoretical models guiding their research;

Third, virtually all of the substance abuse prevention research

has been conducted with predominately white, middle-class

populations. Future research needs to be conducted to determine

the extent to which these programs are also applicable to those

low SES populations likely to be at high risk for becoming

substance abusers.

Fourth; future research should attempt to identify the “active

ingredients” of this type of prevention strategy in order to

determine whether or not the kinds of general coping skills

taught actually contribute significantly to program

effectiveness. One approach to this issue would be to conduct

studies which provide for the testing of the various components

of these programs both alone and in combination.

Fifth, future research should attempt to identify the factors

that can either positively or negatively affect program outcome.

This would involve examining issues such as the relative efficacy

of different types of primary providers; different methods of

training primary providers, and different program formats. In

addition, future studies should include measures of environmental

variables, such as community characteristics and school

atmosphere; and these variables should be related to program

outcome effects.

Sixth, these prevention strategies should be tested against other

substance abuse prevention models in order to determine their

relative efficacy and cost-effectiveness. The most obvious

example of this type of investigation would be one comparing the

type of generic personal and social skills prevention strategy

discussed in this chapter with the more focal type of prevention

strategy discussed by Flay in this volume.

Seventh, it will be necessary to learn more about how to insure

successful implementation of these kind of programs in the

absence of highly motivated researchers. It will be important to

determine the extent to which these kind of prevention programs

can be effectively implemented by school personnel or other

individuals in the community who would be likely to conduct these

programs on an ongoing basis. Research studies will also need to

to determine the kind of training and ongoing support necessary

to foster the successful implementation of these programs; as

well as the nature and type of curriculum materiels.

Finally, it will be necessary to conduct large-scale “clinical”

trials to determine the effectiveness of these prevention

strategies when implemented with a broad range of students.

39
Table 1

Intervention Components

Focus of Intervention

Components Pentz Schinke Wills Botvin

Assertiveness X X X X

General Social Skills X

Anxiety/Stress Reduction X X

Decision Making/Problem Solving X X X

Information Related to

Substance Use

X X X

40
Table 2

Intervention Characteristics

Study Grade

# of Frequency Primary

Sessions of Sessions Provider Boosters

Botvin et al. 1980 8, 9, 10 10 weekly staff no

Botvin and Eng 1982 7 12 weekly older peers no

Botvin et al. 1983 7 15 weekly, teachers yes

3 per week

Botvin et al. 1984 7 20 1-2 per week peer vs. teacher yes

Schinke and Blythe 1981 6 8 2 per week graduate interns no

Schinke and Gilchrist 1983 6 8 2 per week no

Schinke and Gilchrist, in press 6 8 2 per week social worker no

Pentz, in press 6, 7, 8, 9 7 weekly teacher & staff no

Wills, in press 7 8 4 per week staff yes
Table 3

Methodological Characteristics of Studies
Table 3

(continued)

Notes:

(1) self-report measures were used unless indicated otherwise

(2) the intensive scheduling format condition was divided into a booeter/non-booster condition during the second year of the study with one

school in each condition to provide e pilot test of the effectiveness of booster sessions

(3) 1 year follow-up data are currently being analyzed; et the conclusion of the study 2 and 3 year follow-up data will be available

(4) each of the two treatment conditions have been randomly assigned to booster/non-booster conditions

(5) the relative effectiveness of the two treatment conditions were also assessed in terms of their impact on rural and suburban populations

(6) saliva samples were collected only at the 6 month follow-up

(7) date were analyzed using adjusted proportions, with pretest responses being used as covariates
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AUTHORS

Gilbert J. Botvin, Ph.D.

Associate Professor and Director

Laboratory of Health Behavior Research

Cornell University Medical College

The New York Hospital/Cornell Medical Center

411 East 69th Street

New York, New York 10021

Thomas A. Wills, Ph.D.

Assistant Professor

Laboratory of Health Behavior Research

Cornell University Medical College

411 East 69th Street

New York, New York 10021

49
Social and Personal Skills Training

Programs for Smoking Prevention:

Critique and Directions for Future

Research

Russell E. Glasgow, Ph.D., and Kevin D. MC Caul, Ph.D.

The purpose of this paper is to react to the paper on social

skills training by Botvin and Wills (this volume), commenting on

both accomplishments and shortcomings of this line of research.

Before this can be done, it is first necessary to delineate the

critical or unique aspects of this approach to smoking

prevent ion. We will then discuss the advantages and disadvantages

of a broad-spectrum, general competence approach compared to more

narrowly focused prevention programs. Rather than discussing

social skills training--which is employed by virtually every

recent smoking prevention program--we will restrict our focus to

the broad based social skills training approaches discussed by

Botvin and Wills (this volume). What is unique about these

programs is not their emphasis on social skills among adolescents,

but their methods for enhancing social competence. Although the

two major research groups in this field (based at Cornell and the

University of Washington) use the term “Life Skills Training” to

describe their work, we prefer the broader and more generic term

social and personal skills training.

After discussing the potential pros and cons of a broad-spectrum

social and personal skills training approach, we will turn to a

methodological/empirical critique of the current literature on

this topic. Two basic questions will be examined: Do such

programs work?; How do such programs work? Finally, we will

summarize the current status of social and personal skills

training approaches and provide a number of recommendations for

future research in this area.

Distinguishing Features of the Social and Personal Skills Approach

From a theoretical perspective, one of the major assumptions

behind the social and personal skills training (SPST) approach is

that of a syndrome of adolescent problem behaviors including

smoking, the use of other drugs, and other deviant behaviors such

as truancy and early sexual behavior (Botvin and Wills, this

volume; Jessor 1982). Smoking is viewed as one of a class of

functionally equivalent behaviors through which adolescents

express themselves, cope with anxiety, and deal with the

50
transition from childhood to adulthood. Furthermore, it is

postulated that the same cluster of relatively stable underlying

cognitive and personality variables (e.g., low self-esteem, high

anxiety levels, poor decision making skills) predisposes

adolescents toward the use of alcohol and other drugs and other

problem behaviors (Botvin et al. in press; Jessor 1982). In

fairness to the proponents of this model, it should be stressed

that this is not a naive personality trait theory approach.

Advocates of the SPST approach do consider and address social and

environmental factors; they operate from a person-environment

interactionist perspective. Still, what distinguishes the SPST

approach from other current prevention approaches is a special

emphasis on underlying individual differences.

It follows from this theoretical perspective that two

distinguishing features of SPST intervention programs are (1) the

utilization of therapeutic strategies to modify this underlying

core of intrapersonal cognitive and personality factors and (2) a

focus on general life skills thought to determine the use of

various substances (e.g., alcohol, marijuana) and the

manifestation of other behaviors such as precocious sexual

activity, delinquency and poor performance in school. Figure 1

summarizes the theoretical and treatment components involved in

the SPST approach. The left column of this figure lists the major

SPST intervention components employed, the center column lists

presumed mediating variables and the right column lists behaviors

making up the syndrome of problem behaviors.

Potential Advantages and Disadvantages to SPST

The complexity and broad-spectrum nature of the SPST approach is

the source of both its advantages and disadvantages. In terms of

conceptual advantages, the inclusion of personality factors in the

SPST model and the resulting Person x Situation perspective may

increase the chances of modifying the most important factor or

factors influencing smoking for a given individual. If we accept

the premise that different individuals smoke for different reasons

(Glasgow and Bernstein 1981; Pechacek 1979), it seems logical that

an approach which addresses a variety of factors will be more

likely to address critical factors for a larger percentage of

adolescents than will a more circumscribed approach.

A second potential advantage is that SPST may be particularly

effective with adolescents who are most predisposed toward

substance abuse. More narrowly focused social inoculation

interventions may be ineffective in providing adolescents with

sufficient skills for resisting social pressures to smoke if they

are not at least moderately socially competent to begin with.

With its more intensive focus on general skills and competencies,

SPST may provide the necessary preconditions for training in

specific refusal skills to be effective.

The above arguments suggest that the SPST approach might produce

greater reductions in smoking rates than social inoculation

51
SPST Components

Goal Setting and

Self-Management

Strategies

Homework Assignments

General Assertiveness

and Communication

Skills Training

Anxiety Reduction

Procedures

Decision Making/

Problem Solving

Self-Instruction or

Self-Statement

Procedures

Smoking Specific

Social Skills Training

Mediating Cognitive

and

Personality Variables

Self-Esteem

Syndrome of

Adolescent

Problem Behaviors

Cigarette Smoking

Locus of Control

Marijuana Use

Assertiveness

Social Anxiety

Alcohol Consumption

Influencibility

Need for Approval

Impulsivity

Precocious Sexual

Activity

Delinquency

FIGURE 1

Intervention Components, Hypothesized Mediating Variables,

and Adolescent Problem Behaviors Discussed in SPST Approaches

approaches. A more compelling advantage of SPST programs is that

they may lead to superior generalization and maintenance of

treatment effects. If one is successful in altering stable

characteristics such as self-esteem, sense of personal control,

and decision making ability, such changes should produce changes

in a number of aspects of one’s life in addition to smoking

behavior. Over the course of the adolescent years, one is exposed

to a variety of problem situations, challenges and difficult

decisions. Changed ways of viewing the world would be expected to

result in improvements in areas such as school performance and

interactions with peers and adults. One particularly interesting

generalization issue is whether subjects undergoing SPST are more

likely to change their peer group than are subjects in other

prevent ion programs. If subjects undergoing SPST experience

significant cognitive and personality changes, it seems that they

would also be likely to change the friends that they associate

with most closely.

52
A final potential advantage is that if the same factors underlie

the use of various substances, then it should only be necessary to

develop a single substance abuse prevention program, instead of a

different program for each substance. It is likely that school

administrators will be much more interested in offering one

substance abuse program with broad effects than in having to

support and find time for cigarette smoking prevention programs in

addition to drug and alcohol abuse prevention programs.

Unfortunately, the complexity of the SPST approach could lead to

problems that outweigh the potential advantages discussed above.

It may be, for example, that adolescents will feel overwhelmed

with the range of issues being discussed or the number of life

changes being advocated. A related point is that if one is

attempting to teach several different life skills, there may not

be enough time to do a thorough job in any one area and the end

result may be a superficial introduction to many different issues

rather than indepth work in any particular area. The adult

smoking cessation literature is replete with studies in which

simpler treatment programs resulted in better outcomes than more

complex programs (Lando 1981; Danaher 1977). Our own research

group has found similar results and has identified at least one

reason for this somewhat counter-intuitive finding. We found that

individuals receiving complex multicomponent smoking cessation

programs were less likely to adhere to treatment recommendations

(Glasgow et al. 1981). Of course this finding should not be

surprising given the well-established inverse relationship between

treatment complexity and adherence found in the literature on

compliance to medical regimens (Haynes 1979). The implication of

these findings for SPST is that adolescents receiving a complex

intervention such as SPST may not follow through on many of the

homework assignments or lifestyle changes recommended.

A conceptual problem concerning SPST is that at present we may not

know enough about underlying personality determinants of smoking

or about the best ways of altering such factors. When discussing

individual differences in their recent review of psychosocial

influences on the decision to smoke, Evans and Raines (1982)

commented that the identification of personality traits underlying

smoking was "... an elusive goal” and on “the patchwork quality of

existing knowledge” in this area. They echoed Williams' (1971)

earlier conolusion that “both the empirical results of previous

studies and discussions of the state-of-the-art of research into

personality correlates suggest that personality will not provide

the most fruitful approach to understanding why children do or do

not take up cigarette smoking" (p. 112). Even individuals

identified with the SPST approach have questioned the adequacy of

this knowledge base. In their book on Life Skills Counseling,

Schinke and Gilchrist (1984) state:

Numerous researchers have tried to distill a

consistent psychosocial profile for identifying

adolescents most likely to become substance users.

53
No consensus, however, has emerged. There appears

to be no simple pattern of factors that explains or

predicts adolescent drug use (p. 71).

Of course, there are others (e.g., Jessor 1982) who have reached

different conclusions on this issue. Without going into a lengthy

discussion of the prediction literature, we’d just like to raise

the question of whether or not the type of personality and

cognitive variables stressed by the SPST approach have been

consistently and strongly related to adolescent smoking behavior.

Even if there was consensus about the important intrapersonal

variables underlying smoking, it is not at all clear that we know

how to effectively modify such factors. As Jessor (1982) notes:

In explanatory research, it is possible, for

example, to demonstrate that adolescent involvement

in marijuana use varies with exposure to peer group

norms that support such drug use. Although

establishment of that connection certainly helps us

to understand some of the variation in marijuana

use, it does not help us to know how to change

those peer group norms (p. 448).

There is evidence that attempts to enhance social skills

among adolescents have been relatively successful (Pentz and Tolan

1984). However, it is a far more ambitious task to attempt to

modify factors such as self-esteem and feelings of personal

autonomy. Many individuals have spent years in therapy attempting

to accomplish such goals. In addition to issues concerning the

psychometric adequacy of measures of such concepts, there is not

much research which compares different approaches for modifying

such factors.

A final disadvantage of the SPST approach is that it is costly and

time consuming. Intervention contact time in reported studies has

varied from 7-20 hour long sessions, which is about twice the

length of many social inoculation prevention programs. In terms

of dissemination issues, it may be more difficult, even with a

detailed and well developed training manual, to train group

leaders in this approach than it is for more focal prevention

programs. In support of this point, the paper by Botvin et

al. (in press) speculates that poor implementation may have been

responsible for the lack of effect of their teacher led

intervent ion. For additional training and class time to be

justified, one would like to see demonstrations of the superiority

of the SPST approach.

Before moving on to a discussion of the empirical status of the

SPST approach, it should be noted that developers of SPST programs

have attempted to guard against some of the disadvantages

discussed above by providing information, role playing and

feedback specific to smoking related situations. Thus, what we

are often faced with in interpreting SPST studies is not a “pure”

54
general life skills training, but SPST supplemented by more focal

smoking specific exercises and information. It is plausible that

any effects of this program can be attributed to these specific

techniques and not to training in general social and personal

skills.

Methodological/Empirical Issues- in Evaluating SPST

Table 1 summarizes the questions we will examine concerning the

empirical status of the SPST approach. We will not address issues

such as biochemical validation of smoking status, methods of

assigning subjects to conditions, units of analysis in smoking

prevention programs, or effects of attrition on results. While

these issues are certainly relevant to the SPST area, they are

already dealt with at length in Biglan and Ary’s chapter (this

volume). We will ask two sets of questions, one concerning the

effectiveness of SPST and the second concerning how and why these

programs may work. By way of overview, there are far more answers

to the first set of questions than to the second.

The first question asks whether SPST produces results superior to

no treatment or standard school health education control

conditions. The answer to this question is yes. Botvin and

colleagues have conducted four large scale studies, all of which

found significantly lower smoking rates in SPST conditions. Both

Schinke and colleagues (Schinke and Blythe 1982; Schinke and

Gilchrist 1983) and Pentz (1983) have reported similar results.

While each of these studies can be criticized for various

methodological problems, the consistency of effects across studies

is impressive (see Botvin and Wills this volume). Unfortunately

the answer to the second question, concerning the relative

efficacy of SPST compared to other smoking prevention programs, is

that we simply don’t know. No study has investigated this

question.

The third question, concerning the magnitude of effects produced

by SPST, can be viewed in several ways. One way to evaluate the

meaningfulness of SPST program effects is to compute the percent

reduction in smoking initiation rates for experimental conditions

relative to control conditions, as Botvin has done. This approach

produces impressive results: from 50-87% reductions in smoking

rates. An alternative method is to examine the differences in the

percentages of adolescents who smoke in experimental versus

control conditions. This type of analysis, calculated on the same

set of studies, reveals reductions ranging from 3 to 14%--a less

impressive figure. We feel that the second procedure is more

informative. There are important differences between reducing

smoking initiation rates from 20% to 10% versus from 2% to 1%, but

this distinction is lost using the first procedure as both sets of

figures would indicate a 50% reduction. A third way of evaluating

the magnitude of effects produced by SPST is to compare

experimental-control condition differences reported in SPST

studies to those found in studies of other prevention approaches.

Comparison with results typically reported by the Houston,

55

485-051 0 - 85 - 3
TABLE 1

Methodological/Empirical Criteria for Evaluating

Social and Personal Skills Training

I. How Well Do SPST Programs Work?

A. Does SPST reduce smoking relative to:

1. No treatment or standard health education classes?

2. Alternative psychosocial smoking prevention programs?

B. How large are the effects produced by SPST?

C. Does SPST result in better generalization of effects to:

1. Use of other substances?

2. Other areas of life (e.g., school performance,

difficulties with the law)?

D. Is SPST cost-effective relative to other approaches?

II. How Do SPST Programs Work?

A. Does SPST produce changes in variables hypothesized to mediate

outcome and are changes in these variables related to smoking

status?

B. What are the critical components of the SPST package?

C. What is known about conditions or factors moderating the

effects of SPST?

Minnesota, Oregon and University of Southern California groups

reveals that the SPST approach generally produces results

comparable to and sometimes larger than these other programs.

Once a sufficient number of studies have been conducted, this type

of comparison could be improved by formal computation of effect

sizes for use in meta-analysis studies (e.g., Cook, this volume;

Strube and Hartman 1983).

Before moving on to the next question, the effects reported by

56
Schinke and colleagues (Schinke and Blythe 1982; Schinke and

Gilchrist 1983) are worthy of special comment. They have obtained

significant differences between conditions with sample sizes of

14-28 subjects per condition; in this area, such results are truly

amazing. Although their reports do not specify details regarding

rates of cigarette smoking. For example,

Schinke and Gilchrist (1983) reported that 8% of the 7th grade

subjects in their experimental condition reported smoking,

Effects of this magnitude

are certainly worthy of further investigation.

findings suggest that the program had a sizable effect with a

group of adolescents strongly predisposed toward cigarette

smoking.

Question I.C. in table 1 concerns generalization of treatment

effects and relates to one of the potential advantages of SPST

SPST investigators have recently begun to

investigate whether or not treatment effects generalize to the use

It does appear that the SPST approach

produces reduced rates of alcohol and marijuana usage, as well as

1983). However, it is not clear whether such results should truly

did receive specific information and social skills training

pertaining to those other substances.

research on the issue of generalization of SPST effects to

adolescent “problem behaviors" besides substance use. Pentz

(1983) has reported potentially important findings regarding

improvements in students’ grade point averages following

early sexual behavior or delinquency have apparently not yet been

investigated.

approaches, there is no direct information available on the

relative cost-effectiveness of SPST programs.

a central question for future research, as well as for potential

should be the trade off between the additional time and

expense to offer the somewhat more lengthy and comprehensive SPST

potentially greater treatment generalization

associated with this approach.

How and When Does SPST Work?

The second set of questions in table 1 will be discussed in

somewhat greater detail because the answers to these questions

have great significance for our understanding of the SPST

approach. The first question, concerning hypothesized mediating

variables, can be broken down into two separate questions. The

first concerns whether SPST treatments produce changes in the

variables hypothesized to mediate treatment outcome (see figure

1). All of the investigators whose work is discussed by Botvin

and Wills (this volume) have collected data on potential

5 7
mediators. Their conscientiousness in this regard stands in

contrast to the myriad of prevention studies which provide no

information on why an intervention may--or may not--produce its

intended effects. In particular, Botvin and colleagues have

collected a number of similar process measures in several

different studies.

Table 2 summarizes findings concerning comparisons of SPST to

control conditions on potential mediating variables in four

different studies conducted by Botvin’s group (Botvin et al. 1980,

1983, in press; Botvin and Eng 1982). It is important to remember

that all four of these studies found SPST reduces smoking rates

relative to controls. Table 2, which illustrates the presence or

absence of significant improvement relative to controls on the

various measures, can best be summarized by saying differences

were observed on only some of the measures only some of the time.

As can be seen, there is no consistency across the four studies

for the first five variables listed. Some of this variability

could possibly be explained by population differences, but the

last three studies were all conducted with predominantly suburban

white middle class 7th grade subjects. Indeed, the only

consistent findings to emerge are for locus of control and for

smoking-related knowledge. Significant improvements were never

found on locus of control, which is one of the more central

mediating variables discussed by SPST proponents. On the other

hand, smoking-related knowledge was consistently enhanced more in

SPST subjects than controls. This pattern of results certainly

raises questions about how SPST achieves its effects. Presumably

it is not only through knowledge changes since scores of smoking

prevention studies have demonstrated that increased knowledge does

not result in behavior change (see reviews by Evans and Raines

1982; Thompson 1978).

To understand how SPST works, it is not enough to simply ask if

changes are observed on various mediating variables. One must

also ask if changes in these variables are related to changes in

smoking status. It should be emphasized that even when change is

observed on a mediating variable as well as on an outcome measure,

it does not imply that this variable caused the change in the

outcome measure. The interested reader is referred to Cook and

Campbell (1979), Judd and Kenny (1981) and McCaul and Glasgow (in

press) for more detailed discussions of these issues. The good

news is that the data to answer these questions have already been

collected. What remains is for the appropriate analyses to be

conducted.

The next question in table 1 asks about the critical components of

the SPST package. We know very little about the relationship of

specific components of the SPST package, depicted on the left side

of figure 1, to either the supposed mediating variables in the

center column or to the outcome variables on the right hand side

of the figure. One way of answering this question is through

constructive or parametric research designs which systematically

vary the presence or level of intervention procedures felt to be

58
TABLE 2

Significant Improvement on Hypothesized Mediating

Variables Relative to Controls in SPST Studies

Studies

Mediating

Variables

Social Anxiety

Botvin et al. Botvin & Eng Botvin et al. Botvin et al.

(1980)1(1982) (1983) (in press)

Interaction Yes Interaction N o

with sex with Sex

Self-Esteem (Self-image) No No No Interaction

with Sex

Influencibility No

Assertiveness NR2

Smoking Attitudes NR

Yes

NR

NR

Yes

Yes

No3

No

No

Yes

Locus of Control

Smoking Knowledge

No

Yes

No

Yes

No

Yes

No

Yes

1This study reported different patterns of results across different grade

levels. Results presented here are collapsed across grade levels.

2NR = Effects on this variable not reported

3There were no differences between groups on attitudes at posttest, but there

were significant differences between some (but not all) of the experimental

conditions and the control condition at one year follow-up.

59
responsible for producing certain effects. As Cook (this volume)

points out, dismantling research designs which remove hypothesized

critical components are particularly appropriate for this

purpose. Unfortunately, such studies have not yet been conducted

and all SPST studies to date have confounded components designed

to enhance general personal competence with specific smoking

related information and cigarette refusal skills.

The final question in table 1 concerns whether setting factors and

subject variables moderate the effects of SPST. A number of

studies have answered this question affirmatively. Botvin et

al. (1980; 1983) reported significant Sex by Treatment

interactions; Botvin et al. (1980) and Pentz (1983) both found

SPST to be differentially effective at different grade levels; and

Pentz (1983) found that her intervention produced the largest

effects for adolescents who were initially classified as

aggressive (as opposed to passive or moderately assertive).

Although setting/subject differences seem to be obtained with some

consistency, there has been as yet little attempt to explain such

findings. Attempts to put forth some explanations, even if they

are posthoc, may eventually enhance our understanding of why and

how SPST operates.

Summary and Suggestions for Future Research

The old adage that frequently accompanies review articles-that

"more research is needed”--is applicable to the SPST area as

well. However, we do not need more of the same. There is no

rationale that justifies additional "treatment versus no

treatment” studies that fail to address the issue of why SPST

works. The research strategies most likely to advance the field

are Investigations that include experimental manipulations of

major components of the SPST model and appropriate measures of how

these programs achieve their effects.

In some ways, Botvin’s work can serve as a model for the type of

developmental work that is needed. After developing a treatment

package, he and his colleagues have proceeded to test the effects

of modifying this basic program by varying the scheduling of

intervention meetings (Botvin et al. 1983), adding booster

sessions to enhance maintenance (Botvin et al. 1983; in press),

and implementing the program with peer leaders versus classroom

teachers (Botvin et al. in press). They have even dared, in the

last couple of instances, to put to empirical test some of the

“myths, untested and erroneous assumptions". (Johnson 1982) that a

large number of investigators still accept uncritically. Future

SPST studies should be designed to evaluate the truth or falsity

of the potential advantages and disadvantages of SPST discussed

earlier.

To summarize the current status of the SPST approach in a few

sentences, the results uniformly suggest that an effective smoking

prevention approach has been developed. However, much more work

remains to be done and, in particular, we know little about how or

60
why SPST seems to work. Such knowledge is important for testing

the adequacy of the conceptual model on which SPST is based, to

provide guidelines for determining which SPST components need to

be retained and which can be discarded, and for suggesting ways in

which SPST interventions can be made more effective. Of course,

much the same can be said of social inoculation prevention

approaches. We will now turn to more specific recommendations for

future research, which are summarized in table 3. Botvin and

Wills (this volume) have made this task easier for us by

concluding their paper with recommendations for future research.

We have listed their points in the upper part of table 3, and we

will use these suggestions as a springboard for recommendations of

our own.

They begin by calling for measurement of the impact of SPST on the

skills and personality variables being targeted. While this is

certainly needed, much more attention needs to be given to the

measurement of these intervening variables. With the exception of

role play assessments and observational measures of smoking

refusal skills developed by Schinke and Gilchrist (1983) and Pentz

(1983), the measures utilized to date have consisted of

questionnaires. There are numerous questions regarding the

paychometric adequacy of such measures. Two particular issues

which need to be addressed in future research are the multimethod

assessment of these hypothesized mediating variables and their

discriminant validity. It is not clear if the variables listed in

the center of figure 1 are distinct factors or different ways of

measuring the same construct. Careful measurement of these

mediating processes is as important for the understanding and

refinement of SPST programs as is careful measurement of smoking

behavior.

We have already discussed the importance of carrying this issue of

underlying variables further by attempting to identify which

components of the SPST package lead to changes in particular

mediating variables. Study of the impact of specific program

components on particular mediating variables can be efficiently

accomplished in small scale, short-term analog studies (McCaul and

Glasgow in press). The related question of which of these

variables are in turn related to change in each of the outcome

variables on the right aide of figure 1 will probably require

larger scale long-term trials due to the low base rates of

initiation to substance use over short time intervals.

Botvin and Wills’ second recommendation is that we study lower SES

and non-school populations who are at risk for becoming substance

abusers. We are supportive of this recommendation, but such

research could be enhanced by prior consideration of what it is

about different populations that should make SPST either more or

less effective. Without such thinking, one could envision

proposals to skip from one lower SES and non-school population to

another, to propose teats in urban vs. rural areas, to try

"middle" schools vs. "junior highs” and so on, ad infinitum. A

related issue is that there have not been sufficient analyses in

6 1
TABLE 3

Recommendations for Future Research on SPST

Botvin and Wills’ recommendation:

1. Measure the impact on skills being targeted

2. Study minority populations at high risk

3. Identify active ingredients of SPST

4. Identify factors affecting program effectiveness

5. Test SPST against competing prevention programs

6. Study ways to insure successful implementation

Other issues in need of study:

1.

2.

3.

4.

5.

6.

Additional development and validation of measures of mediating

variables

Investigations of relationships of mediating variables to SPST

intervention components and to outcome variables

Identification of which “transitions” are affected by SPST

(nonsmoker to experimental smoker, etc.)

Investigation of problem specific social skills training

vs. general SPST

Evaluation of the contribution of homework assignments to SPST

and the issue of adherence to such assignments

The necessity of providing anxiety management training

existing studies of which subset of the adolescent population most

benefits from SPST. In particular, we need to know if SPST

primarily reduces initial experimentation with cigarettes,

decreases the number of experimental smokers becoming more regular

users, and/or serves as a buffer against regular users becoming

daily, habitual smokers. Again, these data are presently

available, but such analyses have generally not been reported. In

62
fact, in their earlier studies, Botvin's group excluded anyone who

had smoked at pretest (Botvin et al. 1980; Botvin and Eng 1982).

It can be argued that these excluded subjects are the very

students most in need of a prevention program (Biglan and Ary,

this volume).

The third recommendation about identifying active ingredients of

SPST is certainly indicated. However, the SPST package is so

complex that more specific recommendations are in order. We have

listed three issues which we feel should receive high priority for

future research (see points 4-6 at the bottom of table 3). The

central issue is whether or not general training in social and

personal skills adds anything to the specific training in

cigarette refusal skills provided by almost all present day

smoking prevent ion programs. The study of problem-specific

vs. broad-spectrum coping skills training is probably the issue

most in need of study at the present time. A second

under-researched issue is the role of homework assignments in SPST

training. By systematic manipulation of homework assignments as

well as careful measurement of adherence to such assignments, much

could be learned about SPST. It seems fitting that the issue of

SPST homework be investigated, since the proponents of this

approach are essentially advocating adding a course in life skills

and personal competence to the junior high school curriculum.

Finally, an issue which might permit trimming of some of the

excess fat from the complex SPST curriculum la the necessity for

the inclusion of relaxation training and anxiety management

procedures. At least as compelling an argument can be made for

the importance of such components in adult smoking cessation

programs since a majority of adult smokers report using cigarettes

to reduce tension and stress. Yet, controlled investigations of

the contribution of relaxation training and other anxiety

management strategies to smoking cessation programs have produced

negative results (see reviews by Glasgow and Bernstein 1981;

Pechacek 1979).

The fourth point in the top portion of table 3 states that we

should attempt to identify factors that negatively or positively

affect program effectiveness. Research to date suggests that this

is an important issue and that we should be cautious when making

general statements about the effects of SPST. Interact ions have

already been identified between treatment and the following

factors: grade level, gender, and urban/rural setting. Some of

the developmental factors addressed by Glynn and Leventhal (this

volume) should help to explain these differential results.

Botvin and Wills’ fifth point is that SPST should be tested

against competing substance abuse prevention programs. We

disagree. It makes little sense to just compare one group’s

program to another for the sake of trying to conclude that one is

better than or equally effective as another. The overwhelming

odds are that the results of such a “horse race” comparing, say,

the Cornell program to the Minnesota program, the USC program or

the Oregon program would end up the same way as have the great

63
majority of comparative psychotherapy outcome studies: all

treatments would be better than no treatment and not significantly

different from each other. Also, given the relatively similar

results reported across these different programs, the sample size

that would be required to conduct a sufficiently powerful study

would be enormous. A much more informative strategy would be to

compare conceptually distinct interventions with the measurement

of mediating variables predicted to be differentially affected by

the different treatments.

Botvin and Wills’ final point concerns implementation issues.

They suggest that such research should come after the above

questions have been answered. While it could certainly be argued

that there is a great deal of more basic research that needs to be

done before focusing attention on dissemination, implementation

research could be conducted concurrently with more basic studies

of treatment process. Both types of investigations can

potentially reinforce each other. One implementation factor

potentially worthy of investigation might be the use of

computer-assisted video instruction to deliver portions of SPST

programs.

In conclusion, to integrate the above myriad of recommendations,

we will describe an example of the type of study which needs to be

conducted. Such a study would compare training in specific social

skills relevant to cigarette refusal to either general SPST

training not specifically pertaining to cigarettes and/or to the

combination of those two approaches. It would include carefully

developed procedures to assess hypothesized critical intervening

variables and it would be conducted with a sufficiently large and

heterogeneous sample such that analyses could be conducted on

subject and setting factors potentially affecting outcome. It

would contain measures of “problem behaviors” such as the use of

other substances in addition to cigarettes, assessment of changes

in peer group relationships, and indices of adherence to homework

assignments. Finally, the study would investigate the utility of

individually tailoring components of SPST based upon subjects’

scores on the mediating variables discussed above. Such tailoring

could be done either initially or in a maintenance “booster”

intervent ion.

FOOTNOTES

1Although Schinke and Pentz have conducted far fewer studies than

Botvin's group, it should be noted that they have somewhat more

consistently found significant differences favoring experimental

conditions on measures of problem-solving and videotaped role

plays of cigarette refusal.

64
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Botvin, G.J.; Eng, A.; and Williams, C.L. Preventing the onset of

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Botvin, G.J.; Renick, N.; and Baker, E. The effects of scheduling

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Botvin, G.J.; Baker, E.; Renick, N.; Filazzola, A.D.; and Botvin,

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Rand McNally, 1979.

Danaher, B.G. Rapid smoking and self-control in the modification

of smoking behavior. J Consult Clin Psychol 45:1068-1075,

1977.

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in adolescents: A psychosocial perspective. In: Coates, T.J.;

Petersen, A.C.; and Perry, C.; eds., Promoting Adolescents

Health: A Dialog on Research and Practice. New York: Academic

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Glasgow, R.E.; and Bernstein, D.A. Behavioral treatment of

smoking behavior. In: Prokop, C.K.; and Bradley, L.A.; eds.,

Medical Psychology: contributions to Behavioral Medicine. New

York: Academic Press, 1981.

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and amount of therapist contact in smoking cessation programs.

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Haynes, R.B. Determinants of compliance. In: Haynes, R.B.;

Taylor, W.D.; and Sackett, D.L.; eds., Compliance in Health

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Jessor, R. Critiaal issues in research on adolescent health

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Promoting Adolescent Health: A Dialog on Research and Practice,

New York: Academic Press, 1982, pp. 447-465.

Johnson, C. A. Untested and erroneous assumptions underlying

antismoking programs. In: Coates, T.J.; Petersen, A.C.; and

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Research and Practice. New York: Academic Press, 1982.

Judd, C.G.; and Kenny, D.A. Process analysis: Estimating

mediation in treatment evaluations. Evaluation Review

5:602-619, 1981.

Lando, H.A. Effects of preparation, experimenter contact, and a

maintained reduction alternative on a broad-spectrum program for

eliminating smoking. Addict Behav 6:123-133, 1981.

McCaul, K.D.; and Glasgow, R.E. Preventing adolescent smoking:

What have we learned about treatment construct validity? Health

Psychology in press.

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and Health: A Report of the Surgeon General.

U.S. D.H.E.W. Publication No. (PHS) 79-50066. Washington,

D.C.: U.S. Gov. Print. Off., 1979.

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social skill development. In: Glynn, T.J.; Leukefeld, C.G.;

and Ludford, J.P.; eds., Preventing Adolescent Drug Abuse:

Intervention Strategies. National Institute of Drug Abuse

Research Monograph 47. DHHS Publication No. (ADM) 83-1280.

Washington, D.C.: Supt. of Docs., U.S. Gov. Print. Off., 1983,

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adolescents: A critical review of time trends, dimensions and

outcome, 1972-1982. Manuscript submitted for publication,

1984.

Schinke, S.P.; and Blythe, B.J. Cognitive-behavioral prevention

of children’s smoking. Child Behav Ther 3(4):25-42, 1982.

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smoking. J Sch Health 53:416-419, 1983.

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Adolescents. Baltimore: University Park Press, 1984.

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applications, and functions. J Consult Clin Psychol 51:14-27,

1983.

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Disease Control, National Clearinghouse for Smoking and Health,

September, 1971.

AUTHORS

Russell E. Glasgow, Ph.D.

Oregon Researah Institute

195 West 12th Avenue

Eugene, OR 97401

Kevin D. McCaul, Ph.D.

Programs in Health and Behavior

Department of Psychology

North Dakota State University

Fargo, ND 58105

66
What We Know About the Social

Influences Approach to Smoking

Prevention: Review and

Recommendations

Brian R. Flay, D. Phil.

BACKGROUND

Peer and family influences have been shown more consistently than any

other factors to be primary causes of the onset of smoking among

adolescents (Flay et al. 1983a). Media influences are also thought

to be important, although this has not been established empirically.

The social Influences approach to smoking prevention focuses on one

or more aspects of (a) teaching students about the social influences

to smoke, (b) providing them with behavioral skills with which to

resist those influences, and (c) correcting their perceptions of

social norms.

The seminal study of this genre (Evans et al. 1978) relied heavily on

McGuire's (1964) social inoculation theory. Social inoculation is

analagous to biological Inoculation, whereby a person is exposed to a

small dose of an infectious agent in order to develop antibodies,

thereby reducing susceptibility to subsequent exposure. This model,

applied to smoking, posits that resistance to persuasion will be

greater if one has developed arguments with which to counter social

pressure to smoke (Evans 1976). According to the theory, the

development of counterarguments should inoculate one against social

Influences in real-life situations in a manner analagous to

biological inoculation increasing resistance to the disease

inoculated against. Two studies by the Houston group (Evans et al.

1978, 1981) were based on this theoretical approach, with added

theoretical bolstering from attitude change (persuasive

communications) theory (McGuire 1969) and social learning theory

(Bandura 1977). Their programs used same-age peers on film to impart

information about the three major social influences to smoke and

focused on Immediate rather than long-term consequences of smoking.

Researchers at Stanford and Minnesota quickly followed the Houston

research with a second generation of studies. They placed greater

emphasis on social learning theory, and added elements derived from

attribution theory (Jones et al. 1972) and commitment (Kiesler 1971).

While the first studies by Evans et al. Included films showing

students being exposed to peer pressure and ways of resisting it,

learning those skills does not appear to have been a primary

67
objective of the program. The second generation of studies allowed

students to role-play and receive feedback on their performance of

the behavioral skills. These relatively small-scale studies also

included the first attempts to test (a) the contribution of various

components of the programs, and (b) the differential effectiveness of

different program providers or facilitators.

As this review will suggest, the so-called first and second

generations of studies of the social Influences approach to smoking

prevention can now be considered as no more than pilot studies of a

promising approach. They each had serious methodological flaws,

including only one school per condition in the second generation

studies, that made the interpretation of their results difficult.

However, the consistency of their results made further exploration of

the approach seem worthwhile. The Stanford and Minnesota researchers

quickly moved into improved third generation studies, assigning two

or three schools per condition using some form of randomization.

These researchers were also involved in third generation studies by

three other groups that tested the social influences approach in the

context of larger community studies (North Karelia, Oslo, and

Minnesota).

Third generation studies, while an improvement upon first and second

generation studies, still had many methodological problems and,

therefore, plausible alternative explanations of their findings.

Smoking prevention research is a young field that is just beginning

to mature. Early results, as in any new science, need to be

considered only as suggestive, not definitive; and these early

studies contributed more by the discovery of issues and the

development of methodologies than by providing unambiguous results.

Much improved fourth generation studies were made possible by the

experiences and lessons of the early first, second, and third

generation studies. Six fourth generation studies mostly have been

large-scale randomized trials that have attempted to maximize

internal validity in order to demonstrate the overall effectiveness

of the social influences approach.

Seventeen school-based studies of the social influences approach to

smoking prevention were located. [Studies that include broader life

and/or social skills training (e.g., Botvin and Eng 1980, 1982;

Botvin et al. 1980, 1983, in press; Pentz 1983; Schinke and Blythe

1981; Schinke and Gilchrist 1983) are reviewed by Botvin and Wills,

and by Glasgow and McCaul elsewhere in this volume.] The 17 studies

are reviewed in rough chronological order of their intervention

within the four groups (generations) described above. For most of

the studies to be reviewed, the date the study commenced corresponds

with placement into the four generations. For each study the

program(s) tested are described in terms of the grade(s) of

intervention, number of sessions, total duration of the program,

primary provider, types of peer leaders used, and other salient

factors. Table 1 presents summary information about program

characteristics. Methodological characteristics of each study are

also described, including the experimental comparisons attempted, the

number of units assigned to each condition, what those units were,

68
whether they were randomly assigned, whether pretest differences were

reported, the time of longest followup, whether or not individual

students could be tracked over time, the extent of attrition, and

whether or not and the type of biological validation of self reports

of smoking. Table 2 presents the summary of methodological

information. The reported results are also described for each study,

with comments on any plausible alternative interpretations, and these

are summarized in table 3. Finally, I will synthesize the extent of

our knowledge from all reviewed studies and provide recommendations

for future research.

THE HOUSTON STUDIES (THE FIRST GENERATION)

Richard Evans and his colleagues (1978, 1981) at the University of

Houston developed and tested the first of the social influences

programs for smoking prevention. Their program used nonsmoking,

same-age peers on film to impart information about the three major

social influences to start smoking. The presentation of each film

was followed by "knowledge tests" that emphasized immediate rather

than long-term consequences of smoking, small group discussion of

resistance to persuasion, and the provision of posters to be placed

around the school to serve as continuing reminders. An experimental

test compared students in schools that received this program over

four consecutive days, a program plus feedback group that received

both the program and feedback about the smoking rates among their

classmates at the three posttests (at 1- 5- 10-weeks), a repeated

testing group that was exposed only to the pretest and three

posttests, and a minimal-testing control group that was exposed only

to the pretest and the final posttest. A total of 750 students in 10

junior high schools were included in the study. Two schools were

assigned to each of the four conditions (procedure unknown), and in

two other schools students were assigned randomly to the four

conditions. Reported results did not separate the between-school and

within-school conditions. This was the first prevention study to

include collection of samples of saliva to enhance the honesty of

self-reports of smoking (Evans et al. 1977) by using a variation of

the bogus pipeline technique (Jones and Sigall 1971). Results at the

10-week posttest indicated that the proportion of pretest nonsmokers

in the program conditions who reported smoking at least one cigarette

in the last month (10.0% in the program condition and 8.6% in the

program plus feedback condition) was approximately half that of the

minimal-testing group (18.3%). However, there were no significant

differences between the program groups and the repeated testing group

(10.3%). Note too that any subjects who reported having tried

smoking at the pretest (31% of the total sample) were excluded from

the analysis of program effects.

Evans and colleagues (1981) reported long-term results of the Houston

program. A total of 13 schools were assigned (nonrandomly) to one of

three experimental or four control conditions during the course of

the study. Initially, however, a six-group design, three

experimental and three control groups, was set up in seven of the

schools. Aspects of the program (up to eight films presenting

various messages) were provided to a cohort in each of the

69
experimental schools during each of three years, grades 7 through 9.

The control schools varied from a repeated measurement condition (12

measures during the study that included saliva thiocyanate testing)

to an additional set of schools that was added at the end of the

study as posttest-only controls. Due to administrative and other

difficulties, groups were successively combined during the course of

the study so that only three conditions remained by grade 9.

Subjects were not identified across time, so that only

cross-sectional analyses were possible, rather than more appropriate

longitudinal analyses. The reported cross-sectional analyses are

rather difficult to interpret because the extent to which the

composition of the sample changed over time is not known (sample

sizes ranged from 1,352 to 3,296). It is clear that there were no

program effects by the end of grade 7; indeed, there may have been a

significant reverse effect. The authors claim significant program

effects in subsequent years on the basis of approximately 9.5% of

program students versus 11 to 14% of controls reporting smoking two

or more cigarettes per day by the end of grade 9. Evans et al. also

reported superior knowledge by the program groups and a correlation

between knowledge and smoking behavior; the inability to conduct

longitudinal analyses, however, means that such data cannot be

interpreted to mean that changes in knowledge caused changes in

behavior. Overall, it must be concluded that (a) this study did not

replicate the earlier results at the end of the grade of intervention

(grade 7). and (b) the claimed program effects at 3-year followup are

small and difficult to attribute to the program.

THE SECOND GENERATION STUDIES

Despite the inconclusive results of the Houston studies, the

theoretical derivations seemed firm enough to encourage other

researchers to strengthen and test the approach further. The second

generation of studies on the social influences approach to smoking

prevention are characterized in three ways. First, they expanded

upon the basic inoculation-with-communication model by enhancing the

role of social learning theory and also considering attribution and

commitment theories. Second, they attempted to test the relative

contribution of the various components of their more complex

interventions and/or the importance of the identity of the provider

of each program. Third, they were relatively small-scale studies, as

far as school-based studies go, with one school per condition.

Project CLASP (Stanford)

Investigators at Stanford (Perry et al. 1980; McAlister et al. 1980;

Telch et al. 1982; see also McAlister et al. 1979) expanded upon the

basic social inoculation with persuasive communication model.

Project CLASP (Counseling Leadership Against Smoking Pressures)

included the same features as the Evans et al. program with three

important theory-based innovations. First, high school students were

used as "peer" teachers for 7th graders; second, a session was

introduced to increase social commitment not to smoke; and third,

behavioral learning techniques (Bandura 1977) were introduced in the

form of role-playing where students acted out situations requiring

70
resistance to social influences. The program consisted of three

sessions on consecutive days, with four booster sessions spaced over

the remainder of the grade 7 school year. The program was tested in

one school that had been identified as having a high rate of smoking

among older students and where administrators were seeking a solution

to the smoking problem; two "roughly matched" schools were used as

nonrandom controls. Breath samples were collected from all subjects

in an attempt to increase the honesty of self-reports of smoking

behavior. Individual subjects could not be followed, so analyses

were limited to cross-sectional comparisons. At the end of grade 7,

students in the treatment school reported significantly less smoking

in the past week (5.3%) than students in the control schools (11%).

At the end of grade 8, 5.6% of students in the program school

reported smoking in the last week compared to 16.2% in one of the

control schools (one control school was dropped from the analyses

because of problematic pretest differences; McAlister et al. 1980).

At the end of grade 9, 5.296 of students in the program school

reported smoking in the last week, compared to 15.1% in the remaining

control school (Telch et al. 1982).

This is the first study to have reported large preventive effects of

the social influences approach, with the program group smoking weekly

at only one-third the level of the control group. This is also one

of the few social influences smoking prevention programs for which

prevention of alcohol and marijuana use has also been reported

(McAlister et al. 1980). Unfortunately, the encouraging results

cannot be attributed totally to the program with any confidence

because of the methodological problems noted above. The authors of

the study are well aware of the shortcomings, and they label the

study as a pilot project, pointing out some of the possible

alternative interpretations:

It is possible that these results are biased by natural

differences between the students in the two schools, by

statistical regression, or by 'pseudo-regression' caused

by deliberately choosing a population with reportedly

acute problems as the experimental group and one with

fewer reported problems as the control group (McAlister

et al. 1980, pp. 720-721).

The First Minnesota Study (RASP)

The Robbinsdale Anti-Smoking Project (RASP) was initiated in the Fall

of 1977. Data have been reported for the end of the intervention

year (Hurd et al. 1980) and for 1- and 2-year followups (Luepker et

al. 1983). Project RASP was the first study to attempt to test the

value of (a) same-age peer leaders, and (b) a public commitment

procedure. The initial design involved four schools and five

experimental conditions. The five experimental conditions were (a)

controls with questionnaire and saliva sample monitoring, (b)

minimally measured controls (later dropped from the study because

saliva samples were not collected at pretest), (c) social influences

curriculum, (d) social influences curriculum with peer leaders

(personalization), and (e) social influences curriculum with peer

71
leaders and a commitment procedure. The tested social influences

curriculum consisted of a combination of video/film presentations

(some of which were modifications of the Evans et al. materials) and

discussion groups. The group discussions covered the social

consequences of smoking, ways of saying no, correcting misperceptions

of the proportions of people who smoke, and media pressures.

Students were provided with opportunities to develop

counterarguments, and role-play and practice resistance skills. In

the peer-led condition, selected peers appeared in some of the video

materials and led the group discussions. In the commitment

procedure, students were recorded and played back to the class making

a statement of why they were not going to smoke. The basic

curriculum was four sessions long, with the commitment procedure

adding a fifth period; the sessions were spread fairly evenly across

the grade 7 school year, and were delivered or supervised by trained

pharmacy students.

Classrooms within one school were assigned randomly to whether or not

they received the commitment procedure. The four schools were

assigned to the remaining four conditions so that one lower SES and

one higher socioeconomic status (SES) school was assigned to program

conditions and one pair to control conditions. All students (except

those in the dropped minimal measurement conditions) were measured at

pretest, between the second and third session of the curriculum, at

the end of the school year, and at 1- and 2-year followups. A

distinct improvement over previous studies was that individual

students were tracked through the study.

At each measurement point, data were collected from approximately 80%

of those present at the previous measurement point; 53% of the

original students completed the 2-year followup. At the end of the

intervention year, both the social influences programs seem to have

reduced the amount of ever smoking, though not to a statistically

significant degree. Only the social influences curriculum without

peer leaders (but still with films) seems to have reduced

experimental smoking; and only the peer-led social influences

curriculum seems to have prevented an increase in regular (usually

weekly) smoking. The commitment procedure did not add significantly

to the peer-led program. By the 1-year followup, the only

significant effect was a greater number of never smokers remaining in

the peer-led condition school. By the 2-year followup, even that

difference seems to have decayed somewhat, though when measures of

quantity and frequency are included in a continous index of smoking,

the peer-led curriculum still appears to be superior to a significant

degree.

This study made some innovative advances. Unfortunately, it can be

considered only as a pilot study in that methodoiogical problems make

the reported results very difficult to interpret. The major

difficulty is that SES and other social risk factors for smoking

(e.g., parental, siblings, and friends smoking) were perfectly

confounded with the expected strength of the experimental condition.

That is, the control school was the lowest on SES and the highest on

all the social risk factors; the school that received the social

72
influences curriculum with peer leaders was the highest on SES and

the lowest on all social risk factors; and the school that received

the social influences curriculum from pharmacy students was in

between (see detailed pretest data reported by Hurd et al. 1980).

Thus, without any program, the highest rates of smoking would be

expected in the control school, and the lowest rates in the peer-led

program school. Large pretest differences in smoking rates add to

the difficulties of interpretation --at the final posttest, the

rank-ordering of the three conditions remaining at that time in terms

of level of smoking (experimental plus regular) is exactly the same

as at pretest. Even the finding that peer leadership was superior is

difficult to interpret, in that the selected peers also appeared in

some of the film materials--that is, peer leadership was perfectly

confounded with the familiarity of actors in the media materials.

THE THIRD GENERATION STUDIES

The second generation pilot research prepared the Stanford and

Minnesota researchers to conduct larger and improved studies. The

Minnesota researchers conducted an improved test of their program

with grade 7 students. Both groups of researchers tested their

approach with high school students. Individual investigators from

these groups were also involved with three other groups of

researchers who tested the social influences approach to smoking

prevention in the context of larger community interventions. The

seven third generation studies are reviewed below in chronological

order of their starting date.

The North Karelia Youth Project

The North Karelia Youth Project (Vartiainen et al. 1983) consisted of

community- and school-based interventions to influence behaviors that

are risk factors for cardiovascular disease. A portion of the

comprehensive program was a school-based smoking prevention

curriculum that was based on the CLASP model (Perry et al. 1980).

Two selected schools in North Karelia comprised an intensive

intervention condition in which project staff provided a 10-session

curriculum; two matched schools in North Karelia represented a

county-wide condition, in which regular teachers provided a 5-session

version of the curriculum; and two matched schools in another county

comprised a control condition. Grade 7 students were surveyed by

questionnaire and serum samples at pretest (fall 1978), immediately

after the 2-year intervention (fall 1980), and after a further 6

months (spring, 1981). Of all students participating in the pretest,

95% participated in the Immediate posttest 2 years later, and 88% in

the final followup 6 months later.

At the first followup, 21% of students in the Intensive intervention

condition reported smoking monthly, as did 19% in the county-wide

Intervention schools, compared to 29% in the reference schools. By

the final posttest, these precentages had increased to 24%, 22%, and

34%. respectively. This pattern of results was repeated for

proportions of students smoking daily as well. Analyses by gender

73
found that the significant program effects were confined to boys.

The reported results are very encouraging. However, they must be

accepted with caution for at least two reasons. First, the method of

school selection leaves open the possibility of school-level

differences being reponsible for the observed differences; however,

the magnitude of the observed effects relative to the magnitude of

pretest differences makes this unlikely. More serious is that the

tested program was only one very small component, not only of a more

comprehensive school-based program, but also of a large and very

intensive community-wide intervention (Puska et al. 1981a, 1981b).

It is, therefore, impossible to determine the extent to which the

school program contributed to any overall effect; the lack of any

differences between the intensive and county-wide conditions is

inclusive.

The Second Minnesota Study (PCSC)

The second Minnesota project (Arkin et al. 1981; Murray et al. 1980,

in press) overcame many of the methodological problems of Project

RASP, and also attempted to make other advances in our knowledge of

prevention. In two studies, three versions of a social influences

curriculum were compared with a long-term influences (health)

curriculum. Type of leader (adult health educator versus same-age

peer), the use versus nonuse of media (films), and the public

commitment procedure were also tested. In sequential replications of

the study, type of provider/facilitator (research staff health

educator versus regular classroom teacher) was tested. All curricula

consisted of five class sessions for grade 7 students spread

throughout the school year.

Eight schools were split at the median for pretest smoking rates, and

then one from each group was assigned randomly to the four

conditions. Within all eight schools, half the classrooms were

randomly assigned to the commitment procedure. Two of the eight

schools were control schools in Project RASP, and historical control

data from them were used as the only control for the first study

(research staff delivered). For the second study (teacher

delivered), two additional schools, nonrandomized, served as a

nonequivalent control group. Students were assessed by questionnaire

and saliva sample at pretest (beginning of grade 7, in 1979 for the

first study and in 1980 for the second study), Immediate posttest at

the end of grade 7, and 1-year followup (for the first study only) at

the end of grade 8. Most results were reported in terms of an index

of weekly smoking formed by averaging three self-report measures of

smoking. Results are reported only for pretest nonsmokers and

experimental smokers. The few students who were regular smokers

(i.e., at best monthly) at pretest were not included in analyses of

program effects.

Data reported by Arkin et al. (1981) suggest that in the short-term,

the health consequences program was most successful in reducing the

proportion of nonsmokers who tried smoking by the immediate posttest

(15%). and the social influences programs were next most successful

74
(18-21%) when compared with the historical control (31%). The

analyses presented by Murray et al. (in press), based on the

composite index measure of smoking and covarying for pretest

differences in social risks to smoke (i.e., parental, peer, and

sibling smoking and SES), did not show differences between the four

program conditions but did suggest that all four programs were better

than controls. By l-year followup of the first study, however, the

peer-led conditions appeared to be more successful for pretest

nonsmokers. When pretest experimental smokers are considered, there

were no differences between conditions when health educators

delivered all programs (Study I); but the peer-led social influences

(also called short-term influences) program was more effective by the

immediate posttest when delivered by teachers (Study II). However,

the pretest experimenters in the control group had the lowest level

of smoking by the immediate posttest, making it difficult to

interpret any other program differences. The pattern of differences

found among the four program conditions at the immediate posttest for

Study II was replicated at l-year followup in Study I. That is, by

l-year followup, pretest experimental smokers were smoking at

significantly higher rates when they received the social influences

program without peer leaders than when they received either the

social Influences program with peer leaders or the health program

from health educators. At no point in time, in either study, were

there differences due to the use of films or the commitment

procedure.

These results are difficult to interpret for several reasons. First,

despite the use of an improved procedure of random assignment after

matching, baseline smoking experience in Study I was lower for the

two peer-led conditions (average proportion never smoked = 50%) than

for all other conditions (average of 64% for the other program

conditions, and 56% for the historical controls) (Arkin et al. 1981).

Second, no baseline smoking level data were reported for Study

II--the existence of large differences in the same schools in Study I

would lead one to expect such differences in Study II unless

otherwise reported. Third, pretest differences in smoking levels

were not adjusted out, even though the acknowledged (but unreported)

baseline differences in social risk factors were covaried out in all

but the Arkin et al. (1981) paper. Fourth, the use of historical and

nonequivalent control groups is questionable, and no baseline data

were reported for one of them.

To summarize, these studies attempted to overcome many of the

problems of Project RASP, and found (a) no significant overall

differences between programs at the immediate posttest, (b) a

suggestion that social influences programs were more effective when

peer leaders were used, (c) that peer-led social influences programs

were more effective than adult social influences or health programs

at preventing pretest nonsmokers from starting to smoke, and (d) no

significant program effects on pretest experimental smokers. However,

despite the methodological Improvements, the meaning of any of these

findings is unclear because of serious methodological problems that

remained.

75
The Oslo Youth Study

Tell et al. (in press) report results from a test of a social

influences smoking prevention program delivered as a component of a

comprehensive health education curriculum. A 10-session program was

delivered to grades 5, 6, and 7 students (age 11 to 14) partly by

older peer leaders and partly by project staff. Six schools were

formed into matched pairs. One school from each of two pairs was

randomly assigned to receive the program, while the third program

school was assigned due to an existing relationship between that

school and project staff. Signed consent for participation was

obtained from 82% of parents. Students were pretested via

questionnaire, saliva samples, and other health measures at pretest

(early 1979), and 2 years later (early 1981). The intervention took

place over the 2 years between surveys. Sixty-eight percent of the

initial sample of students completed both questionnaires. Attrition

was greater in control (4096) schools than program schools (25%).

Overall results indicated that the program had an impact upon those

students who had never tried smoking prior to pretest. Of all

pretest students who had never smoked, 16.596 of the program group and

26.9% of the control group reported smoking by the posttest. In a

step-wise discriminant analysis, the program entered after pretest

measures of "acceptability of smoking," parental concern with the

student's health, gender, and availability of discretionary funds.

Pretest measures of friends' smoking and smoking knowledge also

entered at significant levels after the effect of the program.

Significant program effects were also reported for smoking knowledge

and intentions. Similarly, changes were observed in other

health-related behaviors as a result of the complete program--the

program group improved significantly more than the control group in

terms of exercise and alcohol consumption.

The results of the Oslo study are similar to others, with the pretest

nonsmokers from the program group smoking at 39% less than the

control group by the final posttest. However, several factors

prevent clear attribution of the observed effects to the social

influences smoking prevention curriculum. First, the smoking

prevention curriculum was only a portion of a much more complex

health behavior curriculum; the extent to which the remainder of the

program, or any changes caused by it, led to the changes in smoking

behavior cannot be determined. Second, there were reported pretest

differences, with the program students being more knowledgable and

viewing smoking as being less acceptable, and being almost twice as

likely to have tried alcohol. Third, there was differential

attrition from program and control groups, although the direction of

this difference (greater attrition from control schools) would tend

to reduce the chances of finding significant program effects.

Current Minnesota Studies

As part of a large-scale, community-based heart disease prevention

project (Blackburn et al., in press), several approaches to smoking

prevention are being tested (Perry et al. 1983a). One of these was a

76
social influences program. A six-session version of the "Keep It

Clean I" program was tested in three schools (N = 397) within one of

the program communities in 1981-82. Two schools on the outskirts of

Minneapolis were matched on size, SES and grade 7 smoking prevalence,

and used as controls (N=325). The program was taught 1 day each

month during the school year. Teachers and same-age peer leaders

received special training from project staff. Students were assessed

with questionnaires and saliva samples at the beginning and end of

the school year.

Equal numbers of students (4.7%) in the program and control schools

reported smoking in the week prior to pretest. At posttest, more

control than program students reported smoking in the previous week

(8% versus 5%); this difference was marginally significant. When all

grade 7 and 8 students in both sets of schools were assessed, it was

found that 8.196 of the program school students reported smoking in

the previous week compared to 11.8% of control school students. This

suggests that some or all of the observed effect could have been due

to the other antismoking activities being conducted in the

communities of the program schools. That is, whether the effects on

smoking onset are attributable to the school-based program or "were

complemented by the entire community-wide project cannot be

determined by this design" (Perry et al. 1983a. p. 11).

The Stanford High School Studies

The Stanford group has tested the social Influences approach with

high school students (Perry et al. 1980b). The tested program

emphasized the short-term physiological effects of smoking and the

social pressures influencing adoption of the smoking habit. For the

short-term physiological effects component, measures taken from

smoking and nonsmoking students were compared. Students were also

introduced to several smoking cessation procedures. Regular health

teachers were trained to deliver the program on four consecutive

days. All five high schools in one school district near Stanford

University were matched on SES and then assigned randomly to

experimental or control conditions. All students in three schools

received the program, and students in the other two schools received

the traditional tenth grade health material emphasizing the harmful

long-term effects of smoking. Students were assessed by

questionnaire and physiological measures at pretest (September 1978)

and posttest (February 1979).

At posttest, fewer students in the program condition than in the

control condition were smoking (in the past day, the past week, or

the past month). These results appear to be statistically

significant, and they were paralleled by changes in biochemical

indicators (carbon monoxide) and knowledge. This is the first study

to demonstrate that the social Influences approach can be effective

for high school students. Unfortunately, separate results were not

reported for those students who were smokers at pretest, and no

long-term data are available.

In a second high school study, Perry et al. (1983b) used a 2x3

77
factorial design to compare the relative effectiveness of teachers

and college-age peer leaders in delivering health versus social

influences versus physiological effects programs. Twenty classrooms

from four high schools were randomly assigned to the three levels of

programs; then the four schools were randomly assigned to teacher or

college student delivery. Each program consisted of three l-hour

sessions. Students were pretested immediately prior to the programs

(February 1980) and posttested about 2 months after the programs

(May, 1980). Data for assessments were obtained from questionnaires

and carbon monoxide samples. Staff members observed the

implementation of the programs in all classrooms.

All programs were implemented equally well. Of all students who

reported weekly smoking at pretest (N=82), 23% reported not smoking

during the week prior to posttest. Any differences between

conditions were not statistically significant because of small sample

sizes, and there certainly were no significant changes in the overall

rates of weekly smoking. (The apparent effects observed, however,

suggested that teachers may have been better than college students at

delivering health Information, but college students may have been

better than teachers at delivering the social influences

program--this pattern was also observed in the second Minnesota study

[PCSC].)

The USC High School Study

The High School Anti-Smoking Project (HASP) at the University of

Southern California (Johnson et al. 1984) compared the relative

effectiveness of social influences and health programs with grade 10

students. The value of peer leaders and the differential

contribution made by having familiar peers as actors in the media

material were also tested.

The tested social influences program included material on media

influences, social influences and skills for resisting them, values

clarification/decision making, and a public commitment procedure.

The health program included materials on lifestyles and health, the

long-term effects of smoking, the short-term physiological effects of

smoking, and the public commitment procedure. Both programs included

four sessions delivered by project staff (health educators) over a

3-month period.

On the basis of pretest data, nine high schools were stratified and

eight of them formed into pairs such that one high- and one

low-smoking school were yoked together. The four yoked pairs were

then randomly assigned to four experimental conditions created by

crossing the two program types (social versus health) and whether

peers in media material were familiar or unfamiliar. The one

remaining unyoked school, which was ranked in the middle for smoking

level, was assigned to be the control. Within each program school,

the program was delivered to only that half of the student body who

were in health classes during the semester of intervention. The

other half acted as within-school controls. One half of the classes

78
that received the program were randomly assigned to a peer leader

condition. The other half received the program without the use of

peer leaders. Students were assessed via questionnaire and saliva

samples at pretest (January/February 1981), immediate posttest

(May/June 1981), and at 1- and 2-year followups (May 1982 and 1983).

All data collection was conducted by trained data collectors who

visited the schools on predetermined, but unannounced, days. In most

cases, the classes in which data were collected were not the same

classes in which the program was or had been delivered. Attrition

rates were very high--65% by the end of the study, with no

differences in rates between conditions (Hansen et al. in press).

Three sets of main-effect comparisons were made--social versus health

program, peer leaders versus no peer leaders, and familiar versus

unfamiliar actors in media material. Possible interactions were

ignored because of limited sample size. Comparisons were made for

four possible transitions in smoking behavior: no smoking to any

smoking, experimental use (monthly or less) to heavier use, regular

use (a pack or less a week) to heavy use (more than a pack a week),

and current smoking (regular or heavy use) to nonsmoking (quit)

status.

Attrition was lowest for pretest never smokers (20% by the final

posttest). Pretest never smokers were marginally less likely to

become users if they were exposed to the health program than if they

were exposed to the social influences program or if they were

controls. Significant differences were observed only at the l-year

followup, where 46% of the health program students had tried smoking

versus 59% of the social program students and 58% of controls.

Although not significant, the same general pattern held at the 2-year

followup (60% versus 68% versus 68%. and 65% for the

within-health-school controls).

Of all experimental smokers at pretest, only 51% were present at the

immediate posttest, 36% at the 1-year followup, and 31% at the 2-year

followup. Using these samples, significant differences in the onset

of regular smoking was observed, with the social program holding the

onset rate to approximately half that observed for the health program

and control students (4% at immediate posttest, to 6% at one year, to

7% at 2 years for social program students, versus 8 to 9% to 9% to 13

to 14% for both health program and control students). When the land 2-year followup waves were combined, attrition was significantly

less than when considering either wave on its own (59% of subjects

had data at pretest and at least one of these followups). The above

pattern of results was replicated using these pooled data, possibly

reducing, to a small extent, the concern raised by high levels of

attrition. Attrition by pretest regular smokers was very high (87%

by the 2-year followup), and no significant program effects were

detectable using the remaining sample. Neither peer leadership nor

familiarity of actors in media materials made any significant

difference to the pattern of any of the results.

The reported results are obviously compromised to an unknown extent

by (a) severe attrition, and (b) possible ceiling effects, where only

79
at pretest.

a small proportion of the total sample had never tried smoking even

SUMMARY OF SECOND AND THIRD GENERATION STUDIES

The nine second and third generation studies have all provided

While results from no one of the studies were

interpretable in their own right because of methodological problems,

However, an analysis of

the methodological issues is worthwhile because if different studies

have different methodological problems, then they ought to cancel

each other out across studies, and the consistency of results would

then be an indication of a robust finding. On the other hand, if one

or more methodological problems, or threats to internal validity are

present in most or all studies, then the consistency of results would

not be very informative.

With only one to three schools per condition, often nonrandomly

assigned, many studies had noncomparable pretest levels of smoking

behavior and/or social risk values (i.e., numbers of peers, parents,

or siblings who smoke, and SES). In one study (CLASP), the program

school was identified as being a higher risk than the control school.

The label of a "problem" school in this respect might indicate that

additional "interventions" were going on at the same time as the

smoking prevention program and as a result contribute to any program

effect. However, the fact that the relative smoking rates in the two

schools were reversed between pretest and posttest, and the magnitude

of that effect, suggest that the smoking prevention program may well

have been at least partially responsible. Such an interpretation

must be considered with great caution, however, given that there was

only one school per condition in this study so that unknown selection

bias could still have been operating.

In contrast to CLASP, the two early Minnesota studies (RASP and PCSC)

both had pretest differences such that the hypothesized strongest

program group was at lowest risk to becoming smokers while the

hypothesized weakest program or control groups were at highest risk.

Thus, the observed patterns of results could have been observed even

without any interventions. The fact that some effects remained after

adjusting for some of the risk factors provides some encouragement.

However, these analyses were not able to adjust for pretest levels of

smoking (though they may well have been adjusted out, at least in

part, with the social risk factors), and the shortcomings of such

statistical adjustment are well known (Cook and Campbell 1979).

Clearly, we must interpret results from studies with known pretest

differences with great caution.

Three of the programs for which positive results were reported were

but small parts of more comprehensive and intensive interventions,

making it impossible to determine how much of the effect was due to

the tested program rather than the overall intervention. Three of

the studies provided tests of the social influences approach to

smoking prevention for high school students. The results were rather

mixed, however, and difficult to interpret. but they provide

80
encouragement for further research on the application of the social

influences approach to high school students.

Attrition was also a very serious problem for most of these studies.

Attrition can be a threat to internal validity if it is differential

across conditions. This seemed to be the case in only one study

(Oslo), and then In the direction that would be presumed to decrease

the chances of detecting a program effect. External validity is

always threatened by attrition, however; for example, if students at

high risk of becoming smokers are more likely to be absent from

measurement, this would decrease the possible program effect that

could be observed. See Hansen et al. (in press) for an analysis of

attrition issues in smoking prevention research.

Reviewing of many of these studies was often difficult because of

inadequate reporting of data. Some did not provide pretest data, and

most provided inadequate data about smoking behavior at posttests.

As we have noted elsewhere (Flay et al. in press) researchers should

report results for all categories, as established in pretest

measures, of smoking behavior and not just selected significant

findings, to enable readers to fairly judge the practical

significance of findings and make comparisons across studies.

Reported results across these nine studies were not as consistent in

their exact nature as in their magnitude. RASP, PCSC, Oslo, Stanford

High I, and the HASP health program were reported as reducing the

onset of smoking by pretest nonsmokers. CLASP, North Karelia,

Current Minnesota, and the HASP social program, on the other hand,

were reported as reducing the prevalence of regular smoking and/or

the transition from experimental to regular smoking status. In most

instances, the results for the other type of change were not

reported.

All of the second and third generation studies are also susceptible

to two other alternative interpretations of any observed effects:

(a) a testing by treatment interaction, because in most

instances the program and data-collection activities would

have been perceived by students as related; and

(b) a Hawthorne effect, in that program students received more

special attention than controls in almost all studies.

The Stanford, Minnesota, and USC studies attempted to test the value

of various components of the social influences approach, particularly

the use of peer leaders, social versus health programs, the use of

media, and the use of a commitment procedure. However, given the

generally low internal validity and uninterpretable nature of these

studies, none of the findings from these comparisons can be accepted

wholeheartedly without further replication.

On the basis of the earlier reports from the second and third

generation of studies, Fisher (1980) concluded that "It now seems

well established that these interventions work, at least to an

appreciable if not totally satisfactory extent" (p. 678). While

81
these studies, taken together, provided some encouragement for

examining the social influences approach further, the numerous

methodological problems with most of these studies when considered

alone, and the fact that some of the problems were common to all

studies, do not allow us to agree with Fisher. Indeed, the reported

results evidently were not considered by most researchers to be

robust enough to warrant large investments in large-scale studies

designed to test components. Rather, most of the fourth generation

of studies were designed with the sole objective of establishing

whether or not the social influences approach to smoking prevention

is efficacious when tested under more rigorous methodological

conditions.

THE FOURTH GENERATION STUDIES

Despite the many weaknesses of the above studies, the consistency of

reported results provided the impetus for improved studies. The

fourth generation of studies on the social influences approach to

smoking prevention placed a primary value on enhanced internal

validity. They may be characterized as large-scale field trials,

with five or more (half with 11 or more) units randomly assigned to

each condition. Most may also be characterized as demonstration

projects or summative evaluations, in that they compared only program

and control conditions, without attempting to test components or

providers. The six studies reviewed in this section varied, however,

in the success with which the tested programs were implemented, the

exact nature and length of the program tested, the grade level on

which it was tested, the type of peer leaders used, and who provided

it. The latter variable was explicitly tested in one of the studies.

The Waterloo Study

The Waterloo Smoking Prevention Program (Best et al. 1984; Flay et

al. 1983a, 1985) followed the basic principles of the social

influences approach as improved at Stanford and Minnesota but added a

component on decision making that was tailored to the smoking

decision. The program was tested on grade 6 students, 1 year earlier

than most other studies. Six one-hour, weekly sessions were delivered

by health educators near the beginning of the grade six school year

(October/November 1979); two maintenance sessions were delivered near

the end of grade 6; and three booster sessions were provided, two at

the beginning of grade 7 and one at the beginning of grade 8. Evans'

films were reproduced for the Canadian context using student actors

from the local theater group who were 1 or 2 years older than the

grade 6 students. Live peer leaders were not used in the classroom,

but the health educators were Master's students who deliberately

"underdressed" and encouraged students to call them by their first

names. Thus, they were similar to the college-age peer leaders used

in the Houston studies and Project RASP.

Twenty-two schools in two school districts in Southern Ontario

volunteered to participate in the study, and 11 were assigned, mostly

randomly, to each of experimental and control conditions. Pretest

differences were minimal, and were not observed for smoking behavior.

82
Study students were in the same schools for the duration of the

project, grades 6 through 8. Students were tested with questionnaire

and saliva samples at pretest (T1), immediate posttest (T2). the end

of grade 6 (T3), the beginning and end of grade 7 (T4 and T5), and

the end of grade 8 (T6--30 months after the core program). The

health educators were present at pretest and immediate posttest data

collection in both program and control schools, but new project staff

collected data at all other followups. Total attrition plus

absenteeism was less than 10% per year, and 67% of students provided

data at all six data points.

Program results were analyzed according to the pretest status of

subjects, and considerable complexity was found in the pattern of

changes over time. For students who had never tried smoking prior to

pretest, the program was marginally effective in preventing

trying--by the end of grade 8, 53% of the control students who were

never smokers at pretest had tried smoking, while only 40% of the

program students had done so. For students who had tried smoking but

classified themselves as quitters at pretest, 69.2% of the program

group and 50% of the control group remained quitters at the end of

grade 7, but this difference had reduced to 50% versus 46%

respectively by the end of grade 8. For those students who had tried

smoking only once prior to pretest, by the end of grade 8 almost

equal proportions of the program and control students had tried

smoking again (64% versus 63%). However, significantly more program

than control students had decided to never smoke again (43% versus

25%), and only 5% of the program group versus 13% of the control

group had become regular smokers (usually every week). For students

classified as experimenters (tried more than once, but smoke less

than weekly) at pretest, the results varied more across time. Almost

on at least one of the five posttests, compared to less than three

A high proportion of program

group experimenters quit immediately following the program, and this

when 63% of this group were still

quitters compared with 28% of the control group experimenters. By

so many more of the control group

experimenters had also quit that the difference was no longer

(Note that we expect many experimental smokers to quit eventually

because many more adolescents experiment with smoking than ever

The small number of pretest regular smokers

(five in the program and eight in the control conditions) precluded

summary, program effects varied over time, having greatest immediate

with no or little smoking experience at pretest.

The Waterloo investigators also analyzed the effects of their program

social influence reasons. The program was found to have its major

smoke. For example,

smoking prior to pretest, by the end of grade 8, 67% of those in the

83
program group versus 22% of controls still had never smoked, 6% of

the program group versus 39% of controls were experimental smokers,

and none of the program students versus 6% of controls were regular

smokers (Best et al. 1984). Such results provide some validation for

the theoretical rationale for the social influences approach to

smoking prevention.

The Waterloo study successfully overcame many of the methodological

problems of earlier studies, so that the reported results are more

readily interpreted as being due to the program. However. while

pretest comparability was maximized, attrition minimized, and more

detailed analyses reported, there remain several plausible

alternative explanations of at least some of the reported program

effects. First, a measurement by treatment interaction is possible.

This is especially likely at the first posttest where the health

educators also collected the data--although the collection of saliva

samples should have minimized it, and the lack of any significant

program effects at that point suggest that this interpretation of

subsequent effects is not very plausible. Second, as in all other

studies to date, a Hawthorne effect may be operating--the program

students received a great deal of attention from outsiders, and their

subjective evaluations tell us that they liked the health educators a

great deal. Third, there was large variability between schools (not

yet reported in detail), and program effects were apparent in only

some of the program schools--was there something special about them

that caused some or all of the observed effects? This question

cannot be answered. Despite these limitations, however, the Waterloo

study represents one of the more rigorous tests to date of the social

influences approach to smoking prevention; and the demonstration of

strong program effects on those students most at risk provides strong

support for the approach.

The Stanford/Harvard Study

McAlister et al. (1982) tested a 12-session, 2-year version of the

CLASP curriculum delivered to grade 7 and 8 students by high school

students under the supervision of research staff. Junior high or

middle schools were randomly assigned to program or control

conditions from five matched pairs in Massachusetts and California.

The program was not implemented in full in two of the program schools

because of administrative difficulties. Saliva samples and

questionnaire data were collected from students on four

occasions--October 1979, May 1980, October 1980, and May 1981.

School districts insisted that individual students not be identified,

so students generated their own I.D. codes. Analyses indicate some

problems with inconsistent use of codes (McAlister 1983). School

administrators estimated that between the first and last survey

periods approximately 30% of the students transferred to other

schools. Approximately 15% of parents excluded their children from

measurement,

Overall, only about one-third of the original students could be

Overall results suggest that the program only marginally reduced the

84
rates of weekly or monthly smoking, regardless of whether

cross-sectional (using all responses at each time point) or

longitudinal (using only those students who responded and could be

matched across all measurement periods) analyses are considered.

Wide school variations were observed, however, and the authors

attempt to provide reasons for significant program effects in two

pairs of schools and not others. Unfortunately, in the two pairs of

schools where significant program effects were observed, the program

schools had over 60% higher rates of smoking prior to the program

than the control schools. While the pattern of effects looks

promising, with the proportion of smokers actually decreasing in the

program schools and increasing in the control schools, it is

difficult to interpret; it could be due to expected patterns of

quitting by early starters as observed with grade 8 students in the

Waterloo study. In those schools where pretest levels were more

nearly equal, no significant program effects were observed.

Significant program effects on marijuana use was reported for only

one school pair--where there was a large pretest difference.

The Australian Study

Fisher et al. (1983) have tested the social influences approach to

smoking prevention in Western Australia. The Minnesota program

(Arkin et al. 1981) was modified only slightly, including the

remaking of film materials, for the Australian context and idiom.

The program was delivered to grade 7 students, one session every

month over the last 5 months of the Australian academic year (August

to December 1981). The study compared same-age peer- versus

teacher-led programs and controls. Both teachers and peer leaders

received special training for the program.

A total of 45 elementary schools were randomly assigned to the three

conditions after stratification on school size, geographical

location, and SES. Students were assessed with questionnaires and

saliva samples immediately prior to the program, and 1 year after the

end of the program (November 1982). The data collectors were blind

to the experimental condition of the students. By careful tracking,

82% of the initial sample were posttested, even though students had

made the transition from elementary to dispersed high schools during

the intervening year.

One-year followup results indicated that teacher- and peer-led

programs both reduced the onset of smoking among girls (26% of

pretest nonsmokers had smoked during the 12 months prior to posttest

in the two program groups compared to 35% for the control

'group--i.e., a 26% reduction in onset), but the effect was only

marginally significant for the peer-led curriculum after adjustment

for the effect of social risk factors. Only the teacher-led program

was effective for boys (19% in the teacher-led condition, compared to

36% in the peer-led condition and 31% of controls--i.e., 39%

reduction in onset). No program effects were observed for students

who had smoked during the 12 months prior to the program.

This study demonstrates that a social influences classroom curriculum

85
can, by itself, be effective in countries other than the United

States and Canada, at least in reducing onset by previous nonsmokers,

but raises questions about the superiority of peer leaders over adult

leaders. It appears that the use of peer leaders may sometimes not

be beneficial. Of course, cultural differences could explain this

finding--Australian adolescents may not identify as closely with

their peers as Americans do. It also seems that the peer leaders had

a greater responsibility for the entire program than same-age peer

leaders have had in any other study, and one must wonder how well

they were able to implement the program. Small pretest differences

between conditions in smoking prevalence (nonsignificant) cannot

explain the observed effects of the teacher-led programs, and a

multiple logistic regression analysis demonstrates that social risk

predictors of smoking (e.g., number of friends who smoke, response to

cigarette advertising, intentions) do not explain them either.

The Michigan Study

Dielman et al. (1984a, 1984b) tested the social influences approach

to smoking prevention on grades 5 and 6 students. The program

consisted of four sessions delivered by health educators on the

research staff. In addition, grade 5 students also received a

three-session booster in grade 6. In a controlled study, 10 schools

in Ann Arbor were formed into matched pairs on achievement scores,

ethnic distribution, and SES, and then randomly assigned to program,

control, or "mixed" conditions. In the mixed condition (two

schools), classrooms were randomly assigned to program or control

conditions. Signed consent was provided by 83% of the parents of

program students and 75% of parents of control students. Students

were assessed via questionnaire only (i.e., no biological samples

were collected or bogus pipeline procedures used) at pretest (March

1981), immediate posttest (June 1981), 4-month followup at the

beginning of the following academic year (October 1981), and l-year

followup (June, 1982). The health educators who delivered the

program were usually present at data collection in both program and

control schools. Approximately 80% of students were present at all

four measures.

By the second and third posttests, significiant effects were observed

on recent smoking. Reports of smoking in the last month increased

from 1% at pretest to 7% by the 4-month followup to 15% by the 1 -year

followup for control students, versus 4% to 1% to 8% by program

students. No effects were observed on intentions to smoke in the

future, or on the numbers of students who had ever tried smoking

cigarettes (increase from 30% at pretest to 50% at l-year followup

for both groups). Alcohol and marijuana intentions and behavior were

also measured, but no program effects were observed.

The lack of any biological sampling, plus the presence of the health

educators in the classroom during data collection, makes

interpretation of these data somewhat precarious, because both of

these factors can serve to increase the demands on program students

to underreport their smoking. However, the lack of any program

86
effects on either intentions or trying smoking suggests that these

alternative explanations of the reported findings may not be entirely

plausible. Because of the young age of the subjects, final

evaluation of this study requires long-term followup data.

The Oregon Study

At the Oregon Research Institute, Biglan et al. (in preparation)

tested a social influences program delivered/facilitated by classroom

teachers. The tested program consisted of three sessions delivered

on consecutive days with one booster session delivered about 2 weeks

later. Grades 7 and 9 classes of volunteer teachers in six middle

schools and three high schools were randomly assigned to program

(N=41) or control (N=45) (traditional health education) conditions.

Students were assessed by questionnaire and saliva sample at pretest,

6-month posttest, and 12-month posttest. Seventy-seven percent of

the initial students were present at the 6-month assessment and 68%

at the 12-month assessment. The questionnaire included innovative

measures of the proportion of cigarette offers refused during the

week prior to measurement. In addition, refusal skills were assessed

directly for a sample of students (Hops et al. 1984).

Despite random assignment, control students were significantly more

likely to have smoked prior to pretest. Accordingly, analyses of

covariance procedures were used in tests of program effects. At the

first posttest there were fewer regular smokers (at least weekly)

among the program than the control students (10% versus 14%). By the

l-year followup, however, this marginally significant difference had

disappeared (10% versus 11%). When only those students who were

smokers prior to pretest were considered, there was still a

significant program effect at 1-year posttest, but only for

relatively heavy daily smoking (more than 10 cigarettes every day).

Program effects were evident on both the questionnaire and behavioral

measures of use of refusal skills. Students present at pretest but

not at subsequent tests were more likely to be smokers and to have

parents who smoke. They also scored significantly higher on a scale

of deviant behaviors involving alcohol and marijuana use, and had

lower educational aspirations and less educated parents.

The small magnitude of effects on behavior in this study is somewhat

intriguing, given the demonstrated effects on presumed intervening

constructs. The assignment of classrooms could have reduced the

difference between treatment and control conditions, in that one of

the presumed effects of the social influences programs is thought to

be alteration of the norms for complete social environments. The

demonstrated differences between groups in the use of social

resistance skills reduces the plausibility of this Interpretation,

but does not remove it entirely. Other data that might throw light

on this issue have not yet been reported. Fairly serious attrition

also raises questions in that those students who were most likely to

become smokers were less likely to be present for followup

measurement

87

485-051 0 - 85 - 4
posttest differences even without an intervention.

The USC Television Smoking Project (TVSP)

At the University of Southern California, Flay et al. (1983b, 1983c,

1984) tested the social influences approach to smoking prevention

when implemented in a widespread way. Widespread implementation was

attained by the development of a series of television segments that

were coordinated with a 5-day classroom program. In addition,

parents were involved via homework activities; and a television

smoking cessation program was provided for smoking parents the week

following the prevention program. The prevention program consisted

of lessons on social influences to smoke, including peer pressure,

family modeling, and media influences; role-playing and practice of

social skills with which to resist those pressures; immediate

physiological and social consequences of smoking; and decision-making

skills and a commitment procedure. Teachers received a detailed

curriculum guide; all students received personal copies of an

activities booklet, the second half of which included self-help

smoking cessation materials for their parents; and peer leaders were

provided with their own special guide on group leadership skills.

This study was different from other fourth generation studies in that

it included quasi-experimental tests of teacher training and

"curriculum milieu." Four months prior to the program, and on the

basis of very little information, program schools requested the

program. Within each school district where not all schools had asked

to provide the program, comparable schools were selected and asked to

participate as control schools in the evaluation. Students in the 28

selected grade 7 control schools were at marginally greater risk to

becoming smokers than students in the 28, grade 7 program schools at

pretest. Program schools also decided whether to provide the program

to all or half of their grade 7 students (this variable has been

called "curriculum milieu"). This decision was based on school

district policy regarding whether students are provided with one or

two semesters of health education. All program schools were further

randomly assigned from matched pairs (on SES, school size,

geographical location, and the curriculum milieu variable) to receive

or not receive special training for the teachers who were to

implement the program. Once schools were selected for teacher

training, school principals selected one to three teachers to be

trained. Implementation evaluation data show that teachers selected

for training were different from teachers who implemented the program

in other schools --they were more likely to be science, rather than

health, teachers. Classes taught by these trained teachers were

also found to be different--students were more likely to be smokers,

and to have parents and friends who smoke--from classes taught by

untrained teachers. These differences were evidently caused by the

selection of more "problematic" classes by principals in schools that

were offered teacher training than' in schools that were not offered

teacher training. Students from three to six classrooms in each

program and control school were assessed by saliva sample and

questionnaire at pretest (January 1982), immediate posttest

(March/April 1982), and l-year followup (April 1983).

88
Implementation evaluation results (Flay et al. 1983c) showed that

trained teachers implemented the program more diligently and more

enthusiastically than untrained teachers. Students who received the

classroom program were much more likely to view the TV segments

(65%) than control students (10%), and participation by parents was

high (70% for program students). The program produced significant

immediate effects on student knowledge, attitudes, and social

normative beliefs. However, many of the effects had partially

decayed by l-year followup. Only slight program effects on behavior

were observed. Experimental smokers who viewed the TV segments and

whose parents participated in program activities were more likely to

quit smoking than control students (approximately 59% versus 40% in

preliminary analyses). Nonsmokers who viewed the TV segments and

whose parents participated in program activities were less likely to

start smoking than control students (approximately 15% versus 27%).

These effects, however, had also decayed somewhat by l-year followup.

Teacher training made a significant difference to the amount of

change in the above variables in the shortterm. Perhaps the greatest

effects on behavior were observed for smoking parents. Of smoking

parents of viewing students, approximately 45% viewed the cessation

programming, 30% attempted to quit or reduce, and 15% were not .

smoking at both l-month and l-year followup.

This study constitutes the first effectiveness trial of the social

influences approach to smoking prevention. An efficacious approach

was taken and implemented under real- world conditions, that is,

without strict monitoring to ensure even implementation, so that

issues of availability of the program to the target audience, and

acceptance of it by them, become important, as well as program

effectiveness. Results for students are not particularly encouraging

and, like the second and third generation studies, the primary

lessons concern hints for the improvement of future programming and

effectiveness trials of them. That is, this study might be

considered as no more than a prototype of future "fifth generation"

studies.

Summary of Fourth Generation Studies

The six fourth generation studies were mostly methodologically

superior to the third generation studies. The use of simpler and more

rigorous designs provided for greater internal validity and more

interpretable findings. Nevertheless, certain methodological problems

remain, and every one of these studies is still susceptible to one or

more plausible alternative interpretations. Some of the

methodological problems, such as difficulties in achieving complete

random assignment, problems with program implementation, and serious

attrition rates serve to remind us of the difficulties of

large-scale, school-based research.

Four of these studies (Stanford/Harvard, Michigan, Oregon, and TVSP)

suffer from more serious methodological problems than the others.

Ironically, they also reported less promising results in many ways.

The most rigorous studies, Waterloo and Australia, on the other hand,

89
provided the most encouraging results to date. The Waterloo study

reported the most comprehensive results, demonstrating effects for

students with different pretest experience and for different

transitions over time. Long-term results suggest reasonably good

maintenance of effects, though not total. The finding that the

program was most effective for students at high risk seems

particularly important, as it provides some validation of the theory

underlying the whole social influences approach to smoking

prevention. The Australian study, on the other hand, found program

effects only for students who had not smoked at all during the 12

months prior to pretest. The differences in the patterns of outcomes

provided by the two most rigorous studies have no obvious

explanation. Major differences between the programs that might

explain the differences in findings include:

a) the length and duration of the programs, with

the Waterloo program consisting of more sessions spread

over a longer time;

b) the structure of the school systems, where the Waterloo

students have not yet made a transition from elementary to

high school while the Australian students did so between

the program and the 1-year posttest;

c) program providers, with the Waterloo program using

college-age teachers/"peer leaders" and the successful

Australian program using teachers; and

d) length of followup, with the Australian study yet to report

long-term data.

On the basis of existing theory and assumptions, some of these

differences could be expected to lead to the observed differences

between the studies in their magnitude of impact. Differences in the

type of effect are less easily explained.

The Australian finding that the teacher-led program was most

effective is intriguing because the use of peer leaders has become

almost "institutionalized" among major prevention efforts (Flay et

al. 1983a; McAlister et al. 1980; McCaul and Glasgow 1984). Also,

both of the United States studies that relied on classroom teachers

to implement the program (Oregon and TVSP) found much smaller program

effects on behavior. They each also reported effects on intermediate

presumed mediating variables, however, such as knowledge, attitudes,

beliefs, social perceptions of norms, and intentions. The Oregon

study was even able to demonstrate improved social resistance skills

and increased use of those skills, something that other researchers

have yet to do. Both of these programs were very short, however,

with the Oregon program being only four sessions over 3-weeks and

TVSP being only five sessions over l-week. It is possible that the

training of behavioral skills requires a program of longer duration

if not more actual program time (the Australian program was also only

five sessions, but they were spread over 5-months).

Overall, the findings from the most rigorous studies to date suggest

that the social influences approach to smoking prevention can be

effective some of the time. However, this conclusion seems to be

90
somewhat fragile, given the considerable differences between studies

in the patterns of reported results. Also, at least two plausible

alternative interpretations of the reported effects remain--namely,

effects of testing (or screening), and the Hawthorne effect. It may

be that students who are tested and/or who receive special attention

in the classroom will be influenced to alter their behavior or their

reports of it. The likelihood of these processes causing the

observed effects is small, however, especially when one considers

that many tests of other approaches to smoking prevention have not

reported significant effects.

While the results of the fourth generation of studies support the

suggestion of second and third generation studies that the social

influences approach to smoking prevention is an efficacious approach,

further research is needed on the conditions under which the social

influences programs are effective, for whom they are effective, and

why they work. This theme will be addressed in the next section.

DISCUSSION

What Have We Learned From Past Studies?

Seventeen school-based studies of the social influences approach to

smoking prevention have been reviewed in this chapter. They were

divided into four "generations" of studies. The first generation

consisted of the two seminal studies of the Houston group. While the

results from these studies were not very encouraging, their

theoretical justification seemed compelling enough to encourage other

researchers to improve upon the approach and conduct further tests.

The second generation studies improved upon the approach, and the

third generation studies provided additional tests of these improved

programs. At this time, however, all of the second and third

generation studies can be considered as no more than pilot or

prototypical studies, although most of them were undoubtedly designed

with much loftier goals in mind. Our knowledge of whether the social

influences approach to smoking prevention is effective, or of the

conditions under which it might be effective, was not advanced by any

one of these studies when considered alone. Taken together, however,

fairly consistent results across studies, at least in the reported

magnitude of effects, provided encouragement that the approach might

be efficacious. However, the greater contribution of these studies

was improvement of our knowledge of program development and

methodological issues in school-based prevention research, though

this often was in subtle and largely undocumented ways. For example,

approaches to random assignment of large, aggregated units (schools)

to conditions, obtaining informed consent, tracking of individuals

over time, minimizing attrition, and measurement have been developed,

tested, and improved during the course of these studies. Indeed,

without these pilot/prototypical studies, the better controlled,

large-scale studies of the fourth generation probably would not have

been attempted.

The fourth generation of studies were more successful, though not

91
unfailingly so, at maximizing internal validity, and so they have

produced more interpretable findings. Those findings have been mixed,

however, and there seems to be a certain fragility to them. The

programs tested in the two most rigorous studies had certain elements

in common that might inform us of crucial components. They both

included:

(a) media material, with similar-age peers, derived from the

original Houston program;

(b) role-playing and explicit learning of behavioral skills;

(c) information on immediate physiological effects of smoking,

(d) a public commitment procedure;

(e) correction of misperceptions about the prevalence of

smoking;

(f) discussion of family and media influences on smoking, and

ways of dealing with them; and

(g) an extended duration.

While this list of common elements is suggestive, we really know very

little at this time, either from these studies or others, about which

of these program components are necessary for program effectiveness,

or how other components (e.g., health information) or methods (e.g.,

use of peer leaders) might or might not add to program effectiveness.

Johnson (1982) and McCaul and Glasgow (1984) have reached similar

conclusions. It was not inappropriate, however, for fourth

generation studies to have been concerned with determining whether

the approach works at all before exploring further the who, why, how,

what, and when questions. Indeed, the early attempts to explore some

of these questions in the second and third generation studies now

seem somewhat premature, though it is as well to remember that at

that time they would have seemed most appropriate to psychological

researchers who had little experience with large-scale field trials

and all the methodological traps they entail (see Biglan and Ary,

this volume; Flay et al. 1983a).

We also know very little from all the studies reviewed about the

generalizability of their findings. The most rigorous studies were

conducted on white, middle-class, WASP populations, in countries with

slightly more "authoritarian" child-rearing norms than the United

States. We still do not know for sure, then, whether the approach is

effective in the United States for various SES and ethnic groups

(several ongoing studies do address these issues). Two of the

studies (Waterloo and Stanford/Harvard) hinted at large

between-school variations, but we know nothing as yet about the types

of schools in which these programs will be more or less effective

(though studies now underway are also investigating this issue).

We also know relatively little as yet about the types of students for

when the social influences approach is most effective. Most studies

have not performed separate analyses by sex, grade, or other

characteristics of the study participants. Where such analyses have

been done, differences have sometimes been found (e.g., Hurd et al.

1980). Results from the Australian study suggest that males and

females are equally influenced by a teacher-led program, but that

92
they may be differentially influenced by a peer-led program. The

Waterloo investigators analyzed program effects by both pretest

experience with smoking and social risk to becoming smokers. The

results suggested that (a) the program had its initial effects on

those experienced with smoking, influencing pretest never smokers

only in the longer term, and (b) the approach is most effective for

those students at greatest risk to becoming smokers because of social

factors. These findings need replicating, and we also need to

investigate the effectiveness of this approach for students who may

be at risk for other reasons (cf, Leventhal and Cleary 1980; Flay et

al. 1983a).

Another area that past research has not yet addressed sufficiently

concerns broader issues of program dissemination. Once we have an

efficacious program, how will it be disseminated broadly? Should

regular teachers be trained? Trained how? Or would some other

group, such as school nurses or health agency volunteers, be more

effective? What is the potential role of media, both small and mass?

All such questions remain for research to answer.

To summarize, the fourth generation studies have confirmed the

suggestion by second and third generation studies that the social

influences approach to smoking prevention can be effective. We know

very little at this point, however, about the construct validity or

generalizability of the treatment.

Directions for Future Research

Having established from four generations of research that the social

influences approach to smoking prevention can be effective on some

adolescents some of the time, what is the most appropriate next step?

Should we immediately go out and implement the approach in a

widespread way? This seems unwise, because we know so little about

what works, why, when, how, and for whom. Large-scale implementation

would, therefore, run the risk of failure. Not every school district

implements a new curriculum exactly as recommended, and without

knowledge of the crucial components and conditions, any changes could

result in failure. Widespread failure could devastate the prevention

research field. Knowledge of the crucial components and conditions

would allow variations that would be less likely to fail. Therefore,

the focus for the fifth generation of research should be on the

construct validity and generalizability of the treatment--that is, on

the who, what, when, where, how, and why questions alluded to above.

Obviously, however, focusing on issues of the construct validity and

generalizability of the treatment cannot be at the neglect of

internal validity. Indeed, internal validity is desirable for

answers to construct validity questions to be intrepretable (this is

the reason that the complex designs of some of the second and third

generation studies produced uninterpretable results). Even

generalizability questions are more easily interpreted when internal

validity has been maximized, although high external validity is also

required.

93
Construct validity of the treatment concerns the questions of whether

the various components of a program have the immediate effects

expected of them, and whether or not any immediate effects on

presumed mediating variables are related to subsequent smoking

behavior. Very few of the reviewed studies even reported program

effects on presumed mediating variables (see review by McCaul and

Glasgow 1984), and none made any attempt to link any such changes' to

subsequent smoking behavior.

Three major approaches to research on the construct validity of

smoking prevention programs are available They are as follows:

1. Extensive process evaluation of large-scale studies like those of

the fourth generation, where data are collected on program effects

on presumed mediating variables. Each component of a program is

designed to produce a particular effect, and it is the combination

of all those effects that should prevent smoking. As noted above,

too few of the studies reviewed have even collected data on

intervening variables, and none of them have linked changes in

those variables to subsequent smoking behavior. Future

large-scale studies need to include measures of as many of these

immediate and mediating effects as possible in addition to

measuring the final behavioral outcomes.

2. Small-scale, tightly controlled experimental studies of the

short-term effects of program components. These would preferably

be with children from the target group, but analogue laboratory

studies may sometimes be worthwhile. Only a few small-scale

experimental studies, namely those by students of the Houston

group (e.g., Hansen 1978; Hill 1979; Mittlemark 1978) and the

North Dakota group (Glasgow et al. 1981; McCaul et al. 1983;

O'Neill et al. 1983) have tested some of the components of social

influences smoking prevention programs as to their effects on

presumed mediating variables. These types of studies could be of

value in establishing that program components produce their

hypothesized effects on variables presumed to mediate smoking

intentions and behavior; however, results from the two groups of

studies conducted to date have not been very promising.

3. Experimental comparisons of programs derived from competing

theoretical positions in large-scale field trials that include

measurement of target population acceptance and characteristics,

and program effects on mediating variables. Successful smoking

prevention programs have now been, or soon will be, developed from

competing theoretical perspectives. This is a healthy sign for a

science of prevention. Programs developed from competing

theoretical perspectives will need to be pitted against one

another, not as tests of the competing theories, but with an eye

to determining which approaches, or which combination of

approaches, are most effective for which types of people, under

what conditions.

Generalizability concerns the transferability of an effective

program--for whom is it effective and under what conditions of

94
implementation/dissemination? Such questions can be addressed in

studies of types 1 and 3 above, as well as though two other

approaches:

4. Experimental studies of approaches to program dissemination.

Most studies of the efficacy of the social Influences approach to

smoking prevention have involved the program being provided or

facilitated by research project staff. Such arrangements

obviously will not be possible under most real-world conditions.

So questions of who should provide the program (teachers, school

nurses, health agency volunteers, other public health personnel),

how they should be trained, the role of media (both small and

mass), and the role of auxiliary programming (e.g., other

interventions on the school environment, such as changes in

regulations or disciplinary procedures regarding smoking, and

smoking cessation programs for teachers and/or parents), will all

need to be investigated. The TVSP project from USC provides one

early example of this type of study. Others are already in

progress.

5. Evaluation of large-scale demonstration projects that include

measurement of population characteristics as well as program

effects on presumed mediating variables. Once efficacious

approaches to smoking prevention are implemented on a wide scale,

evaluation needs to include assessment of availability to the

target population (or program implementation), acceptance of the

program by the target audience (or involvement in program

activities), characteristics of the treated population, and

program effects on presumed mediating variables, as well as

outcomes.

How do we choose between the five types of research suggested above?

Should we conduct further large-scale research or should we confine

ourselves to tightly controlled, small-scale, laboratory-style

studies to answer questions of treatment construct validity? Tightly

controlled, small-scale studies can inform about whether or not

program components have the desired effects on presumed mediating

variables, why or how the programs have the effects they do, and the

program components that are most crucial. Such knowledge is

necessary, and small-scale studies are less costly, more easily

controlled, and of short duration. However, they are of low external

validity, can miss important complex interactions (McGuire 1973,

1983). and the end-point dependent variable usually cannot be smoking

behavior. In addition, the small-scale, components analysis approach

has not proven to be very useful so far, just as it has not in

educational or smoking cessation research (Lando 1981).

Large-scale studies, on the other hand, can be of long duration,

costly, and entail certain methodological problems (see Biglan and

Ary, this volume). However, the methodological problems are rapidly

being reduced (see Cook, this volume), smoking behavior is the

end-point, and such studies are necessary for assessing

generalizability, determining whether program components still have

their presumed effects on mediating variables in real-world settings,

95
testing variations in dissemination variables, and comparing

different programs derived from competing theoretical perspectives.

Large-scale studies are also necessary for testing components by

removing them one-by-one from an efficacious combination--an approach

to components testing with more promise than small-scale studies of

one component at a time. Large-scale studies also allow for the

investigation of multivariate interactions. Even extremely

large-scale studies, like evaluations of state-wide or national

models, can provide valuable information on which models work best

under which conditions.

The results of four generations of studies on the social influences

approach to smoking prevention are consistent enough to suggest that

large-scale studies be employed to answer questions of the construct

validity and generalizability of the approach. In addition, given

that the review or synthesis, rather than the individual study, is

the unit of advancement of knowledge, the sooner a large number of

studies are accumulated, the more certain will be our knowledge.

The conclusions reached above have several implications for future

research. First, future studies need to be of the highest level of

internal validity. The fourth generation studies have demonstrated

that we now have the capability of conducting large-scale studies of

high internal validity, though not without great difficulty. Without

high internal validity, answers to questions of treatment construct

validity will be uninterpretable.

Second, future large-scale studies need to include assessments of

program implementation (including characteristics of the provider)

and availability to the presumed target audience. Many current

studies are already doing this, but much work will be needed to

develop rigorous methods. Such assessment is needed to determine the

integrity and strength of a program as actually delivered (Sechrest

et al. 1979). Without such information, variations in the level of

program impact reported by different studies will not be

interpretable: they may be due to inadequate delivery and we would

never know it.

Third, all future studies need to include comprehensive assessment of

presumed mediating variables. Most ongoing studies of which we are

aware are already improving the process evaluation component, but

much attention will need to be paid to the selection and development

of high-quality measures of presumed mediating variables. Results

from future research, particularly negative or no difference results,

will be uninterpretable without highly valid measures of the presumed

mediating variables, such as social normative beliefs, self-efficacy,

resistance skills, and intentions, as well as outcome variables such

as smoking behavior. Without such information, questions about

program components cannot be answered. With such information,

recently developed analytic approaches (e.g., Judd and Kenny 1981)

can be used to investigate causal linkages between the presumed

mediating variables and subsequent smoking behavior.

Fourth, future large-scale studies need also to include comprehensive

96
measurement of target audience involvement (or acceptance),

characteristics of the treated audience (i.e., individual

differences), and properties of the social environment (family,

classroom, school, community) inhabited by the target audience.

Without such information, questions about generalizability cannot be

answered. Effort needs to be spent, therefore, in developing

measures of audience and social environment characteristics with good

psychometric properties and high construct validity.

To summarize, future studies need not focus exclusively on whether or

not the social influences approach to smoking prevention can be

effective. Rather, future research needs to focus on:

(a) determining those program components that are important for

program efficacy;

(b) establishing the conditions under which programs are most

effective;

(c) determining for whom the programs are most helpful; and

(d) investigating alternative approaches to disseminating

successful programs.

In addition, comparisons of programs derived from competing

theoretical perspectives will soon become important. These research

objectives will best be accomplished by the use of five types of

large-scale field trials. The five types of studies go hand-in-hand,

with results from each type (re)validating findings from the others.

All future large-scale studies need to:

(a) be of the highest internal validity;

(b) include comprehensive measures of presumed mediating

variables; and

(c) include comprehensive measures of (i) program implementation,

(ii) involvement by the target audience, and (iii) population

characteristics.

Meeting all these conditions will ensure the development of a true

science of prevention and maximize the probability of developing

effective prevention programs.

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101
TABLE 1

Characteristics of Tested Social Influence Programs
TABLE 1 (con't.)

NOTES: a)

b)

c)

d)

e)

f )

g)

h)

i )

j)

Number of sessions and duration varied by experimental condition.

These studies included tests of use versus no use of peer leaders.

This study compared a 5-session, teacher-led program with a 10-session research staff-led program.

These studies Included comparison of two types of program provider.

Six were sessionsdelivered weekly at beginning of grade 6, 2 booster sessions at end of grade 6,

2 maintenance sessions at beginning of grade 7, and 1 at beqinning of grade 8.

Program providers were Master's students who deliberately "underdressed" so as to identify as

closely as possible with participants.

Provided largely by high school students with project staff providing supervision.

Grade 6 students received 4 sessions over 8 weeks: grade 5 students received an additional 3

booster sessions during the second year.

One week of prevention and 1 week of cessation for parents.

Commercial TV segments coordinated wrth the classroom program.
TABLE 2

Methodological Characteristics of Studies
TABLE 2 (con't.)
NOTES: a)

b)

c)

d)

e)

f )

g)

h)

TABLE 2 (con't.)

S = school, C = classroom within school.

N = no, Y = Yes, NR = not reported (cannot determine from report).

From core or major program.

A few studies did not collect unique individual identification codes, and so were unable to track

Individual students over time.

N = no significant attrition, Y = severe attrition, NR = details not reported.

Numbers signify total attrition by the latest reported followup.

S = saliva, B = breath, Se = serum, N = None.

Two schools assigned nonrandomly to each condition; classrooms assigned randomly

to all four conditions in two other schools.

7 schools initially assigned nonrandomly to six conditioner in total 13

schools assigned to 7 conditions.
i )

j )

k)

1)

m)

n)

o)

p)

q)

r)

s)

t)

u)

vI

w)

One school assigned to each of two P and two C conditions; then classrooms within one

P school randomly assigned to the commitment procedure.

Intensive = 10 sessions provided by project staff in two schools randomly selected

from N. Karalia.

County-wide = 5

from N. Karalia.

sessions provided by teacher in two schools also randomly selected

Controls in two comparable schools selected from another county.

Four yoked pairs of schools (one high- and one low-level of smoking) were

randomly assigned to four cells.

This test provided by a conceptual replication in the same schools in the second year,

in which teachers, rather than project staff, provided the program.

In the first year, "historical

controls were used.

controls" were used. In the second year, non-equivalent

From matched pairs: Two out of three pairs were randomly assigned.

Small differences only, not in smokinq behavior, and in opposite directions on different variables.

20 classrooms in 4 schools randomly

assigned to teacher-led vs peer-led

assigned to type of program, then schools randomly

One yoked pair randomly assiqned to each proqram x personalization condition; then classrooms

within P schools assigned (by policy) to P or C: then P classrooms randomlv assiqned to adult

vs peer leaders.

Prom matched pairs; 8 out of 11 pairs were randomly assigned.

Randomly assigned from matched pairs. Pretest differences in those pairs where program effects were found.

Student generated

Estimated by school administrators

Random assignment to P,C, & "mixed.' Within mixed schools, classrooms were randomly

assigned to P or C conditions.

schools selected themselves to participate in the program. Comparable schools were selected

from within the same districts for controls. Within proqram schools, some provide proqrams

to all students, some to half. Within program schools, half were randomly assigned to having

their teachers especially trained. Schools selected three to six classrooms to participate in

the study. Pretest differences between trained and untrained conditions are throught to be due

to the selection of "problem" classes by school personnel when training was provided.
TABLE 3

Summary of Findings and Plausible Alternative Interpretations

STUDY

FIRST GENERATION

Reported Finding: Plausible Interpretation:

Houston I Program cut nonsmoking to smoking transition

by 50% compared to minimal testing only.

Program not different from intensive measurement

conditions.

Houston II Small effects on pretest never smokers.

Correlation between posttest knowledge and

behavior.

SECOND GENERATION

CLASP Program cut smoking prevalence by 67%.

RASP Social programs reduced onset of ever

smoking in short-term; but only peer-led

social program effective at l-year, with

some decay by 2 years.

THIRD GENERATION

N. Karella Program cut prevalence in regular smoking

by 30% (boys only).

No differences between intensive and countywide conditions.

Breakdown of design.

Attrition.

Inability to track etudents.

Reliance on cross-sectional analyses.

Large pretest differences (program provided in

"problem" school).

Inability to track students.

Incomplete data reported.

Pretest differences in social risk factors perfectly

confounded with hypothesized treatment strength.

Pretest differences in smoking prevalence.

Peer leadership confounded with familiarity of actors

in media materials.

Serious attrition.

Program was small component of a more intensive

intervention in N. Karelia.

School selection.
TABLE 3 (con’t.)

STUDY Reported Finding: Plausible Interpretation:

PCSC No significant effects at immediate posttest. Pretest differences in smoking prevalence (peer-led

Social program more effective when peer group different from others).

leaders used. No pretest data reported for Study II.

Peer-led social program most effective at Historical and non-equivalent controls used.

preventing onset by pretest nonsmokers. Serious attrition.

No significant effects on pretest smokers. Incomplete data reported.

Oslo Progran cut nonsmoking to smoking transition

by 39%.

Program was small component of a more comprehensive

curriculum.

Pretest differences in knowledge, attitudes, and alcohol

use (but not smoking).

Differential attrition.

Current Cut prevalence of smoking in the last week Program was component of an inteneive community-based

Minnesota by 38%. intervention.

Inadequate data reported (as yet).

Stanford High I Program effects on pretest nonsmokers at

4 months. I

(No long-term data.)

Stanford High II No significant differences between social, Inadequate data reported.

health, and physiological programs.

(Teachers better with health programs;

college students better with social program.)

HASP Health program marginally superior at

preventing transition from never smoked

to smoked.

Severe attrition

Inadequate data reported (as yet).

Social program cut transition from experimental

to regular smoking by about 50%.
TABLE 3 (con't.)

STUDY

FOURTH GENERATION

Reported Finding: Plausible Interpretation:

Waterloo Significant effects on knowledge.

Significant effects on cross-sectional

prevalence of never smoking, quitters,

tried oncers, and experimenters (e.g.,

cut experimental smoking by 43% at

grade 8).

Significant effects on transitions from

nonsmoking to trying, tried once to quit

or experimenting, and experimenting to

quit.

Even greater effects on students at high

social risk (e.g., reduced never smoker

transitions to trying by 58%, to

experimental smoking by 85%, and to regular

smoking by 100%).

Stanford/

Harvard

No significant effects on prevalence of

regular smoking.

(Significant effects in two pairs of

schools only.)

Australia

Michigan

Both teacher- and peer-led programs cut

nonsmokers to smoker transition by 26%

for girls.

Only teacher-led program cut same transition

for boys (39%).

Effects still significant after adjustments

for pretest number of friends smoking,

responses to cigarette ads, and intentions.

Cut prevalence of experimenta

No effects on ever smoked or

1 smoking by

ntentions.

47%.

Not total randomization.

Measurement by treatment interaction*

Hawthorne effect**

Large pretest differences in the two pairs of schools

where program effects were observed.

Serious attrition

Inadequate data reported (as yet),

Hawthorne effect**

(No long-term data yet)

Measurement by treatment interaction*

Lack of biological validation of self-reports.
TABLE 3 (con’t.)

STUDY Reported Finding: Plausible Interpretation:

Oragon Temporary cut in prevalence of smoking (29%). Serious attrition.

No significant effects for pretest nonsmokers Assignment of classrooms within echoola (possible

by 1 year. contamination).

For pretest smokers, significant cut in

transition to daily smoking.

Significant effects on questionnaire and

behavioral measures of use of social

resistance skills.

Inadequate data reported (as yet).

TVSP Important implementation evaluation data.

Significant, but temporary, changes in

knowledge, attitudes, and social normative

beliefs.

Minimal effects on student behavior.

Large effect on parental smoking.

Serious attrition.

Differential implementation

Nonrandom assignment.

No validation of parent behavior.

Inadequate data reported (as yet).

NOTES: *Most studies are susceptible to measurement by treatment interactions in that students often know of the

association between program and testing activities. This alternative is clearly minimized only in the

Australian study.

**All studies that have reported effects to date are susceptible to this alternative interpretation. The

only studies to guard against the Hawthorne effect(e.g., Stanford High II) found no differences between

programs.
AUTHOR

Brian Flay, Ph.D.

John Stauffer Pharmacology

Sciences Center

Health Behavior Research Institute

University of Southern California

1985 Zonal Avenue

Los Angeles, California 90033

112
The Social Influences Approach to

Smoking Prevention and Progress

Toward an Integrated Smoking

Elimination Strategy: A Critical

Commentary

Harry A. Lando, Ph.D.

I should clearly state my biases at the outset of this chapter.

First, I am not essentially a prevention researcher. I have

spent approximately 15 years researching smoking cessaiton

methods. When first introduced to prevention research at a small

group meeting, I felt that I had stumbled into a foreign country.

That feeling has abated wlth increasing exposure, but there are

still times when I perceive myself to have only a “weak grasp" of

the language.

Thus, in considering this review of the social influence approach

(Flay, this volume) and my more general observations concerning

smoking prevention, it must be remembered that I am coming from

something of an outside perspective. My background is in

smoking cessation so I will make some evaluative comments and

recommendations based upon my experiences in that area.

Essentially, I see myself as a consumer of the prevention

research. As such, my major interest is in determining

techniques that I can take back with me to Iowa. In addition, as

a cessation researcher, I am especially alert to the possible

cessation effects of prevention programming and to the preventive

effects of cessation interventlons.

METHODOLOGlCAL CONCERNS

In evaluating methodological issues and flaws in the social

influence area, and more generally in prevention, I cannot help

remembering the early work in cessation. Even what Brian Flay

terms the “first generation" work of Evans and his col leagues is

considerably superior to early cessation methodology. This is

not to deny the concerns that Dr. Flay so cogently discusses, but

rather to indicate again my different perspective. By the

standards of much of the cessation work, prevention studies have

achieved high levels of methodological rigor.

I am encouraged by the improvement that has occurred in the

cessation field during the past 15 years and suspect that

considerable improvement will occur in prevention methodology

113
during the next 15 years. Prevention studies cited in this

monograph tend to be quite new, with a substantlal number

published in the 1980s. Cessatlon interventions have a somewhat

longer history. Bernstein’s seminal review and critique was

published in 1969 and helped to set the tone for much of the

research conducted subsequently. Bluntly stated, the

representative study cited in Bernstein’s review had no

intervention, no controls, no standardlzatlon, no validation, and

no followup (the latter point is essentially moot because most

studies also had no impact, at least beyond the first 1 or 2

months).

In considering methodological issues in smoking prevention, I

will also want to draw upon my background as a grant reviewer.

Many of the methodological issues I will mention have been very

important in the evaluation of research proposals.

One major concern relates to the approprlate unit of analysis.

Cook (this volume) has argued for the smallest unit commensurate

with assignment to condition that will maintain validity.

Certainly, this argument has important implications from a cost

perspective. Prevention researchers have sometimes opted for

schools rather than individuals or classrooms as the unit of

analysis (occasionally entire school districts have been randomly

assigned). In Flay’s grouplng of studies, those that he refers

to as thfrd generation, have in particular focused upon schools

as the unit and use a larger sample base.

In addition to cost, random assignment of schools can pose other

problems. There is no guarantee, for example, that events unique

to a particular school mlght not substantially influence

treatment outcome (although this problem can be minimized by

recruiting large numbers of schools to conditions). However, if

classrooms or certainly if individuals are used as the unit of

analysis, possible contamination of treatment effects can become

a major issue. Surely, individuals within classrooms cannot be

viewed as independent unfts. Analytical designs that focus upon

the individual without regard to possible classroom effects are

obviously problematic.

The case for contamination at the classroom level appears less

straightforward. It has been argued that treatment content may

be disseminated from experimental to control classes within the

same school . However, the case for such contamination is not

clear at this time. Careful process analyses are needed (see

below) to assess possible diffuslon of treatment content across

cl assrooms. A related concern of prevention researchers is that

introduction of treatment can lead to general changes in norms

for an entire school. This concern is especially relevant in the

context of social influence approaches. Careful component

analysis could again shed light upon possible overall normative

changes resulting from the introduction of prevention programming

into selected classrooms.

114
If process analyses fall to indicate major contamination effects

either in modeling of treatment interventions or in changes in

social norms, future studies can focus upon unlts at the

cl assroom level. Not only will this permlt more cost-efficient

data collection, but it should permit researchers lacking access

to large urban populations to conduct meaningful studies. In any

event, researchers must present clear Justification for their

choice of unit of analysls. Statistical power calculations must

then be consistent with this choice of unit (e.g., previous

investigators have sometimes opted for the classroom as the unit

and then computed statistical power on the basis of total numbers

of students).

Problems have sometimes been encountered in random assignment to

condition. School principals occasionally refuse a designation

of nontreatment control. Classroom teachers may resent being

denied active programmlng that is available elsewhere in their

school. Obviously, deviations from random (or matched)

assignment due either to refusal of control procedures or

deliberate introduction of “bootlegged” prevention material in

control classrooms can significantly reduce interpretability of

results.

Possible reactivity effects of repeated measurement have often

been ignored. Evans and his colleagues (1978, 1981) found

evidence of such effects in their initial research. Al though

these effects have not been observed consistently, research

designs should consider repeated measures controls. Certainly,

administration of extensive questionnaire and saliva samples on

an annual or semiannual basis could in itself produce a

significant impact (O’Rourke 1980).

Another major concern relates to long-term tracking of subjects.

Too of ten “dropouts” are slmply discarded from data analysis.

Grant applicants sometimes budget sufficient statistical power to

detect anticipated treatment effects even in the face of losses

of 50%, 75%, or more of their original subject population.

Unfortunately, this ignores the lilkelihood that the remaining

subjects are not an adequate representation of the total target

population.

Investigators may find themselves in somewhat of a “Catch-22”

situation. Failure to include long-term followups can seriously

limit the interpretability of study results. On the other hand,

incorporation of long-term followup periods may raise issues of

unacceptable rates of subject loss and lack of generalizability

to the entire subject sample. The problem is further complicated

when children are followed through transitions in school

attendance, e.g., junior high school to senior high school.

Subjects from previous experimental and control conditions may

blend into new classrooms. This could present an additional

source of contamination, especially in studfes in which

additional booster content is to be presented.

115
Dropouts, whether simply absent from measurement, nonparticipants

in studies, or individuals who leave school, tend to be at higher

risk for smoking (Schinke et al., in press). Such individuals

should be included in data analysis to allow an estimate of

overall treatment impact. Procedures for tracking study

participants require considerable improvement. Random sampling

of dropouts or nonparticipants mlght allow more meaningful

evaluatlon of prevention programs. One advantage of smaller

scale studies might be that they can facilitate greater attention

to the tracking of individual students (cf. Biglan, this volume).

CURRENT ISSUES IN ASSESSING PREVENTION PROGRAMS

Previous reporting of outcome data has often been selective.

Thus, results for certain categories of subjects (e.g., smokers

at study onset) are sometimes ignored. Flay (this volume) has

argued that it is essential to include complete data for all

subjects. Surely it is possible that treatment effects can

interact with previous smoklng status. Failure to consider

smoking status of all categories of subjects risks the loss of

valuable information.

One of the most intriguing sets of findings to date came from the

Waterloo Smoking Prevention Program (Best et al., in press; Flay

et al. 1983a, in press). This project demonstrated greater

immediate effects with adolescents who were already experienced

smokers and more substantial later effects with individuals who

had little or no smoklng experience at pretest. Especially

encouraging is the fact that the experimental intervention had

its largest impact upon adolescents classified as high risk.

Additional research is needed concerning the predictive

significance of various categories of smoking. How likely is the

occasional smoker to proceed to habitual use? Over what period

of time? Obvlousiy, published data are already available

concerning both these points (cf. Glynn, this volume). However,

further work detailing the natural progression of smoking onset,

both with and without special prevention curricula, could prove

extremely informative.

The profile of the hlgh-risk individual must also be more sharply

defined. Some predisposing factors already appear evident from a

number of studies. Thus, individuals whose parents and/or older

siblings smoke are at higher risk for smoking onset, as are

individuals whose scholastic record tends to be poor, who have a

high rate of absenteeism , or who drop out altogether.

An instrument that could provide approprlate weighting

of potential risk factors for smoklng and other drug use is

needed. Assignment of individuals to high-risk categories is

somewhat intuitive at present. Although certain risk factors are

known, other potential predictors of smoking require further

study. Precise weighting of diverse relevant factors in

establishing a composite indicator of risk does not appear

116
feasible based upon

further research.

current knowledge and should be a goal of

The majority of stud ies reported to date have been heavily

weighted with subjects who are white and middle class.

Generalizability to lower socioeconomic and minority populations

is probably tenuous. Assessment of existing interventions with

high-risk populations is clearly needed. Approaches that prove

effective with relatively advantaged subjects may have little

applicability in urban ghetto environments.

In addition to being heavily biased toward white middle-class

populations, subjects have been drawn disproportionately from

urban areas. Additional programming has sometimes occurred

simultaneously in the same communities (cf. Vartiainen et al.

1983). This severely limits interpretability of results.

Furthermore, some populations may be sufficiently atypical that

serious questions must be raised concerning generalizability of

results.

Thus, the Southern California population studied by Flay and his

coworkers at the University of Southern California may not be

fully representative of the rest of the country. This population

has been shown to have a higher level of mobility than the

population of other areas. Furthermore, it is possible that

prior intervention in the Los Angeles school systems (and

delivery of prevention/cessation programs through the media

enlisting such highly credible sources as Dr. Art Ulene) have

affected this population (cf. Johnson et al. 1984). Flay and his

colleagues present an impressive account of their success in

reaching a mass audience through five-minute segments on the

evening news of a major commercial television station (Flay et

al., 1983c). The combination of televised smoking prevention and

cessation programs together with extensive and repeated

intervention in large numbers of Los Angeles area schools

conceivably could have had some cumulative effect upon normative

standards and expectations.

I am surprised that more research has not focused upon critical

ages for intervention. Work from a social influences orientation

has been reported with students from fifth grade through high

school. Much attention has been devoted to individuals at the

seventh grade level. Yet, this may be quite late for

interventions that are designed to reach high-risk subjects.

Many high-risk individuals will already have had considerable

experience with smoking (Ary et al. 1983). My suspicion is that

a more intensive long-term program of intervention will be

necessary. Such a program might commence in the thlrd grade and

continue through high school. Cognitive-developmental

considerations will be extremely important in tailoring material

to divergent age groups.

Another area that requires far more research attention i S

prevent on of forms of tobacco use other than cigarette smoking.

117
Smokeless tobacco is heavily promoted on television and in other

media. In contrast to patterns of cigarette consumption among

adolescents, use of other tobacco products is accelerating

sharply. For many adolescents (and even elementary school

students) a new status symbol is the distinctive round spot

identifiable on the back pockets of jeans from carrying tins of

tobacco. Some bubble gum manufacturers have begun to exploit

this trend by selling bubble gum packaged to resemble chewing

tobacco.

Use of smokeless tobacco products in itself is far from

innocuous. Long-term effects can range from relatively minor

dental problems to oral cancer. Of even greater concern may be

the possible role of smokeless tobacco in recruiting youth to

both cigarette smoking and to other forms of drug abuse.

Possible incremental effects of booster sessions is also an area

that requires further study. Certainly, from an intultlve

standpoint it is reasonable to follow initial programming with

booster content at later grade levels. This intuitive

supposition is consistent with data indicating that tobacco use

tends to accelerate over time even in those populations exposed

to earlier prevention efforts (Botvin et al. 1984; Flay et al.

1983a; McAlister et al. 1980). Again, booster programming should

be modified to reflect the subjects’ developmental level and

increased maturity. Some of the most promising results for

booster intervention have been reported by Botvin and his

colleagues. It must be noted, however, that if booster sessions

cannot be demonstrated to produce significant incremental impact,

principles of parslmony and cost-effectiveness considerations

would argue against their use.

Questions may be raised concerning the comprehensiveness of

social influence programming. Approaches that are limited to

inoculation strategies and resistance to persuaslon may have

limited impact. This type of programming falls to address those

adolescents who view smoking as a sign of sophistication, as a

desirable risk, or as a form of rebellion.

In practice, however, social influence interventions do not

appear to suffer these types of limitations. In fact,

differences between social influence and social skills approaches

may be relatively minor. Although social skills training as

applied by Botvln and others would appear to have a broader

scope, treatments derived from social influence models

increasingly include such interventions as assertiveness

training. Furthermore, in being taught awareness of conformity

pressures and strategies to counteract such pressures, subjects

are also learning important social skills.

Both social influence and social skills interventions teach

methods of refusing cigarette offers. Both consider other

options and suggest that students actively generate alternatives

to tobacco use. Flay has suggested that the natural

118
rebelliousness of adolescents can be rechanneled into rebelling

agalnst influences to smoke. He and his colleagues have also

included programmfng in which students analyze cigarette

advertising and counter implicit messages of sexuality and

sophistication. The importance of conformity pressures and the

potentlal value of this programmlng is underscored by findings

that adolescents overwhelmingly choose a specific brand of

cigarettes (McCarthy, this volume).

Thus differences between social influence and social skills

training do not appear very substantial in practice. This is

especially evident in reviewing protocols constructed by Flay and

his colleagues at the University of Southern California and by

Botvin and his colleagues at Cornell. Furthermore, the role and

effectiveness of some components that may serve to distinguish

social influence and social skills approaches are questionnable.

Relaxation training and other anxiety management strategies have

tended not to show positive results for either cessation or

prevention (cf. Glasgow, in this volume). Eliminating

ineffective components of social skills training and adding

coping skills to social influence interventions (as the USC

group has done) could lead to very similar interventfons.

I also suspect that both social influences and social skills

tralning can be applied either narrowly to tobacco use or more

broadly to a number of areas. Work by the USC group (Hansen et

al., in press; Johnson et al. 1981), by Schinke (cf. Schinke and

Gilchrist 19841, and by Botvin (Botvin et al. 1984) has already

suggested the potential generalizability of prevention training.

The extent to which treatment will generalize to other forms of

substance use and/or healthy lifestyle patterns is clearly an

empirical issue. Two relevant questions are: How much natural

generalization occurs in programs explicitly oriented toward

tobacco? Can this generalization process be significantly

enhanced by specific programmlng?

In considering inclusion of other types of programming in tobacco

prevention programs, can such material be included without

detracting from effectiveness in combating smoking? A major

issue and concern taken from the cessation literature involves

the need to avoid excessive program content. Overly inclusive or

detailed interventions whether exclusively targeted toward

tobacco use or more broadly oriented toward lifestyle

modification may lead to reduced comprehension, lowered retention

of information and skills, and less adherence to treatment.

Attentlon must also be devoted to selection of optimal group

leaders and program providers. Previous results tend to support

the effectiveness of peers as group leaders, although

inconsistent findings have been reported (Fisher et al. 1983).

At this point it is not clear how regular classroom teachers fare

in comparison to trained health education personnel. Components

of effective training programs for both group leaders and program

providers need to be specified.

119

485-051 0 - 85 - 5
DISCUSSION

Flay’s organization of social influence studies by generatlons is

a useful aid to understanding both the overall scope of research

and improvements in methodology. His emphasis upon such

methodological shortcomings as data by treatment interactions and

Hawthorne effects is welltaken. However, it should be emphasized

that such shortcomings are by no means unique to the prevention

area.

Overall, in reviewing studies of social influence approaches to

prevention, one is impressed by the general consistency of the

findings. Obviously (as noted by Flay) a common flaw in all of

these studies could invalidate this trend; however, the pattern

of results appears distinctly positive. The Water loo project

(Flay et al., in press) in particular is noteworthy both in its

methodological rigor and in its finding of a more pronounced

treatment effect for subjects seen as high risk.

Flay has concluded that our knowledge from previous social

influence studies is limited. First and second generation

studies suffered sufficient methodological limitations as to be

lilttle more than pilot investigations. In his opinion, this

research has contributed more to our methodological

sophistication than to our confidence in outcomes. Procedures

have been developed for adequate random assignment, proper

obtaining of informed consent, improved tracking of individuals

over time, reduced attrition, and more sophisticated measurement.

Flay argues that third generation studies are more interpretable,

al though still limited.

The absolute differences in smoking onset between intervention

and comparison conditions have sometimes been dramatic (Telch et

al. 1982), despite the presence of methodological flaws that are

sometimes quite serious. Work is now needed at the level of

meta-analysis (cf. Cook, this volume). Individual studies tend

to provide limited information. Confounds may occur and

alternative interpretations are likely. Once a systematic body

of research has been established with results pointing in a

positive direction, the case for effectiveness will be

considerably strengthened.

Flay argues that at this point we know little about the why,

when, what, whom, and how of social influence approaches.

Detailed process research focusing upon effects of theoretically

important mediating variables is essential and is long overdue.

However, one cannot be overly confident that such analyses will

be either simple or easily interpretable. Glasgow (this volume),

for example, has listed several mediating variables hypothesized

to influence outcomes in social skills training approaches.

However, significant effects were found for only some of these

variables and then only some of the time. I suspect that the

situation will be similarly complicated in evaluating the social

influence approach.

120
Encouraging steps already have been taken to look at process

variables in prevention research. Work by Glasgow and his

col leagues (Glasgow et al. 1981; McCaul et al. 1983; O’Neill et

al. 1983) and by Biglan and his coworkers (Biglan et al., in

press; McConnell et al., in press) is noteworthy in this regard.

Biglan’s group included an innovative measure of proportion of

cigarette offers refused during the week prior to measurement.

In reviewing the prevention literature, it is not always clear

precisely what interventions have been employed. Commonly

accepted labels for treatment components may obscure major

differences in methodology. Although space limitations obviously

preclude exhaustive descriptions of procedures in published

journal articles, it would be extremely helpful for investigators

to maintain resource materials and manuals. These materials

could contain assessment instruments, leader and student guides,

detailed data analysis protocols, and so forth.

An important issue involves the extent to which treatment should

be tailored to the individual subject. Procedures that are

effective for relatively affluent suburban schools may not be

appropriate for schools in the inner city. Cultural differences

may also influence effectiveness of specific treatment

components. My own bias is to search for strong treatment

components that might be implemented in a diversity of settings.

Once effective programming is available and process analyses have

indicated more clearly which elements of treatment contribute to

outcome, additional work might attempt to modify specific

elements for different audiences.

Biglan (this volume) has warned against a "monomethod" bias in

evaluating programming. Previous work has relied very heavily

upon paper-and-pencil measures. A number of other possibilities

have been widely overlooked, including self-monitoring, telephone

probes, and observing extended interactions. Standard izat ion of

assessment instruments and of biochemical validation procedures

(Schinke and Gilchrist 1983) could also contribute to

interpretability of results across studies.

Assessment of norms and changes in norms relevant to smoking in

classroom and entire school contexts would be especially

appropriate in evaluating social influences programming. Biglan

has suggested that investigators look more closely at social

contingencies for smoking. A reduction in the number of smoklng

models could in itself contribute to the effectiveness of

treatment. Process analyses of successful treatments should

reveal measurable increases in the modeling of antismoking

statements and decreases in the modeling of prosmoking

statements.

A critical issue that is unresolved at present relates to the

long-term effects of prevention programming. if such programming

is successful, does it actually reduce onset of smoking or does

it simply delay onset? Lack of long-term followup data precludes

121
an unequivocal answer to this question. Demonstrated effects

among seventh-grade students may not be reflected in continued

differences in smoking among students finishing high school.

However, it should be emphasized that even a delay in smoking

onset is likely to produce long-term health benefits.

What is our best guess as to effective treatment components based

upon the evidence currently available? It appears to be

important to keep interventions as simple and as streamlined as

possible. Process analyses should enable us to revise and

sharpen our programs. Elements that are ineffective can be

revised or discarded. Programs can be modified for special

target populations. Process analyses will provide valuable

information relating to both potential mediating variables and to

actual delivery of treatment components.

As noted by prevention researchers, social contexts can

profoundly influence adolescent smoking. Interventions that

limit themselves to the school setting are likely to have

correspondingly limited impact. Community norms may be extremely

important. A more promising approach is to devise intensive

prevention treatment for children of varying ages. Such a

program should not be confined to the schools, but should be

extended to the home and to the community.

In this respect, the work of the USC group is exemplary. Not

only have they conducted large-scale school-based prevention

trials, but they have extended the scope of these efforts through

additional media programming (Flay et al. 1983b, 1983c). Nor

have they confined themselves totally to a prevention approach.

Much of their work has involved developing cessation components

for family members and other adults who may be critical role

models for children.

However, in addition to cessation programming, it might be useful

to include modeling strategies that could affect the behavior of

adults who continue to smoke. This possibility appears to have

been overlooked in previous work. Perhaps adults who are unable

or unwilling to quit can still become better role models. Other

parental attitudes and behavlors could potentially be as

important as smoking status in affecting the likelihood of

children’s smoking. if parents and other adults can be taught to

be better role models even when they continue to smoke

(especially considering the relatively modest outcomes attained

by existing cessation programs), the impact of prevention

programming on the social environment could be significantly

enhanced .

Another important step in prevention may be to prepare packaged

programs for large-scale distribution. Dr. Art Ulene, for

example, has a syndicated television program that could be

potentially duplicated in a large number of markets.

Unfortunately, this type of program, although it could

potentially reach a mass audience , may have limited impact due to

122
the lack of active aud fence involvement. The Stanford group (cf.

Perry et al. 1980) has developed a series of highly professional

videotaped vignettes and complementary printed materials.

Perhaps these could be used in a more interactive format

especially in the school setting. To the extent that prevention

efforts can be built around quality standardized materials, costs

might be reduced and replicability enhanced.

Additional work is needed to isolate subject variables that may

relate to outcome. At this point we know little about individual

characteristics--e.g., sex, grade level, prior smoking

experience--that might predict success in different

interventions. Which treatment components are most effective for

which individuals under which set of conditions? It appears

unlikely that a given approach, whether it be social influence,

social skills, or cognitive developmental, will prove uniformly

superior in preventing the onset of smoking. Perhaps social

skills training will produce greater generalizability than social

influence training under most conditions. However, this is an

empirical issue that deserves study. It is highly plausible that

even if differences are demonstrated between social skills and

social influence approaches, these dlfferences will be both very

specific and very dependent upon a given set of treatment

conditions.

Further research is needed to systematically assess different

types of prevention approaches both alone and in combination.

Long-term followups are al so needed to unequivocally demonstrate

that prevention programs are effective not merely in delaying

smoking onset but also in permanently reducing recruitment of new

smokers. It should be noted that even negative findings have

contributed to knowledge in this area. Thus it has been falrly

well established that interventions emphasizing delayed health

consequences of smoking are unlikely to be effective in

influencing the behavior of early adolescents (e.g., Botvin and

McAlister 1982).

CONCLUSIONS AND FUTURE DIRECTIONS

At this point, a major issue becomes application and

dissemination of existing prevention technology. Flay and others

have argued that it would be foolish to immediately proceed to

large-scale implementation. They are concerned that we do not

know the critical components of treatment for specific

individuals. If prevention programming is applied improperly

and, therefore, results in failure, the resulting disillusionment

could essentially destroy the field.

These concerns are certainly welltaken and require careful

cons iderat ion. However, my own perspective is somewhat

different. Again, this perspective is heavily influenced by my

experiences in the area of smoking cessation. Overall, I have

been disappointed by the lack of application of state-of-the-art

research-based cessation programs. Unlike prevention, various

123
entrepreneurs have offered cessation treatment on a commercial

basis. Unfortunately, the smoking cessation field has suffered

more than its share of charlatans (Kesling 1983).

I do not believe that cessation researchers should in effect

abandon the field beyond their laboratories to the purveyors of

fantastic claims. I have argued for years that in the case of

cessation, we cannot afford to wait for the development of

"perfect" techniques before offering our best interventions to

the millions of smokers who have professed a sincere desire to

quit, but who so far have been unable to do so on their own (cf.

Lando 1978a).

There is a natural tendency for researchers to be cautious in

applying their findings. (I have noted virtually the opposite

tendency on the part of corporate planners who seem to prefer to

rush to application even in the absence of minimal pilot

testing.) I would argue that an optimal strategy for both

prevention and cessation must fall between these extremes. We

should ask ourselves whether we can offer programs that are

superior to those routinely available.

Those of us who are heavily invested in laboratory research can

easily lose sight of the “state-of-the-art” in most nonresearch

application. We must remember that both prevention and cessation

treatments are being presented to the public with or without our

stamp of approval. Perhaps an example from my own locality will

suf f ice. In Iowa, smoking prevention has consisted largely of

"I'll Never Smoke" clubs sponsored by the American Lung

Association. These clubs are open after school on a voluntary

basis to interested students. The probable impact of such clubs

upon high-risk adolescents is easy to imagine.

I believe that we can do better than this on the basis of

knowledge that is currently available. Furthermore, I believe

that we have an obligation to do so. It is possible to proceed

both cautiously and systematically. Work can continue

simultaneously at several levels. Large-scale application can go

hand-in-hand with small-scale laboratory research.

Large-scale dissemination trials can and should include extensive

process analysis. Such trials could allow both increased power

for assessment of individual treatment components and further

validation of apparently efficacious intervention programs. A

major goal would be to establish optimal treatments for field

application based upon current knowledge. These treatments would

be modified and improved as new knowledge becomes available.

Dissemination trials themselves should raise further issues that

could be subjected to I aboratory study.

Small-scale laboratory research can test specific program

components. Larger scale demonstration projects can assess the

effectiveness of entire treatment packages. Process analyses can

be helpful in pinpointing effective elements in these larger

124
multifaceted interventions. Both quality control and systematic

process evaluation are essential in field contexts.

Al though we still do not know which treatment components are

critical to program effectiveness, Cook (this volume) has argued

that an important initial step might be to establish effective

multicomponent programs. Once such programs are established,

specific active elements can be isolated. This is essentially

the strategy that I have attempted to pursue in the area of

smoking cessation. Initial efforts concentrated upon

constructing a successful treatment package (cf. Lando 1977).

Subsequent studies have attempted to isolate effective components

of treatment (e.g., Lando 1978b, 1981, 1982).

In many respects, smoking researchers appear to have conducted

themselves much as blind individuals examining different parts of

the elephant. A successful approach to reduction of smoking must

be multifaceted and must include both prevention and cessation

components. Unfortunately, we have tended to be very

circumscribed in our approach. Fads have emerged in which

part icul ar “hot topics” have been pursued to the detriment of

both other areas and ongoing paradigmatic research. Thus in the

area of cessation, for example, data from surveys of smokers

suggesting that the majority of individuals preferred selfquittlng (e.g., Gallup 1974) resulted in the sudden neglect of

the intensive face-to-face interventions so critical to the

hardcore heavy smoker. It was erroneously assumed that because

most individuals quit in the absence of formal treatment, smokers

would be responsive to written self-help materials.

Surely, a coordinated effort between prevention and cessation

researchers would be far more likely to produce impact at the

community level than would a continuation of existing piecemeal

approaches. This intensive effort would include media appeals,

self-help procedures for smokers who wish to quit, school and

community based programming for prevention and cessation,

physician advice and referral, and formal clinics for smokers who

need additional help in quitting. lntensive integrated

programming could have a greater effect upon community norms

which already appear to be changing in an antismoking direction.

Political action would also be encouraged, both with respect to

restrictions upon tobacco advertising and increased awareness of

the rights of nonsmokers. As opportunities for smoking become

increasingly limited and as smoking loses social acceptability,

corresponding forces for change should accelerate treatment

effectiveness.

I believe that we now have the technology to achieve significant

impact both upon current smokers and upon recruitment of new

individuals to tobacco use. My own 5-year plan includes both

systematic application of state-of-the-art programming and

continuation of basic laboratory research. An integrated

multifaceted approach targeted to a large audience is likely to

125
produce measurable cumulative effects. Each component taken in

isolation is likely to have only limited impact.

My goal is to intervene simultaneously at the level of both

cessation and prevention. Cessation programming will include

intensive face-to-face clinics (cf. Lando 1977), self-help

materials, physician advice and referrals (cf. Pederson 1982),

single-session orientations to self-quitting conducted especially

at the worksite, and media presentations through such vehicles as

public access cable. Prevention programming will include

elements of social influence and social skills training delivered

both in school and community settings. There is already

suggestive evidence of a synergistic effect when cessation and

prevention components are applied simultaneously (Lando 1985).

In concluding this paper, I feel that it is essential to note

that science cannot proceed solely by fads and fashions. If we

are to have impact upon smoking, we must cast our information net

widely. Priority should be placed upon approaches that address

multiple aspects of the smoking epidemic. We should avoid

ignoring important parts of the problem. Researchers and applied

professionals should begin to collaborate in implementing

community interventions.

A combination of prevention and cessation is likely to have the

greatest impact, and such programming should be strongly

encouraged. Research approaches that include several levels from

basic hypothesis testing through widespread community application

should be enthusiastically supported. The type of model being

proposed for smoking prevention and cessation may also be

applicable to other forms of drug use. Integrative approaches

that combine basic laboratory research and larger scale

application should no longer be allowed to slip through the

cracks when it comes to funding decisions.

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AUTHOR

Harry Lando, Ph.D.

Iowa State University

Department of Psychology

Ames, Iowa 50011

129
A Cognitive Developmental

Approach to Smoking Prevention

Kathleen Glynn, Ph.D., Howard Leventhal, Ph.D., and

Robert Hirschman, M.S.

INTRODUCTION

It is well known that cigarette smoking is injurious to

health, increasing the risk of heart disease, lung

cancer, chronic bronchitis, peptic ulcer, respiratory

disorders, damage and injuries due to fires and

accidents, lower birth weight, and retarded fetal

development (U.S. Public Health Service 1964, 1980,

1981). As the adult public has become aware of these

dangers, millions of smokers have attempted to stop

smoking. While substantial numbers of people have

successfully quit smoking on their own (Schachter 1982),

many others find themselves unable to do so. For those

who turn to organized anti-smoking therapy, there is no

guarantee of success. Studies indicate that smoking is

refractory to a wide range of innovative techniques:

although the majority of procedures are capable of

producing short-term behavioral change, all current

approaches are plagued by high rates of recidivism (Gritz

and Siegel 1979). For example, among those who come to

clinics for help with giving up cigarette smoking, the

percentage remaining abstinent for at least 1 year after

treatment is consistently low, roughly 25% (Raw 1978;

Evans and Lane 1980). The difficulty of becoming a

permanent nonsmoker once the smoking habit is firmly

established suggests that attention be given to primary

prevention.

The present paper presents a formulation of smoking

prevention programs based upon a cognitive-developmental

view of the process of becoming a smoker. There are two

critical componenta to this perspective. The first is

that becoming a smoker involves an extended developmental

history that, for convenience, can be divided into a

series of stages: preparation for smoking, initiation and

initial trials, becoming a smoker (experimenting and

130
adopting the habit). and maintenance or addiction. The

second key point is that the experience of smoking is the

product of a complex set of underlying processes involved

in the "interpretation" (perception and understanding) of

the act of smoking, and the skills available for

controlling cigarette use and for achieving aims through

means other than smoking. The smoking prevention program

being tested attempts to alter the way information is

processed and smoking is experienced at each

developmental step. By altering the way sensations and

actions which are part of smoking are perceived, the

child's experience becomes an integral part of the

anti-smoking intervention. rather than a violation of an

anti-smoking rule imposed by adult authorities. In the

following paragraphs, this approach will be briefly

compared with the approach of other smoking prevention

programs, and then will be described in detail.

SMOKING PREVENTION PROGRAMS

Since the first Surgeon General's report (U.S. Public

Health Service, 1964), a variety of smoking prevention

programs have been implemented in Junior and senior high

schools, many without an evaluation component. Of those

which have been evaluated, some have shown significant

results, and there appears to be an emerging

comparability of results across studies. The earliest

smoking prevention programs were based largely on

information about the health consequences of smoking, and

showed little success (Thompson 1978). More recent and

promising programs have been based on social

psychological theory, specifically, McGuire's (1964,

1972) communication theory and Bandura's (1969) social

learning theory. These theories may be seen as

extensions of the persuasive-communication research

initiated by the Yale Group (Hovland et al. 1953). The

social psychologically based smoking prevention programs,

which are reviewed ably and at length in this volume,

rest on the well-documented fact that peer pressure is an

important impetus for experimental cigarette smoking.

These prevention programs attempt to bolster resistance

to social pressure by giving young people broad spectrum

life skills and/or specific social skills for avoiding

substance use (e.g., refusal skills and pressure

resistance tactics). It would not be far from the mark

to suggest that these approaches are designed to prevent

any use of cigarettes: social skills prevent

experimentation, and thus avoid addiction. The

youngster's experience with smoking is not typically an

intrinsic component of the skills-based smoking

prevention program.

One important indicator of the efficacy of these programs

is the percent of nonsmokers at pretest who are shown to

have been “recruited to smoking" at posttest. In a study

131
reported by Botvin and Wills (this volume), upon

immediate posttest there were 8% new smokers in the

experimental group versus 19% new smokers in the control

group. Among those who indicated at l-year posttest that

they were smoking weekly or daily, the figures are 11%

for the experimental group and 25% for the control

group. In a similar study, Botvin and Wills (this

volume) found 6% new smokers in the experimental group

and 13% in the control group at immediate posttest. At

l-year posttest, these figures were 15% and 22% for new

monthly smokers, 8% and 15% for new weekly smokers, and

6% and 11% for new daily smokers. In another study

(Flay, this volume), there were 5% new smokers in the

experimental group and 13% new smokers in the control

group at two-year posttest. (All differences reported

above are statistically significant.)

While the results of these and similar studies are

encouraging, it is clear that there is still room for

improvement. The social- and life-skills approach does

not deter all adolescents from smoking. The assumption

made in this paper is that the gap will not be closed

simply by strengthening the social skills component:

another type of information and preparation needs to be

added. The information to be added concerns the young

person's perception of and experience with smoking, as

these perceptions and experiences relate. smoking to the

individual's basic motives, and set the goals for skilled

behavior. This analysis suggests that the more socially

skilled and competent youngster may be MORE, not less,

likely to smoke if he or she perceives smoking as a safe

(not health-threatening> and effective way of regulating

emotional distress, achieving independence or managing

his or her social environment. Moreover, since most

(i.e., 85% to 90%) if not all children try a cigarette,

it would seem reasonable to try to alter the way the

child experiences such experiments, in order to make them

a part of the anti-smoking message. Finally, given that

addictive behavior develops over time in a series of

stages, and that different factors operate at different

stages to either encourage or discourage smoking, there

may be several ways and many times at which intervention

is possible.

THE STAGE MODEL

The central concept in this model, first described by

Leventhal and Cleary (1980), is that becoming a confirmed

cigarette smoker can be a long and complex process

(Salber et al. 1961; Cartwright et al. 1959; Pechacek et

al. 1984). Although movement toward regular smoking is

in some sense continuous, four discrete stages in the

progression to this end point can be delineated for

purposes of analysis. At each stage, some individuals

132
drop out of the sequence. Those who remain vary in speed

of transition from stage to stage (Hochbaum 1965;

Leventhal 1968; Mausner and Platt 1971; McKennell 1968;

Tomkins 1968). Over the course of this sequential

movement, there are a variety of factors operating to

impede or impel transition from stage to stage.

The first stage is the preparatory stage, when young

people are developing attitudes toward cigarettes, but

have not made any serious attempt to smoke a cigarette.

For most young people, this stage encompasses the years

up to about 12. Children as young as 4 months of age

are aware of cigarettes in their environment, and by 3

years more than 90% of children are familiar with

cigarettes (Barie and Fischer 1979). During this time,

youngsters form perceptions of what smoking involves, the

functions it serves, and the personalities of smokers and

nonsmokers. Young people are also developing needs and

are establishing patterns in the way they deal with those

needs. These patterns may influence, at a later date,

their likelihood of becoming a smoker, and the speed with

which they transit through the smoking stages.

The second stage is initiation, when a youngster smokes

one, two, or perhaps three cigarettes. Virtually all

young people reach this stage, that is, try at least one

cigarette (Grant and Weitman 1968; Palmer 1970; Wohlford

and Giammona 1969). There is a great deal of

variability, however, in age at Initiation and in whether

and how rapidly a child progresses from this stage

through the others (Hirschman et al. 1984).

The third stage is becoming. Young people in this stage

smoke irregularly and do not define themselves as

smokers. This stage involves experimentation with the

behavior itself (e.g., how to hold a cigarette and light

it) and regularization of the behavior (e.g., making

regular purchases of cigarettes, and associating smoking

with such activities as eating, drinking, socializing,

and studying). During this stage, smoking becomes

conditioned to environmental cues by being performed

periodically in conjunction with the same activities.

The fourth stage is maintenance, when a person has moved

to regular smoking and has adopted the image of a

smoker. It seems to take 2 or more years for most people

to make the transition to relatively heavy and consistent

smoking (Cartwright et al. 1959). but there are large

individual differences.

This picture is complicated since smoking determinants

differ for adolescents with different reasons for

smoking. Thus, the "causes" of cigarette smoking vary as

133
a function of smoking stage end smoking motive. Smoking

motives arise from end are part of the child's general

pattern of needs and strategies for need satisfaction.

According to the model proposed here, the three most

important reasons for pre-addictive smoking by

adolescents are social compliance. affect regulation, and

self-definition.

The social complier is a child who has a high need for

social approval and a history of acquiescing to peer

pressure. This pattern is associated with feelings of

uncertainty, need for belonging, and anxiety about

rejection. Affect regulators are children who are

monitors of their internal state, and who readily

acknowledge the presence of some unpleasant emotions.

When they are unable to control their environment, and

they lack inner resources, they resort to foods

(e.g., sweets), beverages (e.g., caffeinated drinks), and

over-the-counter medications (e.g., antacids> to control

emotional states such as worry or unhappiness. Two

surveys conducted in the Milwaukee area indicate that

about 30% of children use some substance in this way

(Glynn 1983). It is hypothesized in this paper that a

past history of this kind of behavior predisposes a child

to use cigarettes to regulate emotional state.

Self-definers are children who desire to express

individual autonomy and rebel. They strive to present

the self as tough, "cool," authority-defying, older than

one's age, end willing to take risks. Self-definers use

cigarettes to regulate social contact and fend off

influence attempts. They smoke to keep people away

rather then to attract people, and their message is

"Don't tread on me," or "I'm off limits".

The scheme in Figure 1 depicts some of the factors that

influence movement to a given stage for young people with

different motives for smoking.

Stage- end Motive-Specific Predictors

The social compliance-motivated child. In the

preparatory stage, this child has a high need for social

approval and a history of acquiescing to peer pressure.

This pattern is connected to cigarette smoking by the

beliefs that one's friends expect one to smoke, or at

least to try smoking, and that smoking is normative and

will lead to social approval.

In the initiation stage, the child smokes the first few

cigarettes with friends, motivated either by curiosity or

by peer pressure (Bergen and Olesen 1963; Hill 1971;

Hirschman et al. 1984; Biglan et al. 1984; Bewley et

al. 1974; Palmer 1970). Because their attention is

turned outward, these individuals are relatively unaware

134
SMOKING MOTIVES

social

appliance

affect

regulation self-definition

S

preparatory need for social use of foods, beverages, need to express autonomy,

approval and OTC medications to a "rebel"

regulate emotional state

T

initiation peer pressure, social curiosity about mood- need for impression

imitation, non- altering properties management; i.e., how

specific curiosity of cigarettes one appearstoothers; need

A

to regulate or reduce others'

efforts to control one

G

E

becoming continuing social

Influences

positive evaluation of

sensations produced by

smoking

skips this stage; is an

"instant adopter"

S

maintenance continuing social establishment of a link satisfaction with projected

influences; positive between smoking and "image"; positive evaluation

evaluation of sensa- affective state of sensations produced by

tions produced by Smoking

smoking

FIGURE 1

Stage- and Motive-Specific Predictors of Cigarette Smoking
of their body's reaction to the cigarette. If they

experience any aversive reactions such as coughing, they

simply hope that they will soon adapt to the symptoms.

These children anticipate that cigarette smoking will

make them feel closer to and more comfortable with their

friends.

In the becoming stage, the smoking cue is still primarily

a social setting, with cigarettes being used as a means

of nugmenting relationships with other people. Movement

through this stage is facilitated by the acceptance of

cigarettes when they are offered, by the purchase of

cigarettes to share them with others, and by the use of

cigarettes with others as a way-of defining

togetherness. The social smoker moves most slowly toward

smoking alone; the movement is, rather, toward a pattern

of socially determined use.

Nonsocial factors first tske on importance in the

maintenance stage. Social smokers begin to notice how

their bodies react to a cigarette, and to discriminate

certain of these sensations as pleasant. During this

stage, they may recognize a link between their affective

state and smoking. If so. they may begin to smoke alone

to regulate mood state by regulating nicotine level.

The affect resulator. In the preparatory stage, these

individuals have a high degree of awareness of their

internal state, particularly of irritability and other

such unpleasant emotions. When unable to control either

the environment or their emotional reactions, they resort

to foods, beverages, and over-the-counter medications to

relieve dysphoria. This pattern is connected to

cigarette smoking by the belief that cigarettes help

people to control their feelings.

In the initiation stage, affect regulators look for

verification that cigarettes can be used to alter mood.

These individuals are the most likely of the three

"types"' of smokers to make a solo try, and to dismiss the

aversive reactions that may accompany it. They actively

attend to, and evaluate, their physiological reactions to

each puff of each cigarette. They continue to smoke only

if they find that smoking elevates their mood or reduces

anxiety.

In the becoming stage, the link between positive mood end

smoking becomes more and more clearly established. As

the affect regulator continues to smoke, maintenance of a

positive emotional state becomes dependent on smoking.

From this linkage smokers derive a sense that they can

control, and even fine tune, their mood.

136
In the maintenance stage, emotion-regulating smokers

stabilize as regular users of cigarettes as long as they

continue to experience episodes of emotional distress.

If distress is sufficiently intense and widespread,

smoking becomes pervasive and strong dependence

develops. The cognitive developmental model of smoking

suggests that the affect-regulating smoker is most likely

to continue on to the use of other substances to control

emotional state.

The self-definer. The youngster with a strong need for

self-definition is, in the preparatory stage, a child who

needs to rebel or express individual autonomy. Feelings

of anger and hostility, stimulated perhaps by social and

school failures, appear likely antecedents of this

motivation. According to our model, this general stance

is connected to smoking by the expectation that smoking

is in fact valuable for self-definition as independent

and adult. The self-definer believes that cigarette

smoking is a sign of independence from authority and that

smoking will project this independent image to others.

In the initiation stage, this youngeter is the most

likely to practice holding and puffing on the cigarette.

According to our model, these young people want to smoke;

they are not motivated by social pressure, and social

skills training will not affect their likelihood of

smoking. With respect to the body’s physiological

reaction, self-defining smokers view symptoms such as

coughing as challenges to be overcome. Self-defining

smokers skip over the becoming stage; they are "instant

adopters."

In the maintenance stage, self-defining smokers are

likely to continue smoking as long as they feel

comfortable with the image projected by the act of

smoking. They keep smoking because the behavior allows

them to present a defined self, to ease anxiety and

tension with respect to self-identity, to provide status,

and to eliminate conflicts about self-worth, such as

failure to meet standards set by family and social

institutions. Self-defining smokers are also likely to

become hnbitual or addicted smokers. Repeated smoking in

isolation as well as in social groups allows the smoker

to discriminate nmong the sensations produced by

smoking. Eventually, self-defining smokers recognize a

link between their affective state and smoking; they then

smoke to regulate mood state.

The emoker's primary motive for smoking can shift over

time. For example, social smoking is potentially fragile

and can shift to self-defined or affect smoking,

depending on a variety of factors. Among these are the

individual's potential for addiction; a severe life

137
stress that reveals the usefulness of cigarettes for

controlling dysphoric emotion; social factors that

encourage self-labelling, and unsuccessful efforts to

quit smoking that lead to labelling oneself as an

addicted smoker. With enough time, of course, all three

"types" of smokers become dependent upon cigarettes in

the sense that cigarettes are smoked to maintain plasma

nicotine levels (Schachter 1978).

Interpretations of Smoking-Induced Sensations

As stated in the introduction, the assumption made in

this paper is that the process of becoming a smoker is

driven by an interaction between an underlying,

interpretive. information processing system and specific

smoking episodes. Thus, how a young person experiences a

first, second, third, or hundredth cigarette is a product

of the cigarette, the social context, the youngster's

physiological reaction to the cigarette, and the

youngster's way of interpreting (perceiving and

understanding) this reaction.

This focus on the importance of the individual's

interpretation of smoking-induced sensations is

consistent with a familiar theme in social psychology and

in the literature on drug use. It is well accepted among

social psychologists that there is a distinction between

physiological arousal and the psychological

interpretation of that arousal (Schachter and Singer

1962). A given level of arousal or a given sensation can

be interpreted in a variety of ways, depending on the

situation and the individual's understanding of that

situation. For example, in his classic study of reaction

to pain, Beecher (1959) found that wounded soldiers were

much less likely to ask for pain medication than were

male civilian patients undergoing major surgery. Beecher

explained the variation in terms of the differing meaning

of pain in the two groups; the soldier's wound was a

badge of courage and carried the hope of escape from the

battlefield, whrle the surgical patients were facing a

wholly unpleasant ordeal. The evaluation of a sensation

as painful or pleasurable can also be influenced by the

individual's expectation or mental set. Thus, Anderson

and Pennebaker (1980) found that the evaluation of a

neutral stimulus (sandpaper rubbed on a fingertip) as

painful or pleasurable depended upon the information

given to the Subject prior to administration of the

stimulus. Those who were told that the experience would

be painful Judged it to be so: those who were led to

believe the experience would be pleasurable found it to

be so.

The best known exponents of this theme with respect to

drug use are Lindesmith. who studied the development of

addiction to opiates (Lindesmith 1947), and Becker, who

138
studied the development of the user's response to

marijuana (Becker 1967). Both investigators highlight

the importance of the drug user's cognitive and affective

interpretation of the drug experience, stress the

importance of the user's social situation and knowledge

base as influences on this interpretation, and identify

this interpretation as a crucial factor in the movement

to addiction. According to Lindesmith, physical

dependence on opiates and addiction to opiates are two

different phenomena. After physical dependence has been

established, opiate users "get hooked" only if they

accurately identify withdrawal symptoms as such, and

treat them with more of the opiate. Users become

addicts, and regard themselves as such only when they

make a cognitive connection between administration of the

drug and relief of withdrawal distress. Thus, Lindesmith

attributes the origin of addiction not to a predisposing

trait or to a single event, but to a series of events.

This implies that addiction is established in a learning

process extending over a period of time. In a similar

vein, Becker describes the process of becoming a

marijuana smoker. He points out that the effects of a

given drug can vary according to the user's physiology,

psychology, and social situation. The effects also

depend on the user's pre-existing ideas and beliefs about

the drug. Thus, the sensations produced by marijuana are

subject to a variety of interpretations. The would-be

user must learn to discriminate certain sensations,

interpret them as pleasant (not aversive), and attribute

them to the marijuana. The social context in which use

of marijuana takes place is important primarily because

it determines the amount and kind of information

available to experimenters and, therefore, the

interpretations they can make about that experience. As

Becker points out, "psychotic" epiaodes were common

sequelae of both marijuana and LSD use, until there was

enough information available to provide other

interpretations for sensations such as altered perception

of space and time. Finally, Becker maintains that what

experimenters do not know also affects their experience,

making certain interpretations and actions based on that

missing knowledge impossible.

The reactions of an individual to a smoking episode can

be viewed in the framework suggested above. A

youngster's physiological response to a cigarette varies

depending on his or her age, weight, previous exposure to

ambient smoke, composition of the cigarette, depth of

inhaling, and other factors. There is also variability

in a young person's cognitive and affective response to

the same cigarette-induced sensation. For example, a

given sensation may be evaluated as pleasant by one

person and as unpleasant by another. Friedman and his

colleagues (1985) found the degree of reported pleasant

139
emotional and physiological effects experienced during

the initial three smoking episodes discriminated those

who went on to smoke more than ten cigarettes from those

who did not. It is not known what factors entered into

the young smokers' definitions of "pleasant". Sensations

can also "mean" different things to different people.

One person may view a physiological response such as

coughing as a sign of damage being done to the body,

while a second person views the same response as a sign

of weakness which should be mastered or overcome.

Whether a person learns or is conditioned to smoke to

suppress cravings or to achieve a euphoric "lift" (see

Stewart et al. 1984), it is clear that a complex learning

history and a multitude of factors influence a young

person's cognitive and affective response to sensations

experienced while smoking. Among these factors are the

‘setting in which smoking takes place, and the

individual's attitudes toward smoking, beliefs about how

body systems operate, and expectations about how smoking

"should" make one feel. For example, those who smoke in

a social situation are likely to notice fewer sensations

than those who smoke alone, because the group-smoker's

attention is turned outward, toward the others in the

group. Symptom perception may be heightened by the

arousal generated by fear of being caught smoking.

Alternatively, the fear arousal may be misattributed to

the cigarette and be re-evaluated as a "high." The child

who has a relatively more sophisticated understanding of

the respiratory system is more likely to infer injury

from a smoking-induced coughing spasm.

There is also change over time, both in the physiological

responses induced by smoking, and, more importantly, in

the smoker's interpretation of those responses. It is

well known that the body adapts to cigarette smoking so

as to minimize the surface indications of bodily damage.

Symptoms such as coughing and burning in the throat, for

example, abate with increasing exposure to smoking. The

smoker's cognitive response to cigarette-induced

sensations also undergoes a developmental process. The

first-time trier has different thoughts and attributions

about such sensations than does the dependent smoker.

The dependent smoker is a person who, at some point in

the developmental process, has learned to evaluate

cigarette-induced sensations positively, as pleasant and

enjoyable.

The mechanism which underlies the interpretive process

can best be described as a set of "cognitive schemata" or

memory structures which originate in the prior history of

the individual and which give meaning to stimulus

situations and actions. In this view, it is important to

distinguish between the individual's objective and

140
emotional processing of a stimulus situation (Leventhal

1974, 1980). The production of emotion involves the

addition of a noncognitive reaction to perception. This

additional factor is emotional memory. When a stimulus

situation is perceived (or experienced), it is matched,

by pre-attentive or nonconscious processes, to an

emotional schema that includes expressive motor,

autonomic and other motor reactions. This match evokes

the emotions which are linked, in memory, to previous

situational experiences similar to the new one. When the

match occurs, the emotional memory is activated, and an

emotion is experienced and colors the new situation.

One illustration is the young person who has a history of

using sweet foods and caffeinated beverages for a "lift"

when feeling lonely and unhappy. A cigarette-smoking

episode may mimic these earlier experiences in both the

setting and the youngster's lonely and unhappy frame of

mind, and the ornl administration of the cigarette may

further emphasize similarities to the previous "candy bar

and soft drink" experiences. In this case, the positive

affect which accompanied the earlier episodes is evoked,

re-experienced, and attributed to the cigarette. A very

different example is that of a child with a history of

severe asthma. If this child experiences coughing and

choking as part of a first cigarette try, the panic and

terror associated with the previous asthma attacks may be

re-experienced while smoking. It is predicted this

reaction serves as a deterrent to future smoking

attempts. The overall point is that youngsters with

different histories, and therefore different cognitive

and emotional schemas, perceive, recognize, label, and

evaluate the effects of cigarette smoking in very

different ways.

Supporting Evidence for the Stage Model

The stage model will be useful to the extent that

different factors can be found to influence smoking at

each stage. Unfortunately, few studies have attempted to

determine the different antecedents for the different

stages of the process of becoming a smoker. Most studies

have simply attempted to discriminate smokers from

nonsmokers. To learn something about the factors which

are associated with movement to each smoking stage, two

surveys have been conducted on a random sample of

students in grades 2 through 12 in 8 Milwaukee public

schools. To describe movement from the first cigarette

to regular smoking, several comparisons were made.

Subjects who had never smoked were compared with those

who had tried a cigarette. and then subjects who tried

only one cigarette were compared with those who

progressed to a second. In a multiple regression model,

the most important predictors of trying a first cigarette

141
were age, having a best friend who smokes, and a high

score on a risk-taking scale. The most important

predictors of trying a second cigarette were somewhat

different. They included age, negative attitudes toward

smoking (negative relationship), having siblings who

smoke, having more than half of one's friends smoke,

risk-taking, coughing while trying the first cigarette

(negative relationship), and reports of both feeling

dissatisfied with life and having given up trying to

improve the situation ("helplessness") (Hirschman et

al. 1984). Thus, movement to a second cigarette is

influenced by two dispositional or personality factors

which did not predict the first try (attitudes toward

smoking and helplessness). In addition, something in the

first cigarette experience (coughing) negatively

influenced the likelihood that the youngster would

progress to a second cigarette.

Because of the importance of learning which variables

influence speed of transition from stage to stage,

separate regression models were computed for those who

progressed to their second cigarette quickly (within 1

week, n = 23) and for those who progressed to their

second cigarette more slowly ( n = 31). Factors which

predicted only slow movement were social-environmental in

nature: having a best friend who smokes and having more

than half of one's friends smoke. Factors which

predicted only fast movement were helplessness, having

changed schools in the year preceding the first cigarette

try, coughing during the first try (negative

relationship), and experiencing dizziness during the

first try (positive relationship). Thus, quick movement

to a second cigarette is associated with two stress

variables and two variables which relate to the young

person's experience with the first cigarette, while slow

movement is associated with the presence of smokers in

the young persons's environment. These results suggest

that there is a subset of youngsters whose initial

attempts are motivated by inner need and by their

reaction to the smoking experience itself rather than by

peer pressure.

The fact that coughing during the first try is negatively

associated with continuing on to a second cigarette,

while dizziness is positively associated with continuing

on. suggests a close look at all the data on sensations

experienced during the first try. The survey instrument

asked about the presence or absence of six sensations; in

addition to coughing and dizziness, these included

nausea, feeling sick, headache, and a feeling of burning

in the throat. The assumption was that each of these

sensations would be experienced as aversive. The

hypothesis tested was that a negative correlation existed

between the degree of aversiveness of the cigarette

142
episode and the probability that the individual will

smoke again. As has been indicated, it was found that

coughing during the first try had a deterrent effect on

further smoking attempts. However, there was no

deterrent effect of any other sensation, or of the total

number of sensations, or of the severity of the

sensations (as measured by their duration>. Those who

reported feeling dizzy were significantly more likely

than were the others to continue to a second cigarette,

and were more likely to be current smokers at the time of

interview. It is possible that dizziness is perceived as

a "high" and that this perception encourages further

smoking attempts.

Another finding of interest comes from responses of

ex-experimenters about their reasons for discontinuing

smoking. The single most common response was not related

to social pressure or to health concerns. The response

was "because smoking did nothing for me" or "I didn't get

anything out of it." Those who gave this response had

physical reactions to cigarettes equal in number and

severity to those giving other responses. This response

appears to be similar to the previously mentioned

positive association of dizziness with quick movement to

a second cigarette. Thus, as is the case with first-time

triers, experimenters are likely to be searching for some

beneficial effect of smoking and are willing to overlook

aversive effects. If no effect that they interpret as

positive is forthcoming, they discontinue

experimentation.

The hypothesis that those who interpret cigarette-induced

sensations as signs of bodily damage are less likely to

continue to smoke was tested by asking the respondents

whether any of the sensations they experienced meant that

the cigarette was damaging their body. Of those who made

the damage interpretation, 10% were current smokers at

time of interview. Of those who did not make the damage

interpretation 23% were current smokers at time of

interview (p<.05). The fact that past events can be

reinterpreted in the light of current smoking status

suggests caution concerning this finding. However, if

this effect is found in the prospective data, it will

support the idea that interpretation of a sensation, not

the sensation itself, is important as a block to further

experimentation.

THE SMOKING PREVENTION PROGRAM

Programs

Implications of the Stage Model for Smoking Prevention

The stage model has become commonplace in theoretical

discussions of the development of cigarette smoking

(e.g., Fishbein 1982; Flay et al. 1983). However,

143
researchers do not typically draw implications from the

stage model for the content of smoking prevention

programs. One clear implication of the stage model is

that prevention opportunities exist at all stages in the

process of becoming a smoker. Another implication is

that, because the factors which influence smoking differ

by stage, young people should be given the different

kinds of skills, knowledge, and attitudes relevant to

each stage. This requires continuing investigation into

the factors which produce movement through the

developmental process of becoming a smoker --a research

endeavor which is currently being undertaken. However,

enough is now known to devise a theoretically and

empirically grounded smoking prevention program.

The Smoking Intervention

One prime target for intervention is the young person's

interpretation of the body's changing reactions to

smoking. In the smoking prevention program described in

this paper, students are provided with a knowledge base

to enable them to interpret these reactions negatively,

that is, as concrete signs of a health threat. For

example, it is explained that the body's initial

reactions to a cigarette --reactions such as coughing,

feeling a burning sensation, and so forth --are signs

that the body is being damaged. The physiology of the

respiratory system is described, and it is explained that

the initial sensations of smoking are part of the body's

warning system, which has been activated by the more than

2,000 toxins in cigarette smoke.

Over a period of time, the burning, roughness, and bite

of cigarettes abate, and this disappearance of symptoms

may incorrectly be taken as strong evidence for the

harmlessness of the cigarette. Therefore, it is pointed

out that adaptation to cigarettes and lack of reaction to

them does not mean that the damage ceases, but that the

body's warning system has been "knocked out." Students

are taught about the pain system, that it adapts to

repeated irritation, and that it can fail to provide the

necessary warning of potential disease. Students are

also taught the falsity of the belief that pain is

associated with all serious illness and harm, and that

the absence of pain can mean danger, not well-being. The

students are encouraged to perceive adaptation to

smoking-induced sensations as a sign of the risk of

addiction and loss of control over the smoking response.

Habituation is presented as a precursor of emotional and

addictive processes that limit the individual's freedom

and autonomy.

The goal is to prepare students for experimentation in

such a way that their experiences with cigarettes

confirm, rather than disconfirm, the notion that smoking

144
is harmful. To this end, those who continue to

experiment are prepared for the decline in physical

performance that they will experience, and it is

emphasized that this is evidence of damage inflicted on

the body.

It is clear that social pressure is an important

motivator of early smoking for many young people. For

this reason, social skills (e.g., graceful ways of saying

no) are taught through extensive discussion,

role-playing, and modelling in the classroom. This is,

of course, the primary component of many other smoking

prevention programs, and will not be elaborated here.

The cognitive developmental perspective suggester that

nonsocial factors are important predictors for some young

people at these same stages, and perhaps for social

smokers at the becoming, or maintenance stage. For

example, it has been suggested that two important subsets

of young people smoke for self-definition and for affect

regulation. To reach these young people, information is

presented which is designed to change the symbolic

meaning of the cigarette vis-b-via the needs to which

they are responding. For example, it is pointed out that

smoking is not really an adult behavior: many adults are

quitting or trying to quit and smoking among adults is on

the decline. The case is made that smoking is not

necessarily a sign of autonomy and is often not perceived

as a sign of autonomy by other people. Smoking may

reflect acquiescence to peer pressure or to images of

smokers which are portrayed by the media, and even if a

given youngster is not smoking for either of these

reasons, others may assume he or she is. It is

anticipated that young people who are exposed to this

message will be less likely than others to smoke in order

to enhance an imege of independence.

Addicted smokers are presented as people who do not have

their emotional equilibrium entirely under control and

who have more trouble with "nerves" than do

non-smokers. It is anticipated that youngsters who are

exposed to this message will not see smoking as an

attractive way of dealing with their emotional

reactions. Program participants are provided with an

understanding that the addictive process "creeps up" and

cannot be detected in advance. They are also provided

with an understanding that withdrawal is physically and

emotionally unpleasant, and that delaying quitting until

after one has become addicted is unwise. The view that

smoking is normative is countered by presenting

information on the actual proportion of adults and

youngsters who smoke cigarettes.

145
The above points refer to specific (and isolated) aspects

of the process of becoming a smoker. The developmental

model is also used as a pedagogical device. It becomes a

"meta-cognitive tool" for self appraisal. Thus, the

students are reminded that their ideas and feelings

change over time and are different now from what they

were 5 years ago: the needs and worries of the 6th

grader are not those of the 12th grader, which are not

those of the high school graduate. The earlier needs and

problems may seem childish when young people mature and

look back. The key point is that one may wish to avoid a

way of managing problems that becomes in itself a

permanent problem.

The format of the program is four 45-minute class

sessions. This is less classroom time than many other

programs require, but a program of this length has a

better chance of being adopted on a wide basis than does

a much longer program. Each session begins with a 10

to-12 minute slide-tape presentation and continues with

30 to 35-minutes of guided discussion in the classroom.

Both are led by adults. The slide-tape presentation

features an adult talking to young people seated together

at a table. The youngsters depicted range in age from 13

to 23, and are unfamiliar to the Subjects. A control

condition consisting of three standard anti-smoking films

for young people of this age was also provided.

Results

In the fall of 1982, the smoking prevention program was

piloted. Classrooms within one middle school (grades six

through eight) were randomized to either the experimental

or control condition. The control condition consisted of

three standard anti-smoking films for young people of

this age. The experimental condition included seven

classrooms with 176 students (54.8%). The control

condition included six classrooms with 145 students

(45.2%). A pretest and three posttests were

administered, one at 1 week, one at 6 months and one at

18 months post-intervention.

One program goal was to alter the labels and evaluations

of early smoking experiences. Pre- and posttest Items

measured interpretations of first cigarette reactions as

signs of damage to the body, of adaptation to cigarettes

as a sign of destruction of the body’s warning system,

and of a decline in physical abilities as a sign of

serious bodily harm. Experimental subjects endorsed

these interpretations significantly more often than

control subjects, especially on the 1 week posttest. For

example, experimental subjects were significantly more

likely than were control subjects to:

146
-disagree with the statement that lack of reaction to

the first cigarette means that the person is immune to

the harmful effects of smoking;

-agree with the statement that reactions such as

coughing and dizziness are signs of damage to the body:

-agree With the statement that the poi sons in

cigarettes are carried to every cell in the body;

-disagree with the statement that when an experimental

smoker no longer experiences coughing, a burning

sensation and so forth, that means that smoking is no

longer damaging the body; and

-disagree with the statement that smoking does not

damage the body until after the smoker has become

addicted.

The primary program goal was, of course, to discourage

cigarette smoking. The absolute number of students

reporting smoking activity on the immediate posttest and

on the 6-month posttest was too small to permit

analysis. However, the 18-month follow-up data indicate

that, among those who were nonsmokers at pretest (n=183),

11% (n=1O) of the experimental group and 25% (n=23) of

the control group describe themselves as smokers (p=.O3);

15% (n=14) of the experimental group and 27% (n=25) of

the control group report that they have smoked at least 1

cigarette in the past month (p=.O9). Whether these

differences will persist is not known. If the analysis

upon which the intervention is based is correct, and a

young person's experience with cigarettes is important in

the decision to continue or discontinue smoking, then a

cumulative effect over time is to be expected. The

subjects will be followed until they are 18 years of

age.

As has been indicated, there ere gaps in young people's

knowledge about cigarette smoking that seem

extraordinarily resistant to change. One of these gaps,

which is found in survey studies and in prevention

program pre- and posttests, is misperception of smoking

norms. Other investigators have found that many

youngsters overestimate the proportion of smokers in the

population. Therefore, a segment on the actual

proportion of people who smoke was included in the

intervention. However, on immediate posttest. 36% of the

experimental Subjects said that 9 out of 10 high school

students are smokers, and 48% said that 9 out of 10

adults are smokers! This misperception about smoking

norms is clearly very entrenched and resistant to

change.

147
POINTS OF DEPARTURE

Two of the many unresolved issues in the area of smoking

prevention research merit special attention. The first

concerns the choice of a within-school design or an

across-schools design for evaluating anti-smoking

programs. Use of a within-school design introduces the

possibility of contamination; that is, youngsters in the

experimental program may share their new-found knowledge

or attitudes with their school mates in the control

program. Use of an across-schools design introduces

another kind of problem, as differences in smoking status

found at posttest may be due to a school effect: that is,

they may reflect differences in the populations at the

two schools, possibly brought about by different

histories (i.e., different activities taking place in the

various schools). The across-schools design predominates

among the better known smoking prevention programs that

have a rigorous evaluation component. Decisions to use a

within or between school design depend to some extent

upon the theoretical aim of the intervention study. A

program which alms at changing the individual's

perceptions of his or her smoking experience may suffer

less cross-condition contamination, as the intervention

is not designed to alter social behavior and the general

environment in which the child develops. A strong social

skills program, on the other hand, cannot help but have a

powerful effect on the social context making it nearly

impossible to preserve even a modicum of separation

between experimental and control conditions using a

within school design.

The second issue concerns the pretest, which may have a

sensitizing effect by making the participants more alert

to the program material. This was viewed initially as a

threat to external validity: the concern was whether the

experimental results would generalize to an un-pretested

population (i.e., to the students in a school system that

adopted the smoking prevention program without its

research component). An alternative view is that the

pretest, or something like it, might be used in a

deliberate way to prepare the students for the program

content. Ways in which to do this are now being

considered. For example, one could prepare children for

program exposure by focusing them on personal life

experiences in which they have acted on motives similar

to those involved in the different stages of smoking,

and then regretted those actions. For example, the

youngsters could be asked to recall episodes in which

they acted on a dare and ruined something they liked

(similar to the initiation of smoking) or times when they

148
ignored warning signs and were hurt in social

relationships (similar to ignoring the disappearance of

coughing, etc., in smoking). The similarity and

relevance of these epi sodes to smoking could be brought

out in post program discussions. Another way to do this

is to have a fairly short, guided discussion about the

students' goals and plans for the not-so-distant future

(perhaps for high school), and about how cigarette

smoking does or does not fit in with those plans. The

goal would be to make salient the future self and certain

self-values, and to draw out the implications of smoking

for those values. At a minimum, this sort of preparation

should enhance memory for the content of the smoking

prevention program. It may also reduce the contemporary

demands of social pressure, by inducing the participant

t o "take the longer view."

SUMMARY

Most smoking prevention programs for middle-schoolers

target non-smokers. These programs seek to educate young

people about the hazards of smoking, influence young

peoples' attitudes toward smoking, and reduce initial

experimentation with cigarettes by providing sociallife-skills training. The program described in this

and

chapter incorporates these features and adds a component

which explores, in some depth, the nature of the user's

response to cigarettes This component focuses on the

young person's physical and psychological reaction to

cigarette smoking, and provides a knowledge base which

promotes a negative evaluation of that reaction. This

component targets all young people, but it is anticipated

that it will be especially effective with pre-addictive

experimenters who are wondering what smoking can "do for

them". One challenge for the future is the development

of intervention strategies that have something to offer

the young addicted smoker who wishes to quit smoking.

These young people are largely unserved by school-based

smoking education programs, drug abuse programs, and

organized smoking therapies.

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AUTHORS

Kathleen Glynn, Ph.D.

Department of Behavioral Medicine

Mount Sinai Medical Center

P.O. Box 342

Milwaukee, WI 53201

Howard Leventhal, Ph.D.

Department of Psychology

University of Wisconsin

Madison, WI 53706

Robert Hirschman, M.S.

Department of Psychology

University of Wisconsin

Madison, WI 53706

152
The Cognitive Developmental

Model and Other Alternatives to

the Social Skills Deficit Model of

Smoking Onset

William J. McCarthy, Ph.D.

This conference testifies to the success of school-based smoking

prevention programs that provide adolescents with training in

either general social skills or in specific social skills thought

to be particularly useful in preventing regular cigarette smoking

in teenagers. No other generic approach to substance use,

including fear appeals, moral suasion, health consequences

education, and self-esteem enhancement has occasioned the 50

percent reduction in onset rates of tobacco use that multiple

investigators have achieved with social skills training programs.

Given such success, shouldn't we be investing substantial sums of

money in disseminating social skills and social influence training

programs to all school districts in the United States? A critical

evaluation of the literature suggests that our enthusiasm to

disseminate the successful smoking prevention approaches must be

tempered by the high cost of these programs and by their repeated

failure to maintain the relatively high levels of smoking

abstinence initially achieved. There are also too many important

questions that remain about how to most effectively target

adolescents of different ages, what the psychosocial consequences

of preventing teenagers from smoking are, and what strategies are

politically, socially and economically feasible. Using an

alternative smoking prevention program proposed by Glynn,

Leventhal and Hirschman in this volume as an example, this chapter

discusses alternative prevention perspectives that address major

conceptual issues that have not been addressed by social skills

and social influence skills training programs. Until the major

conceptual issues have been addressed, extensive field trials

would seem premature.

In the course of this chapter I argue that: 1) social skills

training programs will be considerably improved by tailoring the

programs according to the developmental needs of the targeted

adolescents, and 2) more study of mediating processes in smoking

onset is needed to determine how an individual's developing social

and psychological needs influence his/her smoking status, and, in

particular, under what conditions attitudes predict or explain

smoking behavior.

153
The originators of social skills and social influence training

programs are among the first to admit that the documented success

of their programs in reducing the rate of cigarette smoking onset

among targeted adolescents must be qualified.

unambiguous evaluations of their

They recognize that

programs have been vitiated by

non-random assignment, interpretive confounds, inadequate

followup, biased attrition, and model misspecification.

Unambiguous evaluation of any multicomponent, school-based,

smoking prevention program is an ideal that will not be achieved

in a single investigation because of the practical difficulties

always encountered in trying to implement a prevention program in

real-world settings. A reasonable consensus about the general

virtues of social skills and social influence training programs

could emerge, however, from a rigorous meta-analysis of all

publicly available results from such programs. Such a consensus

depends on: 1) the non-replication of methodological weaknesses

across studies, and 2) comprehensive coverage of the significant

influences on smoking onset, when all studies are considered

jointly. In this monograph, Flay, Biglan, and Cook have

thoroughly addressed the first challenge to consensus, namely the

general and specific methodological problems in reaching a

consensus in the area of smoking prevention. This chapter focuses

on the second challenge to consensus, that is, on the need to

consider all major influences on smoking onset, including both

causal and mediating variables. Below, I discuss a number of

important influences on teenage smoking onset that published

studies have heretofore ignored.

THE SOCIAL SKILLS DEFICIT MODEL AND ITS IMPLICATIONS

Most of the theoretical models of smoking prevention used to

justify the smoking prevention programs reviewed in this monograph

have been classified under the labels: "Social influence models,"

"Social skills training models," and "Refusal skills training

models." The smoking prevention programs reviewed here that are

based on these models presume that a deficit exists in the target

population with respect to refusal skills or social skills. These

interventions, of course, seek to eliminate these deficits through

health education and application of social learning principles. I

accordingly group the smoking prevention programs reviewed in this

monograph under the rubric: "Social Skills Deficit" programs.

Most of the Social Skills Deficit programs have targeted junior

high students, especially seventh graders, and most have targeted

whole classes or whole schools, regardless of the students' a

priori risks of becoming smokers. The prevention programs have

been designed to expose all participating teenagers to information

about how to acquire social skills or refusal skills, whether or

not the targeted teenagers show a need or desire for those

skills.

Implicit in Social Skills Deficit programs is a model of

development that imputes the same kind of passivity and

malleability to pupils that Holt (1964) claimed is the model

154
governing theory in formal education. The model, as applied to

the context of explaining cigarette smoking onset, is that of a

defenseless teenager who, for lack of general social skills or

refusal skills, passively accedes to social pressures to smoke

unless educators forearm him/her with concrete, appropriate words

and rehearsed acts that communicate a clear "NO!" to pressures to

smoke.

In addition, exclusive reliance on the Social Skills Deficit model

implicitly excludes the possibility that some teenagers will

decide to smoke for intrapsychic reasons, that is, because the

perceived non-social rewards to the self for smoking are perceived

to outweigh the costs.

GLYNN, LEVENTHAL AND HIRSCHMAN'S COGNITIVE DEVELOPMENTAL

MODEL OF BECOMING A CIGARETTE SMOKER

Glynn, Leventhal and Hirschman's Cognitive Developmental model

includes many features foreshadowed in earlier work by Leventhal.

One feature is a preference to view the targets of health

communications as self-regulators rather than as relatively

passive respondents (e.g., Leventhal et al. 1983). Another

feature is a focus on cognitive responses and cognitive

interpretations of such health-related events as pain and smoking

(e.g., Leventhal et al. 1983; Leventhal and Cleary 1980;

Leventhal and Nerenz 1982). A third feature is a categorization of

smoking prevention strategies according to how effective they will

be for each of several distinctive stages of becoming a smoker.

That is, adolescents are targeted differently depending on whether

the teenager is a novice smoker, an experimenting smoker, or an

addicted smoker (e.g., Leventhal and Cleary 1980; Hirschman et

al. 1983). Finally, the last feature is a concern with affective

responses to stimuli and the impact of the affective responses on

perception, interpretation, and memory of the stimuli (e.g.,

Leventhal and Cleary 1980; Leventhal et al. 1980).

According to Glynn et al., the path from naive non-smoker to

addicted smoker is a long one, mediated by four distinguishable

stages. They argue that the motives for moving from one stage to

the next vary by stage, requiring that different smoking

prevention strategies be used to discourage individuals from

moving to each of the higher stages.

The four stages of this model are: 1) the preparatory stage, 2)

the initial experimenting stage, 3) the becoming-a-smoker stage,

and 4) the identity-as-a-smoker stage. Glynn et al. acknowledge

that Social Skills Deficit intervention programs are effective at

discouraging teenagers from initial experimentation with

cigarettes, that is, discourage movement from the first stage to

the second stage. They imply, however, that Social Skills Deficit

programs have not been effective in preventing or discouraging

teenagers from moving from initial experimentation to regular

smoking, that is, from moving from the second to the third stage.

They suggest that a program that addresses the cognitive and

affective reactions of experimenting smokers to their smoking

155
experiences would be more effective than current social skills

oriented prevention programs in deterring these experimenting

smokers from regular smoking. Glynn et al. have been recently

testing such a program derived from the Cognitive Developmental

approach.

HOW THE COGNITIVE DEVELOPMENTAL APPROACH IMPROVES ON

CURRENT PREVENTION APPROACHES

The model of the development of a cigarette smoker proposed by

Glynn et al. supplements the Social Skills Deficit model in

several respects:

- One, it explicitly links mediating cognitive processes to the

influencing social pressure on the one hand and to the

cognitive affirmation of one's self as a smoker or nonsmoker

on the other.

- Two, it allows for and explains how it is possible for a

teenager to choose to become a smoker despite the absence of

social pressures to become a smoker.

- Three, it posits a more active role for the individual

engaged in the process of affirming his/her status as a

smoker or nonsmoker.

- Four, it attends conscientiously to an evolving status over

time; that is, it is very much concerned with the process of

becoming a smoker as well as with the long-term outcome of

what smoking status the teenager opts for.

- Five, it recognizes large individual differences in responses

to seemingly the same phenomenon of cigarette smoking.

- Six, it recognizes that the individual's previous history of

smoking will influence how his/her cigarette smoking will be

interpreted, i.e., as experimenting, as expressing solidarity

with peers, as constituting an overlearned habit, or as a

reflection of a physiological addiction.

The Cognitive Developmental approach sketched by Glynn et al.

brings a new perspective to prevention issues. It is sufficiently

dissimilar from currently popular models to stimulate new thinking

about how to improve smoking prevention programs.

NEW DIRECTIONS SUGGESTED BY THE COGNITIVE DEVELOPMENTAL APPROACH

The Cognitive Developmental approach suggests new directions, some

of which are discussed below. One new direction is Glynn et al.'s

insistence on interpreting the meaning of an individual's current

smoking experience only in light of that individual's smoking

history. The recognition that cigarette smoking is a

qualitatively different experience in individuals who differ in

smoking history helps to explain some recent findings on initial

brand name choice. In research on why teenagers start smoking,

156
conducted over the last 3 years in Los Angeles, I noted that there

are different kinds of smokers depending on, among other things,

how old the teenager was when beginning the smoking habit

(Wong-McCarthy, 1982). Among Anglo and Hispanic smokers who

started smoking at a very early age, there was a near unanimity

among Anglo and Hispanic children of choice of brand (this brand

will be referred to here as "brand X").1

Teenage smokers who reported smoking a brand other than 'brand X"

cigarettes at the start of their smoking habit were significantly

older than the "brand X" smokers (Wong-McCarthy, 1982). The

overwhelming popularity of "brand X" cigarettes among younger,

Anglo smokers has been replicated in the National Institute of

Education (NIE, 1979) study, and by investigators in Minnesota and

at the University of Southern California.

These differences in initial brand name choice across different

ages suggests that the choice to smoke is phenomenologically

different for younger and for older teenagers. The Cognitive

Developmental perspective welcomes and expects this difference.

The Social Skills Deficit model does not account for such

differences. These differences in initial brand choice also

suggest that effective antismoking appeals targeted at older

adolescents need to differ substantively from the antismoking

appeals that will effectively discourage younger teenagers from

smoking.

THE CONTRIBUTION OF THE COGNITIVE DEVELOPMENTAL APPROACH

IN HIGHLIGHTING THE ROLE OF COGNITIONS IN SMOKING ONSET

The role of cognitions in mediating social influences and

teenagers' smoking status is an important one that has been

inadequately addressed by most prevention researchers. Brian

Flay, who examined the mediation of cognitions in the context of a

mass media-based prevention program, is an exception (cf. Flay et

al. 1983).

The subject of memory must be included in any general discussion

of the role of cognitions in mediating teenagers' choice of

smoking status. Glynn et al.'s discussion of the role of memory

in the recruitment of teenagers to smoking is provocative and

provides a possible description of the process by which cigarette

advertising influences teenagers to smoke. They assert that one's

smoking history lives on in memory and colors the interpretation

of all subsequent smoking experiences. Their discussion of the

role of memory in smoking onset was particularly interesting

because they felt compelled to posit the existence of a particular

kind of memory, one that they called: "emotional memory."

According to Glynn et al., emotional memory is a holistic type of

memory. By reading between the lines I inferred that emotional

memory for events and people is established for an individual only

with repeated exposure to the events or people to be remembered.

The specifics of any one event contributing to the development of

an "emotional memory" are irrelevant. What resides in emotional

157
memory are common accretions, of expectations and residual affect

that remain from the individual's emotional reactions to episodic

events.

This discussion of memory is mentioned at some length because I

have been concerned with demonstrating that cigarette

advertisements have a measurable impact on the recruitment of

teenagers to the smoking habit. The literature suggests that

acute exposure of teenagers to any one instance of a particular

prosmoking advertisement does not have a measurable effect on the

adolescent's behavior. The concept of emotional memory proposed

by Glynn et al., however, suggests that we examine more closely

the effects on memory of repeated exposure

influences.

to prosmoking

The intermittent but continual exposure of teenagers

to prosmoking billboards may have cumulative effects over time

that are not measurable with only one exposure. The Cognitive

Developmental approach, with its focus on measuring process and

measuring cognitions, may explain how the mass media can influence

people's attitudes and behavior toward cigarette smoking through

low-level, repeated effects.

Another redirection suggested by the Cognitive Developmental model

is a return to the view that humans are active choosers, and, even

when pressured by social forces to adopt a particular outcome,

work hard cognitively to maintain the belief that their life

choices were of their own choosing (e.g., Taylor 1983).

SOME NEEDED CLARIFICATION OF FEATURES OF THE COGNITIVE

DEVELOPMENTAL MODEL

Glynn et al.'s Cognitive Developmental theory suggests

consideration of new foci of research effort. The new perspective

should not ignore, however, the theoretical insights and

methodological innovations associated with the older paradigms.

Cognitive Developmental theory has areas that need elaboration;

some of these are discussed below.

One can take issue with the implied necessity of smokers moving

sequentially through four discrete states to become the smokers

they are. One can also take issue with the implied necessity of

defining would-be smokers in terms of their actual experience with

cigarette smoking instead of in terms of their aspirations to live

a lifestyle that includes cigarette smoking.

The Jessors' work (1977), the work done by Kaplan (1980, 1983) on

self-esteem-related predictors of drug use and my own work

(Wong-McCarthy and Huba 1981) suggest that long before they smoke

cigarettes regularly some teenagers have already chosen for

themselves a lifestyle that will include cigarette smoking.

Christiansen et al. (1982) have similarly documented, for alcohol

use, how teenagers' attitudes toward alcohol can become much more

favorable despite having no direct experience with alcohol. To

the extent that smoking is but one of many components that

contribute to the kind of lifestyle that supports regular

cigarette smoking, it is easily conceivable that a person could

158
become committed to regular smoking without having yet developed a

history of smoking.

Another problem with the Cognitive Developmental model is the

failure to evaluate the importance of cognitions relative to the

importance of other developmental influences, especially social

influences, for directing teenagers' behavior. The data on

initial choices of cigarette brand suggest that the social need

for solidarity, for security through conformity, is very powerful

for young teens and measurably less so for older teens.

Individuals' cognitive interpretations of the smoking experience

are, therefore, likely to be a more important determinant of

smoking status for older teenagers than for younger teenagers,

whereas social influences will be a more important determinant of

smoking status for younger rather than older teenagers. In

general, the evidence suggests that individuals' cigarette-related

cognitions will explain an increasing amount of the variance in

smoking status as age of smoking onset increases. The

longitudinal work of Sherman and his colleagues (1983b) has

generally confirmed this pattern that cigarette smoking-related

cognitions gain increasing importance relative to social

influences with increasing age as a predictor of teenage smoking

behavior.

Yet another problem, which may simply be a reflection of the

inchoate status of Glynn et al.'s theory, is that the general

nature of the cognitions for the different stages of becoming a

smoker have not been identified. One naive hypothesis is that

beginning smokers have a rather vague conception of what is

entailed in being a smoker and have cigarette smoking-related

cognitions that are highly influenceable. Some evidence suggests

that the script that defines the role obligations and the rewards

of being a smoker become well-articulated only with time. Another

hypothesis for which data already exist seemingly contradicts a

notion implicit in Glynn et al.'s model of smoking onset. The

hypothesis is that initial expectations concerning the perceived

social benefits of smoking, such as expectations for increased

popularity and increased social sophistication are disconfirmed

over time for most smokers (Kleinke et al. 1983; Schoonmaker

1983; National Institute of Education 1979; Wong-McCarthy 1981).

Implicit in Glynn and Leventhal's model is the notion that some

experimenting smokers will adopt more positive beliefs about the

consequences of smoking by virtue of their direct experience with

smoking. With respect to the social consequences of smoking, that

seems generally not true -- smokers see smoking as having fewer

social benefits than do nonsmokers, presumably because smokers

become disabused of their initially positive expectations about

smoking through direct experience.

As are most researchers on social psychological processes, we are

bedeviled by the problem that attitudes predict behavior only some

of the time. We do not know, a priori, whether attitudes

influence behavior or whether behavior influences attitudes at

different stages. While it is simple enough to say that there is

a continued bidirectional exchange between the two domains, there

159
may be theoretical justification for asserting that attitudes,

especially for the younger teens, are merely epiphenomena that

serve as post facto rationalizations for choices already made for

social reasons. Cigarette smoking-related cognitions may be more

predictive of later smoking behavior for older teenagers.

Taylor's Cognitive Adaptation Theory (1983) might explain the

process by which a young teenager's cognitions could follow from

and merely confirm the individual's de facto smoking status.

Glynn et al. assert that an intervention at the level of

cognitions will be a more effective smoking prevention strategy

because cognitions are easier to change than behavior. Few would

disagree with this assertion. If teenagers' cognitions about

smoking are so easy to change, however, what is to prevent

intervention-influenced cognitions from reverting to prosmoking

attitudes in response to the continued barrage of prosmoking

messages from cigarette advertising and selected peers? The

long-term benefit of Glynn et al.' s intervention program remains

an open question as long as their intervention does not include

procedures that "lock in" the anti-smoking attitudes that their

intervention is designed to stimulate.

ADOLESCENT MOTIVES TO SMOKE NOT INCLUDED IN EITHER MODEL

Many children may be smoking for reasons other than low

self-esteem and inadequate social skills. They may be smoking as

a self-prescribed medication for depression or feelings of

powerlessness (Hirschman, Leventhal and Glynn 1984; McAlister

1983; Wong-McCarthy and Huba 1981). Gochman (1972, 1977, 1982),

and Gochman and Parcel (1982) have argued persuasively that

children, at puberty, learn that there is more to life than merely

preserving one's physical health. Cigarette smoking is almost

universally viewed as physically harmful, even by teenagers and

adults who smoke. Children, nevertheless, develop increasingly

favorable attitudes toward smoking cigarettes from age eleven to

age fifteen (e.g., Botvin et al. 1983). Teenagers who might have

strongly opposed cigarette smoking as prepubescent children will

actively work to incorporate smoking into their lifestyle,

presumably for the perceived psychosocial benefits that they now

associate with cigarettes. Who are we to say that all teenagers

are wrong to adopt the smoking habit? For some teenagers the

psychosocial benefits that smoking provides may appear to be

unavailable to them through any other means and may appear to

greatly outweigh the perceived health costs of regular smoking.

Glynn et al.'s model focuses on those cognitions that originate

from the experience of smoking. While their intervention entails

the use of persuasive information to change the smoking-related

cognitions of would-be regular smokers, their model gives short

shrift to the influence of non-physiologically mediated cognitions

on adolescents' decisions to smoke. Other researchers, notably

Sherman and his colleagues, have examined those smoking-related

cognitions that originate from perceptions of other smokers, from

conversations with peers, and from exposure to public messages

concerning smoking. The work of Sherman and his colleagues is

160
discussed at some length below because of the high quality of its

design and its reporting, and because their findings have

considerable relevance for improving smoking prevention efforts.

Based on a 4-year longitudinal study of several thousand junior

and senior high school students, Sherman and his colleagues have

recently published a series of insightful reports on the role of

smoking-related cognitions in cigarette smoking onset. They have

examined such cognitions as adolescents' intentions to smoke

(Chassin et al. 1981), adolescents' ideal self-images and their

ratings of the images of smokers (Barton et al. 1982; Chassin et

al. 1981), adolescents’ estimates of smoking prevalence among

adults and peers (Sherman et al. 1983a) and adolescents'

perceptions of their environment not specific to smoking but

predictive of smoking (Sherman et al. 1983b).

In a recent review of their major findings, Sherman et al.

(1983b) reported the following: 1) adolescents at highest risk of

smoking grossly overestimated actual smoking prevalence; 2)

attitudes, beliefs and intentions predicted the later smoking

status of experimenters better than they predicted the later

smoking status of never smokers; 3) behavioral intentions at year

1 were consistently the best predictor of smoking transitions at

year 2; 4) the presence of parents and older siblings who smoked

was more important to the initiation of smoking than to later

transition from experimental to habitual smoking; and 5)

nonsmokers whose self-concepts were more similar to adolescents'

image of a smoker were more likely to plan to smoke in the

future.

Sherman et al. drew several conclusions from their review that

are relevant to mention here. Their findings concerning the

importance of adolescents’ aspirations for developing a particular

social image suggested that changing the social image associated

with smoking or giving adolescents other ways to project an image

of toughness, precocity, and sociability would be useful adjuncts

to current smoking prevention programs. Their findings concerning

behavioral intentions suggested that cross-sectional studies of

smoking intentions and their correlates could serve as a

time-efficient way to understand smoking initiation, because

behavioral intention at time 1 could be used as an analogue to the

true outcome measure, namely, smoking status at time 2. Their

findings concerning the strength of the influence exerted by

smoking models at different stages in becoming a smoker suggested

that, once an adolescent begins to smoke, interventions that

attempt to combat family influences and the influence of adult

smoking models in general may be less effective in preventing

regular smoking than other, formerly unimportant, influences on

smoking status.

Evidence, then, is accumulating (Sherman, 1983; NIDA, 1985) that

neophyte smokers, experimental smokers, and regular smokers differ

in their responsiveness to particular health-related messages.

Nonsmokers appear to be disproportionately influenced by physical

health concerns, both short-term and long-term (NIDA, 1985).

161
Neophyte smokers are prevented from becoming experimental smokers

by interventions that train them in the skills needed to "say no"

to peer pressure to use drugs (e.g., Evans and Raines, 1982).

Experimental smokers, on the other hand, are best deterred from

becoming regular smokers by interventions that provide training in

decision-making skills (NIDA, 1985). Sherman et al. (1983) also

noted that social and demographic antecedents of smoking onset

best predicted the transition from neophyte smoker to experimental

smoker but that attitudes toward smoking best predicted the

transition from experimental to regular smoker.

It is becoming apparent that health-related messages must differ

in the degree to which they concern physical, social or

psychological health. These differences appear to distinguish

different stages of smokers as well as different ages, independent

of smoking status. Figure 1 shows the general pattern of

health-messages tailored for different age groups.

Figure 1

Relative importance of physical, social and psychological health, for

youth aged 9 to 19 years

The foregoing suggests rather specific prevention strategies

appropriate to each of several classes of would-be cigarette

smokers. Such strategies could include the following:

for the neophyte smoker: fear appeals related to physical

health, especially those dealing with the immediate

physiological consequences of substance use

for the experimental smoker: assertiveness skills, how to

"say no" to offers by peers to use a substance

for the confirmed, occasional smoker: "life-skills",

especially communication skills and decision-making skills

for the confirmed, addicted smoker: self-efficacy skills and

strategies for effecting lifestyle changes; also, information

about the benefits of alternative, healthful lifestyles and

information designed to reduce the perceived costs of making

lifestyle changes.

162
Overall, the work of researchers concerned with the role of

cognitions in smoking onset strongly suggests that smoking

intervention programs should include different interventions for

adolescents at different stages in the developmental sequence that

culminates in regular smoking. If practical limitations make it

impossible to implement interventions that are targeted separately

at non-smokers, preparatory smokers, experimenting smokers,

"pledged smokers," and regular smokers, they should at least be

targeted by age group. Current prevention programs are neither

stage-specific nor age-specific.

The novel and important findings of Sherman et al. have not yet

been applied to current smoking prevention programs. Until they

have, it would seem premature to embark on large-scale trials of a

consensus smoking prevention program.

A COMPREHENSIVE STRUCTURAL MODEL OF ADOLESCENT SMOKING ONSET

A structural model of smoking onset that includes the major

influences on adolescent smoking onset posited by either the

Social Skills Deficit model or the Cognitive Development model is

presented below. This model is too comprehensive to be tested in

a single empirical investigation. It should serve, however, as an

overall conceptual exemplar to be tested by multiple measurement

models derived from subsets of the structural model. This, or

some equally comprehensive model of smoking onset needs to be

adequately tested before large-scale trials of a consensus smoking

prevention program are warranted.

The correlational model presented in figure 2 should be read left

to right. The circles represent theoretical constructs known to

influence cigarette smoking onset; the arrows represent the

theoretically likely paths of influence, from the stable

predictors of smoking onset, such as age and socioeconomic status

(SES), to the recursively-influenced predictors of smoking onset,

such as cognitions about the personal consequences of smoking. An

example of a path is the effect of adult smoking models on smoking

behavior, mediated by personal goals and needs and self-efficacy.

Note that feedback loops only involve the mediating constructs of

personal goals, cognitions about the personal consequences of

smoking, personal self-efficacy, and the two well-being

constructs. Other feedback loops exist but are ignored for

reasons of parsimony. Perceived smoking norms (construct #12),

for instance, are probably influenced by one's smoking experience

(construct #16), yet there is no arrow signifying a feedback loop

from smoking behavior to perceived smoking norms.

Also note that the relative influence on individuals' smoking

status of the various constructs given in the figure varies as a

function of the individuals' smoking history and age. For early

adolescent, neophyte smokers, family background and general

socioeconomic factors are most important; for middle adolescent,

experimenting smokers, lifestyle factors and emergent personal

goals are the most important predictors of later smoking; and for

163
Figure 2

A comprehensive correlational model of adolescent cigarette smoking onset
1.

2.

3.

4.

5.

6.

7.

8.

9.

10

11.

12.

13.

14.

Indicators of constructs given in Figure 2

Age: Age in years 8 months

Sex: Self-report

Family SES: i) Father’s income, ii) Mother’s income, ii) Father’s formal education, iv) Mother’s formal

education, v) Father’s occupational prestige, v) Mother’s occupational prestige.

Biological Background Influences: 1) family medical history, ii) family athletic history, iii) neonatal medical

history, iv) prenatal nutrition, v) mother toxic substance use during pregnancy (including alcohol & cigarettes).

Family Background Influences: i) birth order, ii) number of parents. iii) authoritarian/democratic childrearing,

iv) family health practices, v) family social practices.

Sociocultural Background Influences: i) cultural health practices, ii) cultural toxic substance

proscriptions/prescriptions, iii) cultural nutritional habits, iv) cultural proscriptions/prescriptions concerning

social relations, v) cultural value on codified information (e.g., education).

Smoking Models: i) parental smoking, ii) older siblings’ smoking status, iii) peer smoking, iv) smoking by admired

adults.

Social Support for Chosen Lifestyle: i) verbal parental support, ii) peer support through group inclusion.

Media Pro-smoking Messages: i) cigarette smoking improves self-image, ii) cigarette smoking is “normal”, iii)

cigarette smoking buffers social and psychological stress, iv) cigarette smoking is not physically hazardous.

Personal Goals and Needs: I) need for achievement, ii) need for autonomy, iii) need for affiliation, iv) need for

social dominance, v) need for security.

Perceived Psychosocial Well-being: i) self-reported social harmony, ii) self-reported enthusiasm.

Perceived Smoking Norms: i) the majority of people smoke, ii) smokers are more engaged with life than nonsmokers.

Perceived Physical Well-being: i) self-reported endurance, ii) self-reported vigor, iii) self-reported incidence

of illness.

Perceived Self-Efficacy: i) self-rated leadership ability, ii) expectation of success at novel tasks, iii)

internality/externality as measured by locus of control scale.

15. Cognitions about Consequences of Smoking: i) enhances self-confidence, ii) enhances social dominance, iii)

enhances vigilance, iv) reduces stress reaction, v) enhances solidarity.

16. Smoking Behavior: i) measure of alveolar carbon monoxide, ii) self-reported smoking (daily), iii) self-reported

smoking (weekly), iv) intention to smoke in future.
older adolescent experimenters, family influences will decrease in

importance relative to the importance of specific cognitions about

the contribution of smoking to one's perceived self-efficacy and

psychosocial well-being.

When enough measurement models have been tested to provide a

rigorous meta-analytic test of the structural model, an attempt

should be made to construct a computer simulation that would

provide point estimates of smoking prevalence by the age, sex,

socioeconomic, and cultural status of defined adolescent

populations. When the results of such a computer simulation

correspond well to the published results of most of the smoking

prevention programs, then and only then could we say that we knew

enough about why adolescents adopted cigarette smoking to justify

the effort to institute a large-scale smoking prevention program.

We have to know more than we do presently about why teenagers

elect to take up the cigarette smoking habit to make it

politically feasible to engage in the arduous and expensive effort

of disseminating a consensus smoking prevention program

nationwide.

FOOTNOTE

1. The Bogalusa study (Baugh et al. 1982) suggests that Black

adolescent smokers may overwhelmingly prefer a popular,

mentholated brand of cigarettes over "brand X". "Brand X" may be

the generic cigarette among U.S. youth only for anglos.

Interestingly, Chapman and Fitzgerald (1982) found that a majority

of teenage smokers in Sydney, Australia were found to prefer a

local brand having a public image similar to that associated with

"brand X" in the United States.

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AUTHOR

William J. McCarthy, Ph.D.

UCLA Psychology Department

Los Angeles, CA 90024

169
Methodological Issues in

Research on Smoking Prevention

Anthony Biglan, Ph.D., and Dennis V. Ary, Ph.D.

In the past several years, smoking prevention research has

provided encouraging evidence that the onset of adolescent

smoking can be deterred. The papers by Botvin and Wills and

by Glasgow and McCaul in this monograph review evidence of

the efficacy of programs which focus on establishing life

skills. The papers by Flay and by Lando review evidence for

programs that concentrate on teaching skills for refusing

cigarettes. Programs that are based on a developmental

perspective are discussed in papers by Glynn and by McCarthy.

It is perhaps inevitable, however, that yesterday's successes

prompt the identification of today's methodological problems.

This paper discusses five facets of the methodology of

research on smoking prevention. It begins with a discussion

of statistical and design issues. Second, "passive" consent

procedures, in which parents respond to statements of informed

consent only if they do not wish their child to participate in

the research, are discussed. It is argued that valid

assessments of prevention programs would be virtually

impossible without such consent procedures. Third, issues

surrounding the construct validity of interventions and the

presumed mediators of their effects are discussed. Particular

attention is given to the need for multimethod assessments of

behavioral skills and social contingencies that prevention

programs purport to affect. Fourth, the validity of subject

smoking behavior measures is examined. Finally, the

implications of subject attrition for the validity of

prevention studies are described, and some relevant data are

presented.

DESIGN AND STATISTICAL ISSUES

In smoking prevention research, a whole school has typically

been the unit of random assignment. This approach has been

widely adopted because it allows interventions aimed at the

schoolwide modification of group norms--an effect that cannot

be achieved if individual subjects or classrooms within

schools are assigned to treatment and control conditions. In

addition, the assignment of a whole school to one condition

avoids the reduction of intervention effects that may occur

when treatment and control subjects interact and affect each

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others' smoking. However, since financial and logistical

constraints have tended to limit the sample size, the

statistical power of whole-school designs is usually not as

high as might be desired. Two strategies which address this

situation are discussed in this section. First, the

statistical power can be enhanced by blocking or matching

schools on categories related to the outcome measure prior to

randomization. Second, a common response to the poor power of

designs in which schools are assigned to conditions has been

to analyze the data using individuals as the units of

analysis. The implications of this strategy are noted. It is

concluded that using means that are calculated over classrooms

is preferable to using individuals as the unit of analysis.

Blocking or Matching Prior to Randomization

One method to enhance the ability of a design to detect

treatment effects is to reduce the error variance by blocking

or matching units on one or more variables prior to random

assignment. In addition, this allows block effects and

treatment by block interaction effects to be tested. An

interaction which reveals that a treatment is more effective

at some levels of a blocking factor than at others may be of

particular interest. For example, where schools are blocked

according to their ethnic and socioeconomic makeup, treatment

may be found to be more effective among middle class whites

than among other groups. Blocking enhances the power of a

design because estimated treatment effects are based on the

differences between groups within each block. Error variance

decreases as the correlation between the blocking variable and

the posttest dependent variable increases, and as the

within-block homogeneity increases. On the other hand, each

additional level in the blocking variable reduces the degrees

of freedom in the error term. Myers (1979) provides a good

summary of the relationships among sample sizes, the

correlation between the pretest blocking variable and the

outcome variable, and the number of treatment groups. In

addition, he presents a simple method to determine the optimal

number of blocks in a given design situation. Maxwell,

Delaney, and Dill (1984) present Monte Carlo data which

indicate that analysis of covariance of randomized block data

yields enhanced statistical power and precision over that

obtained with analyses of variance of randomized block data.

Consequently, they recommend the use of analyses of covariance

with such stratified samples.

Graham et al. (1983) suggest a useful method for blocking

schools when there are a relatively small number of schools to

be assigned to conditions. In brief, their procedure reduces

a set of blocking variables to a single "treatment

enhancement" blocking factor, which is a weighted combination

of factor scores derived from the original set of blocking

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factors. The weights are assigned based on experimenter

estimates of each factor's impact on program effectiveness.

The units are then ranked on the composite blocking factor and

dichotomized into "enhance" and "hinder" groups. Units from

each group are randomly yoked together, then randomly assigned

to condition. The primary benefit of this procedure is that

it enhances confidence that the experimental groups are

comparable on a wide range of potentially confounding

characteristics. It should be mentioned that, with this

procedure, group comparability is improved, but is not

guaranteed.

It could be noted that the enhancement of group comparability

might be preserved, and the error term reduced, by omitting

the yoking procedure if design circumstances permit. That is,

the units should be blocked based on the composite blocking

factor, and then randomly assigned to conditions within each

block. This modification of the Graham et al. (1983)

procedure retains the blocking variable as a factor in the

design, which allows treatment effects to be estimated from

between-group differences within each level of the block.

This blocking approach will yield a reduction in error

variance, while providing for group comparability on the

composite factor.

An alternative to the randomized block design is the

"alternate ranks" procedure (Dalton & Overall, 1977). This

approach is not based on randomization principles, but

attempts to equate comparison group means on a concomitant

variable or composite. First, the units are ranked on the

concomitant variables and are alternately assigned to

condition (e.g., ABBAABB). Maxwell et al. (1984) present

Monte Carlo evidence which indicates that this method of

assignment, in conjunction with Ranks Analysis of Covariance

(Dalton & Overall, 1977), sometimes yields somewhat better

statistical power and precision compared to randomized block

designs. This is true only when the outcome measure and the

concomitant measure are linearly related and the sample size

is relatively small, however.

Quasi-Experimental Methods and Aggregation at the Classroom

Level

As noted above, the cost of carrying out schoolwide

interventions in smoking prevention research has tended to

restrict the number of schools randomly assigned to each

experimental condition. As a result, the statistical power to

detect treatment effects has been limited in these studies.

This situation is particularly acute when treatment effects

are not large.

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One approach employed to circumvent this dilemma uses a unit

of analysis that is smaller than the unit of assignment. This

approach provides more degrees of freedom, and thus greater

statistical power for the analysis. The individual has

typically been used as the unit of analysis despite the fact

that schools have generally been the unit of randomization.

Recall, however, that the intent of the random assignment

process is to increase the probability of comparison group

equivalence on confounding variables. Group equivalence on

confounding variables increases as the number of randomized

units increases. For example, the assignment of 100 schools

to conditions, rather than four schools, is much more likely

to result in equivalence among treatment and control

conditions on confounding variables. When data from four

randomly assigned schools are analyzed using the individual

(e.g., N = 800) as the unit of analysis, much greater

equivalence on pretest variables (e.g., student smoking) and

confounding historical events is assumed than is actually the

case. Consequently, it should be recognized that this

procedure converts what was a true experimental design with

schools as the unit of analysis to a quasi-experimental

design.

In order to accept findings based on such quasi-experimental

methods, we must be in a position to reasonably rule out the

possibility that treatment group differences might be due to

confounding variables or events, rather than to treatment

effects. One must confront and control for two types of

potential confounds: the problem of preexisting group

nonequivalence on variables related to the outcome measure(s)

and the possibility of differential history effects (Cook,

this monograph).

Controlling for preexisting differences on related variables

is the more straightforward of these tasks. Previous smoking

research has provided information about the variables

correlated with smoking. Consequently, these variables can be

assessed with reasonable reliability at pretest, and

adjustment for nonequivalence can be accomplished using

analysis of covariance or analysis of variance with blocking

methods. However, as Cook (this monograph) points out,

on-site monitoring of local (e.g., school) events that might

affect student smoking is necessary in order to attempt to

control for their impact on smoking. It can be a difficult

task to anticipate and monitor all possible historical

confounding factors. For example, a sudden and undetected

increase in the use of chewing tobacco could affect smoking in

a specific school. The impact of such an event is random

across schools, but is clearly not random across the

individuals used in the quasi-experimental analysis.

Consequently, a valid quasi-experimental analysis must have

monitored and successfully detected such historical events in

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order to be confident that adequate adjustment can be

accomplished. In sum, the use of the above adjusting

strategies is only appropriate when the researcher is

reasonably certain that the relevant pretest measures and

on-site monitoring variables have been reliably assessed.

If the researcher is in a position to appropriately adopt a

quasi-experimental approach, the use of the aggregate

classroom mean as the unit of analysis provides certain

advantages over the practice of using individual subject

scores. For several reasons classroom means result in a

statistical adjustment that makes the assumption of

post-adjustment comparison group equivalence of both pretest

and historical confounding factors more tenable. This is due

in part to the fact that the precision for both the analysis

of covariance and the blocking adjustment techniques is

dependent upon a substantial correlation between the adjusting

variable(s) and the dependent measures. In addition, both

adjusting methods can result in biased estimates of treatment

effects by either correcting too much or too little for

pretest differences on the adjusting variables. It is both

this correlation and the biasing effects of random measurement

error on the adjusting variable that we specifically want to

address relative to smoking research.

First, regardless of the adjustment method employed, an

aggregate dependent measure such as the classroom mean will be

more stable than an individual score. This greater

reliability is particularly important to the reduction of

measurement error in relatively unstable questionnaire

self-reports from children and adolescents. When measurement

error is reduced, there is less random noise in the dependent

variable, which results in a lower error term in the analysis

of variance.

Secondly, the use of an aggregate variable to provide

statistical adjustment for pretest group nonequivalence and

for specific effects of history results in greater adjustment

than would be obtained using individual subject data. This is

true because the greater reliability of aggregate data results

in a higher correlation between the more stable adjusting and

outcome measures. For example, in our smoking research with

adolescents, the correlation between pretest self-reported

smoking and one-year posttest self-reports were .47 for

individual and .67 for classroom means. Classroom means

clearly provide a larger, more precise adjustment for pretest

nonequivalence, which results in a substantially smaller error

variance in the analysis.

Third, a concern when employing quasi-experimental methods

which attempt to adjust for pretest differences is that the

adjustment method may yield a biased estimate of treatment

174
effects. An important source of such bias is the measurement

error of the adjusting variable(s) (Cronbach et al. 1977).

Because aggregating by classroom reduces measurement error in

the adjusting variable, it is less likely to yield a biased

estimate of treatment effects.

In summary, it is always preferable to retain the unit of

random assignment as the unit of analysis. However, if the

researcher has determined that it is appropriate to adopt a

quasi- experimental approach, we suggest that the unit of

analysis be the classroom mean, rather than the individual

subject. For most research applications, the use of the

classroom mean usually furnishes ample degrees of freedom to

detect treatment effects, while enhancing confidence that the

requisite assumptions for the analysis have been met. It does

so by reducing measurement error in the dependent variable,

which yields a smaller error term, and by providing an

adjustment for pretest group nonequivalence and for

differential effects of history. The approach is thus more

precise and less subject to bias than that provided by using

the individual subject as the unit of analysis in

quasi-experimental designs.

THE NEED FOR "PASSIVE" CONSENT PROCEDURES

"Passive" consent procedures are essential for valid research

on smoking prevention. Passive procedures involve mailing

parents written statements of informed consent and asking them

to respond to the informed consent only if they are unwilling

to have their children participate in the study. Failure to

reply is taken to be passive consent for the children to

participate. The alternative, "active," procedure requires

that parents indicate their willingness to have their children

take part in the study before they can participate. A major

problem with active procedures is that many parents fail to

respond, not because they object, but for unrelated reasons,

such as loss of form or forgetting. This subject loss may

bias study results.

Severson and Ary (1983) found that the passive consent

procedure produced a more representative sample of adolescents

than did an active consent procedure. They were required by

the school district with which they were working to obtain

active consent from parents before allowing students to

participate in the study. However, this requirement was only

imposed for assessments of smoking that included the

collection of expired air carbon monoxide and saliva

thiocyanate. They were thus able to later obtain a

questionnaire assessment of all students, although

physiological assessment could not be obtained. Students

whose parents had given consent were compared with those whose

175
parents had not consented. Students whose parents consented

were significantly less likely to report cigarette and

marijuana smoking although there were no differences in

alcohol consumption. According to students' reports, the

fathers of subjects for whom consent had been obtained were

less likely to be smokers. Consent students were less likely

to associate with teenage girls who smoked. Finally, the

educational level attained by fathers and mothers of students

who participated in the study was greater than that of

students who did not participate. Thus, the Severson and Ary

(1983) results suggest that the use of passive consent

procedures will produce a more representative sample of

students than will an active consent procedure.

There are at least two ways that requirements for active

consent could affect the validity of smoking prevention

studies. First, the statistical power of studies would be

weakened because a smaller proportion of subjects will be

smokers and study participants will probably have a lower risk

of becoming smokers. Thus, only the most powerful effects

will be detectable. Second, the external validity of these

studies will be impaired, since it appears that the

individuals at greatest risk for smoking will be less likely

to participate in the study.

It is thus essential to employ passive consent procedures in

studies of this sort. Such an approach is not incompatible

with a concern for the rights of subjects. In addition to

sending statements of informed consent to parents, students

can and should give informed consent. The risks and benefits

of participation in the study should be described at least

several days before the assessments are actually carried out

in the classroom. At that time, and at the time of each

assessment, students should be told in simple terms about

their right not to participate in the assessment if they so

choose. A child's refusal should be met with warm acceptance

by assessment team members. It should be agreed in advance

with school personnel that a child's refusal to participate in

assessments will not result in any negative consequences to

him or her. Such procedures have been widely used in smoking

prevention research in recent years. There have been no

reports of objections to their use in studies in at least five

locations.

THE CONSTRUCT VALIDITY OF INTERVENTIONS AND PRESUMED MEDIATORS

OF TREATMENT

McCaul and Glasgow (1983) reviewed available smoking prevention programs in terms of the construct validity of their

interventions. They concluded that little is known about what

are the essential components of successful programs because

most studies rely on designs that simply contrast a complex

176
treatment with no treatment; component analyses have generally

been lacking. Cook (this monograph) presents a cogent

argument for making components analysis research and research

on mediating processes a lower priority than testing whether

prevention programs as a whole affect adolescent smoking. Yet

it is relatively inexpensive to do small-scale studies of the

effects of specific components on processes that are presumed

to mediate program effects. Although such knowledge may not

be necessary to the achievement of preventive effects, it

could contribute to this goal by clarifying which intervention

components are necessary and sufficient for preventing smoking

and by elucidating how programs produce their effects.

To the extent that such research is pursued, there are a

number of things that would refine it: a) clarification of

the treatment constructs and their operations, b) abandonment

of the almost total reliance on questionnaire measurement of

presumed mediating processes, c) assessment of refusal skills,

and d) measurement of the effects of interventions on the

social contingencies for smoking.

Specification of Intervention Constructs and Operations.

More precise specification of the treatment constructs and the

operations associated with prevention programs is needed in

order to learn what works and what does not. All of the

recent prevention programs have been based on more than one

treatment construct. For example, while most programs focus

on teaching peers to resist pressures to smoke, they often

have a component that prompts adolescents to make a public

commitment not to become a smoker (e.g., Flay et al. 1983) and

they routinely include information about some health

consequences of smoking (e.g., Perry et al. 1980). This is

appropriate, since it seems unlikely that single component

treatments will significantly affect the onset and maintenance

of adolescent smoking (Bry 1983). Nevertheless, it is common

to talk about treatments as though they have a single

component. In discussions of the apparent successes of

smoking prevention programs, we need to acknowledge that the

treatments have multiple components. As McCaul and Glasgow

(1983) point out, until process and component analyses are

conducted we cannot accurately determine the active

ingredients of a complex intervention. The papers in this

monograph help to clarify what treatment constructs are

associated with existing prevention programs.

Programs designed to teach peers to resist pressures to smoke

have utilized a variety of actual interventions, from the

presentation of film-mediated models (Evans et al. 1983), to

role-play practice in the classroom (Perry et al. 1980), to

rapid-fire practice of refusal responses to film-mediated

offers of cigarettes (Biglan et al. 1985). These

177
procedures are markedly different. The literature on social

skills training indicates that these procedures do not have

the same effects (cf. McGuire and Thelen 1983). Thus, the

presentation of models of refusal skills will probably not

have the same impact as the provision of behavioral rehearsal.

It seems more appropriate to consider each of these

interventions as a separate treatment construct. For example,

presentation of models constitutes one treatment, while

behavioral rehearsal of refusal skills constitutes another.

As McCaul and Glasgow (1983) suggest, it may be fruitful to do

smaller-scale studies of the effects of each type of

intervention on directly assessed social skills. In

particular, these methods of teaching refusal skills might be

compared for their effects on young peoples' skill in analogue

role play tests.

In enumerating treatment constructs, investigators have

generally ignored the social consequences that their programs

provide for smoking behavior and for verbal statements in

favor of and opposed to smoking. For example, when students

state public commitments to not smoke or practice refusal

behaviors, they receive attention and praise. When they

discuss smoking with their parents, they presumably receive

attention and approval for statements of antismoking

positions. Given the powerful effects of social consequences

that have been demonstrated in numerous other areas of

research (cf McGinnies 1970; Kazdin 1978), explicit attention

to how programs affect the social contingencies for smoking

should lead to more effective interventions.

A Monomethod Bias in the Assessment of Mediating Processes.

Despite the focus of prevention programs on the modification

of refusal skills and the contingencies for smoking,

assessment of the factors that are presumed to mediate the

effects of treatment disproportionately involves questionnaire

measures of cognitive constructs. The cognitive constructs

that are examined include attitudes, belief, values, and

behavioral intentions (Flay et al. 1983), self-efficacy

expectations (McAlister et al. 1983), locus of control, selfimage, and need for acceptance (Botvin and Eng 1980). At the

same time, few studies of prevention programs have directly

evaluated the social or resistance skills of adolescents, and

none have examined whether the social contingencies for

smoking have changed following intervention.

The emphasis on questionnaire measures is an example of a

monomethod bias (Cook and Campbell 1979). Questionnaires are

much easier to administer than other forms of assessment.

Given the demand for huge numbers of subjects to test the

effects of prevention programs, direct assessment of the

social skills of all subjects would be prohibitively

178
expensive. Moreover, there is a strong tradition of using

questionnaires to assess cognitive constructs. This tradition

has seldom been questioned until recently. There is now,

however, growing reason to doubt that people's responses to

questionnaire items get at the cognitive factors that underlie

their behavior. For example, Nisbett and Wilson (1977)

reviewed the evidence on the accuracy of self-reports of

cognitive processes. They concluded that such reports do not

necessarily reflect cognitive processes, but are statements of

the subject's own "implicit causal theories, or judgments

about the extent to which a particular stimulus is a plausible

cause of a given response" (Nisbett and Wilson, p. 231, 1977).

Continued assessment of cognitive constructs requires the

development of more sophisticated theoretical models. For

example, at what point are the behavioral intentions which are

thought to lead to smoking considered to occur? Do they

literally occur just prior to a young person taking his or her

first cigarette? Or are they more abstract characterizations

of a person's tendency to smoke? If they are tendencies, in

what way can they be thought to cause smoking onset?

Clarification of these theoretical issues would help to

specify what additional methods of measurement would be

appropriate to assess the' constructs. For example, if we

believe that behavioral intentions function as antecedents to

experimentation with cigarettes, then we should find that

young people are able to describe these intentions in

interviews that occur prior to the onset of smoking. As

another example, if improving a young person's self-image is

thought to decrease the likelihood of his or her smoking, then

it would be useful to show that smoking prevention programs

produce changes in a child's directly observed behavior that

are consistent with the construct of an improved self-image.

This example reveals, however, a need to further elucidate the

specific behavioral referents of the self-image construct

before behavioral measures of that construct can be specified.

Multimethod assessment of refusal behavior. The social skills

literature makes it clear that questionnaire reports of social

behavior do not necessarily converge with more behavioral

measures of social skill (Bellack 1979; Dow et al. in press;

Glasgow and Arkowitz 1975). Recently, several investigators

have developed behavioral assessments of adolescent social

skills that are relevant to smoking. Hops et al. (in press)

developed a taped situations test of young people's skill in

refusing offers of cigarettes. Via audiotape, the test

presented 26 social situations involving pressures to smoke.

The situations were chosen to be representative of the social

pressures to smoke that adolescents encounter. The choice of

situations was based on an earlier study of the situations in

which young people begin smoking (Friedman et al. in press).

179
The subjects heard a narrator describe the situation, heard

some conversation among adolescents, and then heard one of the

adolescents offer a cigarette. Subjects were instructed to

respond as though actually in the situation. Their responses

were tape recorded for later coding.

The taped situations test was used to assess the impact of a

refusal skills training program among seventh graders. The

assessment occurred six months after the intervention.

Sixty-eight seventh graders were recruited from among those

who had received the prevention program and 63 were recruited

from among those who had not received the program. Subjects

who received refusal skills training (and the other components

of the smoking prevention program) refused the offered

cigarette significantly more often than students in the

control condition. They also gave more excuses and cited

possible external consequences for smoking (e.g., "I'll smell

bad") more frequently. Treated subjects had significantly

longer total response times, and tended to have shorter

latencies to respond. It should be noted, however, that the

Hops et al. study does not provide evidence that the refusal

skills that were assessed were actually being used in

real-life situations. Indeed, existing evidence suggests that

such behavioral samples do not necessarily predict behavior in

real life settings (Bellack 1979). Nevertheless, the study

does confirm that the smoking prevention program had an impact

on the ability of young people to engage in refusal behavior

and is thus consistent with the hypothesis that the prevention

program altered refusal skills.

Schinke and Gilchrist (1983) and Gilchrist and Schinke (in

press) have reported on the use of a similar behavioral

assessment methodology to evaluate the effects of a smoking

prevention program. The assessment procedure requested that

subjects role play coping with social pressures to smoke. A

confederate played the part of the person making the offer.

Interactions were videotaped for later rating of verbal and

nonverbal behavior. Schinke and Gilchrist (1983) found that

sixth-grade students who had received a prevention program

that included interpersonal skills training performed better

on this assessment than did students who received no program.

They made more eye contact, used more personal pronouns, said

"no" more frequently, and asserted their right not to smoke

more often. Gilchrist and Schinke (in press) used a measure

of social skills that was a composite of all the behavioral

dimensions that they had coded. Students who had received a

program that included training in social skills and other

self-control skills outperformed students who had received no

program, as well as students who received a smoking prevention

program that involved discussion about tobacco and smoking,

but no skills training.

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Multimethod assessment of the social contingencies for

smoking. To the extent that prevention programs are intended

to have an impact on the social contingencies for smoking, it

would be valuable to assess these processes. For example, how

often are subjects exposed to peer models of smoking? To what

extent do young people talk about cigarettes? Are

conversations about cigarettes functioning to reinforce

positive attitudes towards cigarettes or to punish them?

Similarly, where prevention programs target parents (Flay et

al. 1983), evidence regarding parent modeling and

reinforcement of adolescents' prosmoking behavior would be

useful. In most prevention studies, only questionnaires have

been used to get at these processes. Subjects have simply

been asked whether their parents and friends smoke. Questions

have not been asked about the frequency and nature of

conversations regarding cigarettes.

To assess some of these processes, we have developed a phone

probe procedure. A small sample of treatment and control

subjects was recruited and called once each month over a

period of six months. In brief interviews each subject was

asked to describe any conversations he or she may have had

with parents, siblings, or peers regarding cigarettes. It is

hoped that, by reducing the period of time between such

conversations and the report of them, more accurate

information can be obtained. In this way, we hope to further

delineate the effects of our intervention on the social

contingencies that shape and maintain pro- and anti-smoking

attitudes toward cigarettes.

It would also be valuable to develop direct behavioral

assessments of these interactions. To our knowledge, no one

has done this. Samples of young people in treatment and

control conditions might be asked to engage in discussions

regarding cigarettes that could be videotaped for later

coding. The conversations could be coded for the frequency of

prosmoking attitudinal statements, the frequency of stated

intentions to smoke, and the occurrence of positive

reinforcement and punishment for such verbal behavior. While

the low base rate of smoking might make it difficult to

investigate the degree to which such samples of behavior

predict later smoking, one would expect that treatment and

control subjects would differ in the way they talk about

cigarettes. This same methodology could be used to assess the

impact of parent interventions on the ways in which those

parents discuss smoking with their children.

It should also be noted that the smoking prevention programs

that teach social skills implicitly legitimize the use of such

skills. That is, when a young person practices refusal skills

and observes fellow students doing so, it presumably

establishes those skills as appropriate behavior for smoking

181
pressure situations. It would be useful to determine whether

the rated acceptability and appropriateness of the refusal

behaviors increases as a result of treatment. That is, do

young people who have been through a prevention program see

such refusal behavior as more appropriate than those who have

not received such an intervention?

THE VALIDITY OF MEASURES OF SMOKING BEHAVIOR

A good deal of progress has been made in achieving valid

measures of smoking behavior.. First, it has been demonstrated

that adolescents' questionnaire reports of smoking are

increased when the adolescents are told that a valid

physiological assessment of their smoking is also being

obtained (Evans et al. 1977). Bauman and Dent (1982) have

found that these increased self-reports come from students who

are in fact higher in expired air CO levels. However, Arkin

et al. (1983) failed to replicate increases in self-reported

smoking using a slightly different procedure. Second, two

physiological measures have been identified that have some

validity in the assessment of adolescents' smoking. Pechacek

et al. (1983) examined the relationships of saliva thiocyanate

(SCN) and expired air carbon monoxide samples to self-reports

of smoking among 2,200 junior and senior high school students.

Both physiological measures were moderately correlated with an

index of self-reported smoking (r =.69 for CO; r =.52 for

SCN). When the sample was subdivided according to age, the

validity coefficients were lower for the 11- through

13-year-olds than for the older subjects. In our own work

(Biglan et al. in press) we were able to replicate the

Pechacek et al. findings for carbon monoxide but not for

saliva thiocyanate (See table 1). In addition, we examined

the possibility that the existence of a sizable number of

marijuana smokers among our sample might alter the correlation

between carbon monoxide and self-reports of cigarette smoking.

Self-reported cigarette smoking was significantly correlated

with CO even after the variance due to self-reported marijuana

smoking was removed (increment in R2 = .39). Thus, it appears

that the existence of marijuana smokers in samples of

adolescents does not substantially undermine the validity of

expired air CO in the assessment of smoking.

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TABLE 1

Correlations Between Self-Reports of Cigarette and Marijuana

Smoking and Expired Air CO

Number of Cigarettes in Last Week

All Subjects (N = 1123) .71

Grade 7 (N = 454) .51

Grade 9 (N = 342) .75

Grade 10 (N = 149) .67

Grades 11 & 12 (N = 178) .80

Number of Times Marijuana Smoked in Last Week

Simple r .36

Increment in R2 when Marijuana Smoking

entered after Cigarette Smoking .005

Increment in R2 when Cigarette Smoking

entered after Marijuana Smoking .386

The reasons for our failure to replicate the findings of

Pechacek et al. (1983) with SCN are unclear. It may have been

that our saliva samples deteriorated during the period in

which they were stored. Prue et al. (1981) found that

samples deteriorate when stored in containers that are not

airtight, and some of our containers came open. Considering

that, in a separate study, Pechacek et al. (1983) found that

the consumption of leafy vegetables produces substantial

increases in thiocyanate, our subjects' dietary intake could

also account for some of the error.

Given available evidence, the expired air CO measure would

appear to be preferable to SCN for validation of smoking

behavior. However, expired air CO has a short half life--as

short as four hours (Benowitz 1982)--and the CO levels will be

low for persons with lower smoking rates and for persons whose

puff topography exposes them to less smoke per cigarette

(Frederiksen & Martin 1979; Burling et al. 1983). This means

that CO will be insensitive to smoking that occurred more than

24 hours before sample collection. Cotinine has been

suggested as a measure that might have greater specificity

than SCN and a longer half life than the expired air carbon

monoxide. The difficulty with this measure has been the high

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485-051 O - 85 - 7
cost of its procurement. Best and Pechacek (personal

communication 1983) have suggested a procedure that could

reduce the cost of this assessment by pooling some of the

saliva from a number of subjects who have indicated on

questionnaires that they do not smoke. Validation of cotinine

using this procedure has not been reported to date.

The Detection of Low Rate Smoking

While studies of the validity of smoking measures are

encouraging, it should be noted that none of these measures

assess the type of low-rate smoking that has been the target

of most prevention studies. For example, a number of studies

have reported beneficial effects of programs on self-reported

experimentation with cigarettes (e.g. Botvin and Eng 1982).

To date, evidence does not demonstrate that such low levels of

smoking can be accurately detected. Similarly, demonstrations

that physiological assessments increase self-reported smoking

have not specifically assessed whether the accuracy of reports

of experimentation is increased. Thus, one cannot infer the

validity of measures of self-reported experimentation on the

basis of the extant evidence. For this reason, we cannot be

as confident about the validity of studies which show the

prevention of experimentation as we can about studies showing

the prevention of higher levels of smoking.

The Importance of Studying Endpoint Smoking

The last point underscores the importance of examining the

effects of prevention programs on "endpoint" smoking. The

concept was first suggested by Terry Pechacek (personal

communication 1983). Endpoint smoking might reasonably be

defined as the presence of high-rate smoking at the end of the

high school career. Further, "high-rate" smoking might be

defined as that level of daily smoking that is so high that it

is very unlikely that the person will stop smoking. Only

further research will determine that level. The ultimate

question for smoking prevention programs is whether they

prevent endpoint smoking. Demonstrating an effect on endpoint

smoking would increase confidence that our prevention programs

are actually contributing to a reduction in the risks of

morbidity and mortality that are associated with smoking.

None of the studies to date have assessed the impact of

programs on endpoint smoking. This statement is not a

criticism of those studies, since it would have been premature

to invest the large sums of money needed to examine such an

impact prior to the existence of some evidence that adolescent

smoking might be preventable. But, the very successes of

those programs make it timely to inquire about likely effects

of our programs on endpoint smoking.

184
Current successes may not necessarily translate into an effect

on endpoint smoking. There is evidence that large numbers of

young people (as many as 29.8%) smoke cigarettes regularly and

quit at some later point (Johnson 1982). In our own work we

have found a significantly lower smoking rate among

adolescents that stop smoking six months later, F(1,79) =

12.52, p < .OOO1) and one year later, F(1,61) = 5.14, p <

.027) than among adolescents that continue to smoke.

Moreover, as table 2 shows, the smoking rate of smokers in

seventh grade is significantly lower than it is for those in

upper grades. Thus, studies that show that low-rate smoking

of seventh graders has been prevented do not necessarily mean

that endpoint smoking will be deterred. At the same time,

there is evidence that measures of experimental smoking do

predict later higher-rate smoking (Ary et al. 1983). Thus,

the deterrence of experimentation and low-rate daily smoking

probably has some value for reducing endpoint smoking.

TABLE 2

Number of Self-Reported Cigarettes Smoked by Grade Level

Grade Number of Smokers

7 52

9 42

10 20

11 & 12 29

Mean Number of Cigarettes

in Past Week

16.4

38.6

48.6

42.4

Note: Difference among grades, F(3,135) = 3.76, p .012.

Grades 7 and 10 differ significantly according to a Tukey

HSD test.

These considerations point to several important requirements

for further research on smoking prevention. First, follow-up

of subjects, at least through their high school careers, is

needed to document that endpoint smoking is indeed affected.

As we discuss below, the serious problem of subject attrition

will need to be overcome in order for such follow-up to be

185
meaningful. Second, studies are needed which focus on the

transitions from lower levels of smoking to higher levels.

What is the prognostic significance of a given rate of smoking

or a given topography for endpoint smoking, and what factors

affect these transitions? Third, the impact of our programs

needs to be examined separately for distinct categories of

adolescent smoking status. For example, we should not assume

that preventing those who have never smoked from beginning to

experiment implies that current experimenters have been

prevented from becoming regular smokers. To some extent this

is being done now. For example, Flay et al. (1983) looked at

the effects of their smoking prevention program on each of the

following groups: a) those who had never smoked, b) those who

reported having smoked but had quit, c) those who reported

experimenting, but smoked less than one cigarette per week,

and d) regular smokers, defined by self-reports of smoking at

least once a week. As studies of the transitions to regular

smoking accumulate, the practical significance of effects on

each of these groups will become clearer.

The Value of Studying Adolescent Cessation

There may be particular benefit in studying cessation among

adolescents who are already smoking regularly. Some of the

success of prevention programs may be due to their prompting

smokers to quit. At least two prevention programs have shown

effects on students who were already smoking regularly at

pretest assessment (Biglan et al. 1985; Flay et al. 1983; Ryan

et al. 1983). While other prevention programs may have

affected those subjects who were already regular smokers, it

is difficult to be certain, because the analyses combined

subjects who were smoking regularly at pretest with those who

were not (cf. Evans et al. 1983). Regular adolescent smokers

often desire to quit (Biglan & Lichtenstein in press) but they

encounter continuing social influences to smoke (Kniskern et

al. 1983; Biglan et al. in press). Skill in refusing

cigarettes could thus facilitate cessation for those who are

already smoking.

These considerations suggest an alternative research strategy.

Regular smokers might be identified and randomly assigned to

programs like those of Flay et al. (1983) and Biglan et al.

(in preparation) or to control conditions. There are at least

three advantages to such a research strategy. First, this

group of smoking adolescents has the highest risk of emerging

from their high school careers as regular smokers (Ary et al.

1983); deterrence of their smoking is of paramount importance.

Second, such a strategy would allow random assignment of

individuals rather than whole schools to conditions, thus

avoiding some of the vexing statistical power problems we just

described. Third, the cost of such studies would be far lower

186
than the massive multischool

programs.

evaluations of prevention

ATTRITION: A THREAT TO EXTERNAL AND INTERNAL VALIDITY

Attrition rates in studies of smoking prevention have been

relatively high. For example, Murray et al. (1983) reported a

10.7% attrition rate among junior high school students at nine

months and a 28.9% attrition rate at a 21-month follow-up. In

the study we conducted (Biglan et al. 1985), 17.5%

of middle school students had dropped out at 6 months and 25%

were missing at one year. For subjects in high school the

rates were 17.9% at six months and 38% at one year.

External Validity

Hansen et al. (1983) have called attention to the threats to

internal and external validity that subject attrition poses to

evaluations of smoking prevention programs. They suggest two

questions regarding the possible effects of attrition on

external validity. First, they ask whether pretest scores for

dropouts differ from those of subjects who stayed in the

program. Second, when assessments are available from subjects

from the first two of three assessments, they ask whether the

pattern of change in use of substances for those who have

dropped out by Time 3 differ from the patterns of those who

have remained. They examined these issues for two studies of

cigarette and drug prevention that had been conducted by the

Health Behavior Research Institute. For both projects they

found that students whose data were missing at posttest and at

one-year follow-up were significantly more likely to have

reported use of cigarettes, alcohol, and marijuana at Time 1,

with the exception of alcohol consumption at one-year

follow-up in one study. With respect to the second question,

they found that subjects who reported use of cigarettes during

either or both of the first two assessments were more likely

to be missing by the third assessment. A similar pattern was

found for users of alcohol and marijuana in one of the

studies, but not in the other. Thus, the students who

remained in the study were significantly less likely to be

users of cigarettes, alcohol, and marijuana than were those

who dropped out. At least for these two studies, it appears

that the results may not be generalizable to all students.

We were prompted by Hansen et al.'s findings to examine

whether the dropouts in our own prevention research differed

systematically from those who remained in the study. A

Multivariate Analysis of Variance (MANOVA) comparing dropouts

and remainers yielded a significant overall effect, confirming

that the threats to external validity that Hansen et al.

(1983) identified are not unique to their studies. Table 3

presents comparisons of missing and remaining subjects.

187
Subjects who were missing were significantly more likely to

report cigarette smoking, alcohol consumption, and marijuana

use at the Time 1 assessment. The parents of dropouts were

significantly more likely to be smokers; so too were the peers

and siblings. Two questions were designed to assess the

subjects' intentions to smoke. On both of these items the

dropouts were more likely to indicate that they expected to be

smoking at some time in the future. The parents of missing

subjects had had less education than those of remaining

subjects, and the missing subjects had lower education

aspirations. Finally, the missing subjects reported that they

received more offers of cigarettes per week than did the

remainers.

Table 3

Significant Differences Between Missing and Remaining Subjects

Cigarette and Other Substance (Self-Reported) Use

On the basis of these results and those of Hansen et al.

(1984), it appears likely that those who drop out of

prevention studies are precisely the young people who are most

in need of a prevention program. Thus, it is possible that

programs that have been shown to be effective in preventing

smoking cannot be generalized to more "hard-core" adolescents.

188
Internal Validity

With regard to internal validity, Hansen et al. (1983) suggest

that prevention studies should examine whether there are

differences in the rates of attrition among experimental

conditions. They found evidence of a difference between

conditions in attrition rate for one of the studies that they

reexamined, but not in the other. The second issue they raise

with respect to internal validity is whether pretest scores

for dropouts are different among conditions. They did not

find evidence of such a difference in either of the studies

they reexamined.

When we examined the data from our smoking prevention study in

a similar way, we found no differences between treatment and

control conditions in the rate of attrition. When we compared

those who dropped out of treatment with those who dropped out

of the control condition, we found no differences in the rate

of smoking in the prior week, in the number of times they had

smoked marijuana in the prior week, or in their consumption of

alcohol in the past week. It should also be pointed out that

the existence of pretest differences for remainers is

suggestive of differential attrition, but does not

conclusively prove it. Pretest differences can be a normal

outcome of the randomization process.

An alternative analysis strategy suggested by Cook and

Campbell (1979) involves testing for condition by attrition

interaction effects. A significant interaction would indicate

differential attrition across conditions. When we examined

our data, we found a significant interaction for pretest

smoking rate, F(1,1719) = 6.40, p <.02, but not on any of the

other variables of table 4. Specifically, the pretest smoking

rate among treatment group dropouts was higher than it was for

dropouts in the control condition, and the reverse was true

for those remaining in the study sample. This finding raises

doubts as to the internal validity of this and other such

studies. That is, if pretest smokers in the treatment group

are more likely to drop out than pretest smokers in the

control group, then findings showing lower smoking among

treatment subjects who remained in the study may in fact be

due to differential attrition rather than to the intervention.

Clearly, attrition is a threat to the internal validity of

evaluations of prevention programs.

Recommendations

Where it has been examined, evidence has consistently been

found which indicates that attrition threatens the external

validity of smoking prevention studies. Evidence that

attrition affects internal validity of prevention studies is

more mixed. Perhaps more noteworthy is the lack of analyses

189
of attrition effects in most studies. Analyses of attrition

should be routinely conducted in studies of smoking

prevention. The questions posed by Hansen et al. (1983)

provide a useful framework.

It would also be valuable to learn more about why subjects are

missing from later assessments. One might attempt to

determine the extent to which those who are missing a) had

transferred to another school, b) had dropped out of school,

c) were absent on the day of assessment, or d) skipped the

class in which the assessment was being conducted.

Finally, Hansen et al. (1983) suggest procedures to reduce the

rate of attrition. These include attempts to trace students

who have left the school, and returning to the school to get

data from subjects who were absent at the first assessment.

CONCLUSION

Designs in which whole schools are assigned to treatment and

control conditions appear to be most appropriate for the

evaluation of smoking prevention programs. Researchers and

funding agencies will have to come to grips with the fact that

such studies will be relatively expensive, yet have relatively

poor statistical power. Blocking or matching schools prior to

assigning them to conditions will strengthen the power of

these studies. Analysis of the data using the individual as

the unit is understandable in light of the low power of

school-level analyses. However, it must be recognized that

use of a unit of analysis that is different from the unit of

assignment converts an experimental design into a

quasi-experimental design. If one does this, we recommend the

use of classroom means as the unit of analysis, rather than

individual scores. Studies of the effects of prevention

programs that target adolescents who are already smoking would

be valuable, since this group has a high risk of continuing to

smoke and individuals could be randomly assigned to

conditions. In schoolwide prevention studies, the use of

passive consent procedures in which parents reply to the

investigators only if they are refusing permission is

essential, since an active consent procedure produces a biased

sample.

Studies of the processes that are presumed to mediate the

effects of prevention programs have been heavily biased toward

the use of questionnaires to assess cognitive processes.

Researchers should clarify what specific events are designated

by these cognitive constructs; multimethod assessment could

then be used to clarify the degree to which current

questionnaire measures actually measure cognitive processes.

Since most programs are designed to affect adolescents' social

skills and the social contingencies that affect smoking, it

190
would be informative to develop a multimethod assessment of

skills and social contingencies.

Although strides have been made in assessing smoking behavior,

we cannot be confident that existing procedures allow us to

detect low-rate and experimental smoking. Studies that show

that experimental smoking has been deterred may not translate

into effects on the prevalence of smoking at the twelfth grade

and beyond. For these reasons, it appears imperative that

smoking prevention programs be evaluated in terms of their

effects on the prevalence of smoking, at least at the end of

high school. Separate assessments of program effects on

subjects in each level of pretreatment smoking status is

needed, and further scrutiny of cessation among regular

smokers could be particularly informative.

Subject attrition is a major threat to the external validity

of smoking prevention studies, and may be a threat to the

internal validity of some studies. Reports of the evaluation

of prevention programs should present analyses of the possible

impact of attrition on internal and external validity.

Studies of the factors that produce attrition could help us to

reduce it. Procedures for tracing subjects who are missing

from postintervention and follow-up assessments could

ameliorate this problem.

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AUTHORS

Anthony Biglan, Ph.D.

Oregon Research Institute

195 West 12th Avenue

Eugene, Oregon 97401

Dennis V. Ary, Ph.D.

Oregon Research Institute

195 West 12th Avenue

Eugene, Oregon 97401

195
Priorities in Research

in Smoking Prevention

Thomas D. Cook, Ph.D.

INTRODUCTION

This chapter discusses issues raised by Biglan and Ary in their

paper “Methodological Issues in Research on Smoking Prevention”.

Rather than comment on their paper point by point, I want to take

their major themes and develop my own thinking on them.

I use their analysis of units of assignment to suggest that many

individual studies of smoking prevention and cessation will

inevitably be flawed In multiple ways. Consequently, one should

not expect too much from individual studies and should instead

rely on reviews for the identification of reliable knowledge,

particularly about effective treatments.

I then use their analysis of construct validity to probe the

kinds of research questions--and hence the kinds of individual

studies--that might have most utility in the study of smoking

prevention, suggesting that large-scale planned comparisons of

currently advocated prevention strategies might have greatest

utility at this time.

Finally, I use their analysis of attrition to probe some of the

Implications that arise for research design and analysis because

smoking seems to be on the decrease In the nation at large. This

means that proponents of smoking prevention are forced to

evaluate their work relative to a comparison standard that is

already moving “by itself” in the very direction prevention

researchers want to take it. In this situation, how can we make

sure that research on smoking prevention in schools is ddressing

issues that are likely to add significantly to current trends?

196
THE UNIT OF ASSIGNMENT AND ANALYSIS

The Problem

Research on smoking prevention in school settings raises the

methodological issue of what should be the unit of treatment

assignment and of data analysis. As in all school research, the

opt Ions are many. One can choose to assign school districts,

schools, grade levels, classrooms, or individual students. The

generally acknowledged principles to follow in unit selection are

two.

Principle 1. The unit of assignment should be the same as the

unit of analysis. Otherwise the assumption of independent errors

is violated, and differences between the higher-order units

(e.g., schools) are attributed to differences between the

lower-order units (e.g., students). Consider the case where

there are two schools in each of two treatment groups and some

event other than the treatment influences smoking rates In one of

the schools. This theoretically irrelevant event would influence

the scores of all or most of the children from the school,

entailing a change in the mean of the treatment group to which

they were assigned. If we knew that the theoretically Irrelevant

force in question had indeed operated, then we would know that,

in the absence of other analyses, we could not distinguish

between whether the irrelevant force or the treatment had caused

the observed effect. However, If we did not know about the

irrelevant force, we might then conclude that the treatment had

caused the change. Yet this would be an error, for the change In

the example was due to the treatment-correlated force that

influenced only one of the schools but many of the Individual

students within that school.

In a sense, using students as the unit of analysis provides too

many degrees of freedom, since schools were originally assigned

to treatments, not students. Under most conditions, inflating

the degrees of freedom is likely to cause spuriously low

estimates o f standard errors and hence produce too many

statistically reliable differences. This is a second consequence

of the mismatch between units of assignment and analysis, over

and above the possibility of systematic bias In treatment effect

estimates.

In the hypothetical example above, the technically correct

procedure is to calculate a mean score for each of the four

schools and to use these means as the raw data In subsequent

inferential analyses that contrast the treatment and control

groups. However, in our example, this technically correct

procedure results in only four observations, two per treatment,

making it easy to see one of the major reasons why Principle 1 is

of ten violated. The result Is data analyses that involve more

units than were originally assigned to treatments, and that

therefore increase the chances of biased estimates of treatment

effects and of standard errors.

197
Principle 2. The unit selected for assignment shouId be the

lowest compatible with the integrity of the treatment

contrast. This principle indicates that it is better to assign

lower-order than higher-order aggregates--e.g., students rather

than classes, Intact cl asses rather than entire grades, and

grades rather than whole schools.

One rationale for this is that it is easier to command the full

attention of individuals than of classes and of classes than of

schools, making it easier to standardize treatments and deliver

them more powerfully. A second rationale is that individual

assignment permits more comprehensive explanation and prediction

because statistical interactions can then be probed at many more

levels. That is, data from individual students can be used to

examine interactions between treatments and attributes of either

individuals, classes or schools, whereas school-level data can

only be used to probe interactions between treatments and

attributes of schools or school districts, but not between

treatments and attributes of either students or classes. A third

rationale is that, when the number of higher-order aggregates is

very small, statistical power to detect true differences will be

low. Assigning lower-order aggregates can dramatically increase

the power of statistical tests, as is most obvious when there are

few schools but many students in a study.

Although the advantages of assigning lower-order units are clear,

it is not always desirable to carry out the treatment assignment

at the lowest order of aggregation. One circumstance arguing

against the practice Is when a treatment is meant to influence

classroom or school norms. When individuals are assigned to a

smoking prevention treatment that successfully modifies classroom

norms, the behavior of control group students within the same

class is likely to be affected and the desired treatment contrast

will have disappeared. Likewise, if a treatment is meant to

influence school norms but Is assigned to individuals or classes,

a change in the school norms will Influence all children,

irrespective of their original treatment assignment. As a

result, the integrity of planned treatment comparisons will be

compromised.

The second circumstance arguing against the principle of

assigning lower-order units is when students in one treatment (or

control) group may be exposed to a different treatment, perhaps

visually or as a result of informal conversation between students

during or after school. This situation is not dissimilar from

what happens when norms are changed. However, with treatment

diffusion students are inadvertently exposed to the instruction

in smoking prevention, whereas with norm change students are

exposed to the target behaviors of the study without necessarily

observing the treatment itself.

For children or classes to be viable as the unit of both

treatment assignment & data analysis requires demonstrating (1)

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that there has been no dissemination across treatment groups of

knowledge of the different treatments; and (2) that students in

one treatment group have not been exposed to others’ reactions to

the treatments they received.

The unit of analysis influences not only the likelihood of

bias-inducing social comparison, but also the statistical power

to detect true treatment effects. However, the relationship

between the unit of analysis and the extent of power loss or gain

is complex. On the one hand, the more aggregated a unit of

analysis is, the more stable are the measures it provides. This

suggests that school means are usually more stable than classroom

means and that classroom means are more stable than scores from

individual children. The desirability of reliable measurement

suggests preferring higher-order over lower-order aggregates as

the unit of data analysis.

But arguing against this are three other considerations. First,

the more aggregated is the unit of analysis the fewer are the

degrees of freedom and the less is the power to detect true

differences. Second, the higher the unit of assignment the fewer

are the statistical interactions that can be probed. Thus, when

entire classes are the unit, interactions involving student

characteristics remain unexamined. Third, some children are

absent from school more often than others, and some understand

the treatment better than others. Consequently, the strength and

integrity of a treatment can vary from child to child. This

source of extraneous variation will go unanalyzed if the analysis

is restricted to higher-order aggregates.

We see then, that the relationship between statistical power and

the unit of analysis depends on many factors, some of which will

be unique to a particular study. Decisions about the preferred

level of aggregation have to depend on a complex interplay

between the sample sizes available, the reliability of measures,

the integrity of treatments, and the likelihood of detecting

statistical interactions Involving lower-order units.

Practical Partial Solutions for Research on Smoking Prevention

To stay true to the two principles of unit selection outlined

above, one could use schools as the unit of assignment and

analysis, but in ways that increase degrees of freedom, minimize

irrelevant scores of variability in implementation, and ensure a

high level of treatment relevance to all or most of the children

in a school. Alternatively, one could use classrooms or

individuals as the unit of assignment and analysis, but in ways

that minimize the diffusion of treatments or their consequences.

As always, though, there Is a third step that could be taken.

One could try to break the set in which the unit issue is

traditionally conceptualized. We now discuss these three

possibilities.

Schools as the unit of assignment and analysis. If schools have

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to be the unit of assignment, It is desirable to include as many

of them as possible in the research design. But how can this be

done with a fixed budget in ways that do not compromise the

integrity of treatment implementation because of the logistical

problems associated with large scale research involving many

schools?

One thing to explore is whether it is possible to modify sampling

plans to contact only a random subset of children (or classes)

within schools and to use the resources saved to contact more

schools. The rationale for doing this Is that, after a certain

point, each additional student lost within a school detracts only

trivially from the precision of estimates, whereas when schools

are the unit of analysis, a few more schools may lead to a

considerable marginal gain in both precision and bias reduction.

In some instances, the nature of a treatment or school may

require that all students be exposed to a treatment, making the

random selection of students impossible when it comes to

treatment exposure. But our major point involves the random

selection of students for measurement, though financial savings

are obviously greater (and more schools can be added) if some

students are dropped both from treatment implementation and from

the measurement of outcome and process. However accomplished,

the strategy of sampling students with in school s has a major

problem, for many students have to be dropped to save enough

money to add just a few schools.

When working with small samples, a second possibility to explore

is the assignment of schools to treatments from with in strata

that are highly correlated with the research outcomes of most

importance. This usually means (1) deciding on a blocking

variable (say, the percentage of estimated smokers); (2)

measuring schools on this variable prior to treatment assignment;

(3) creating blocks of schools that differ in the percentage of

smokers, with the number of schools in each block being some

multiple of the number of treatments; and (4) randomly assigning

schools to treatments from within each of the blocks formed by

the smoking variable.

This stratified random sampling plan has a number of advantages,

listed in terms of descending importance. First, compared to

treatment assignment without stratification, it provides greater

initial comparability between the various treatment groups,

especially when the sample size of schools is tiny. This is

because the prior stratification procedure ensures that random

assignment only takes place among schools that are initially

highly comparable with respect to the major outcome variable.

Second, stratification increases the power to detect effects

because the variance attributable to the blocking factor can be

estimated and removed from effect estimates. And third, if a

large sample of schools is available, interactions between the

treatment and blocking variables can be estimated.

Although many matching variables are possible, for most studies a

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measure of the percentage of pretest smokers is likely to be

preferred. This is because it is nearly always the highest

correlate of the outcome variable that most substantive experts

consider most important: viz, the percentage of smokers at the

posttest. However, if some other outcome variable is of greater

importance in a particular study, a pretest measure of it will

usually provide the best stratification possibility. This is

because, over time, measures usually correlate better with

themselves than with other variables. If matching on multiple

variables is possible, variables should be selected for their

ability to add to the total prediction afforded by pretest

measures of the major outcome variable.

A third step analysts should take to get around the small sample

problem associated with higher-order units is to increase the

number of measurement waves. This is because the total number of

degrees of freedom is determined by the number of schools

multiplied by the number of times measurement occurs. Multiple

pretest measurement waves has the additional advantage that it

provides a gross handle on patterns of historical shifts in

smoking, which is important at present because smoking rates seem

already to be on the decline. If more than one pretreatment

measurement wave is not possible, it is still desirable to

increase the number of measurement waves during protracted

treatments, after a treatment has been discontinued

or--preferably--at both time points. The more often measurement

occurs, the better will be the prediction of time changes within

and between treatment groups, making the statistical and visual

comparison of time trends more sensitive than would be the case

If measurement were restricted to only a single pretest and a

single posttest measurement wave.

Although the benefits of multi-wave studies are extensive, they

have to be weighed against the potential disadvantages of

obtrusiveness and attrition. While steps can be taken to reduce

the magnitude of the obtrusiveness problem--largely through less

salient measurement, longer time intervals between measurement

waves, and complex matrix sampling designs that do not require

measurement of each student at each time point--these techniques

are not universally applicable. Moreover, while fairly obvious

steps can be taken to reduce attrition, these procedures are only

tractable within limits. Nonetheless, everything possible should

be done to limit the problems of obtrusiveness and attrition, and

to measure behavior in as many waves as budgets, hospitality, and

funder patience permit.

To increase the likelihood of detecting true effects, analysts

can adopt a fourth strategy. They should attempt to replicate

administration o f the treatment. If evidence of an effect has

already been manifest with “experimentals", one way of achieving

this is to have the original “controls" switch and be belatedly

exposed to one of the treatments (Cook and Campbell 1979).

Designs in which the original controls belatedly adopt an

experimental status are common in behaviorist psychology, where

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small sample sizes are the norm and causal inference is routinely

made to depend on the controlled introduction, removal, and

reintroduction of treatments. In this tradition, much less

reliance is placed on mechanisms for justifying causal inference

that are commonplace elsewhere--viz, a long string of

pretreatment measures (as in interrupted time-series work),

random assignment (as in classical experimental design), or

causal modeling (as in economics or sociology).

A fifth strategy available to prevention researchers is to

conduct their work in schools where the kinds of student are

particularly likely to begin smoking or to become heavy smokers.

At present, most prevention research is directed at entire

schools. But many of the children in these schools will never be

smokers , or will never be smokers at a level currently considered

to be health threatening. Consequently, many (if not most) of

the children cannot be helped in the most important ways that

provide the political and economic justification for smoking

prevention programs. Moreover, the power to discriminate between

treatments is greater when schools are selected for study because

they contain large percentages o f the types of children that

descriptive research has identified as particularly likely to go

on to smoke. At least this is the case if one can assume that

the efficacy of a smoking prevention treatment does not depend on

the level of initial smoking in the school. If the potency of

treatments is lower in schools with more smokers, then two

countervailing forces are set up that Influence the power to

detect effects. On the one hand school s with more smokers will

have more students who could change; but on the other hand, the

environment in these schools is less conducive to bringing about

Individual facts.

Other than in a trivial physical sense, schools are not fixed

entities and there are daily and annual fluctuations in the

children who attend them. A sixth way to increase the chances of

detecting true effects is to limit the data analysis to purified

experimental and control samples that contain only those children

who have provided data at all the measurement waves. The data

from children who were absent on any day of data collection

should not be used, including the data from those who enrolled

after a treatment. Such a procedure refines the unit studied.

It is no longer the school; it is now the school reconstituted as

those children who provided data at all measurement waves. (Of

course, if one is worried lest those who drop out of school are

the most susceptible to smoking, it is theoretically possible to

track them down and keep them in the measurement plan and data

analysis. Tracking them is an expensive process. If

implemented, as much effort should go into contacting controls

who drop out as experimentals. Indeed, the general principle

holds that experimentals and controls should be treated

identically in all respects other than treatment assignment).

Finally, when schools are the unit of analysis careful monitoring

is required over the total course of a study. This is primarily

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to check on the fidelity of treatment implementation and to

detect any irrelevant school-specific events that might have

affected the major dependent variables. For instance, some

classes within a school may not be exposed to the treatment for

irrelevant reasons; or a local community or hospital might begin

its own health promotion program that influences some of the

students in a school and threatens to distort the treatment

effect estimates. Monitoring for such events is required and can

be accomplished in many ways that differ in cost and accuracy

(Cook, Leviton, and Shadish 1985).

To summarize: Smoking prevention research that requires

higher-order aggregates runs the risk of bias and imprecision

because of the small sample size of units. To reduce the

problems I suggest: (1) sampling students within schools rather

than taking all students, and using the resources saved to add

more schools; (2) stratifying schools on the major outcome

variable prior to random assignment to treatments from within

strata; (3) adding waves to the measurement plan so as to

increase the degrees of freedom; (4) implementing a switching

replication design so that the original control group receives

belated exposure to one of the experimental treatments; (5)

selecting schools for study because of their known high levels of

smoking; (6) purifying the data so as to examine in some analyses

only those students (and their yoked controls!) who have had

exposure to the treatment and have been measured at each testing

wave; and (7) careful monitoring to assess treatment

implementation and to observe whether any unexpected

school-specific events have occurred that might be correlated

with the outcome variables of greatest importance.

Classrooms as the unit of assignment and analysis. Classes are

only viable as the unit of assignment if it is reasonable to

assume that there will be minimal seepage of the effect or of the

treatment across c I asses. Estimates of the likelihood of such

seepage depend on the particular nature of a treatment or effect,

and I am not going to speculate in detail about the treatments

and effects that do and do not facilitate seepage. However, It

should be noted that some classroom-level studies have been

successfully conducted in the health education field after pilot

work was carried out and showed that treatment diffusion was not

likely (e.g., Connell and Turner, in press). The issue we now

address is when one can use classrooms as the unit of assignment

without having to aggregate up to whole schools and absorb the

limitations that go with schools as the unit of assignment and

analysis?

With some types of treatment or effects, I assume seepage is more

likely across classes within a single grade than it is across

different grades. The rationale for this is that students are

more likely to communicate with persons in their own age cohort

than with younger or older students. If true in particular

instances, this assumption implies that one can randomly assign

grade levels to treatments within schools, with each class being

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assigned to the particular treatment its grade level receives.

If adjacent grades are likely to communicate with each other

despite the one year age differential, then immediately adjacent

grades can be skipped. One might, for instance, assign Grade 9

in High School A to the experimental treatment, with Grade 11

becoming the controls. Then, in a matched high school, the

reverse assignment would take place so that Grade 9 become the

controls and Grade 11 the experimentals. This yoked assignment

procedure is then continued until all the high schools in the

sample have been allocated, resulting in a sample size that is

twice what it would have been if schools were the unit of

assignment. Also, the variability between schools can be removed

from the error term, and the measures are likely to be

particularly reliable since they are based on all the children

and classes in a particular grade. However, strictly speaking,

classes are not the unit of assignment in the above case. Grade

levels are.

There are some treatments that fit easily into existing range of

expected school curricula and are not likely to stand out. They

are seen by students as being just more instruction, and are not

likely to be talked about. Under these conditions of "mundane

realism," it is possible to deal with smoking in some ways in

some classes while dealing with It differently or not at all in

other classes at the same grade level. In such a scheme, the

class assignment to treatments is at random, occurs between

classes within grades, and is replicated across all the schools

in the sample under study.

Since the crucial assumption is that little seepage will occur,

it is important to ask when treatments are likely to be so much a

part of expectations that they are rarely (if ever) talked about

outside of the classroom. The assumption strikes me as more

reasonable when different versions of an antismoking treatment

are being contrasted than when one version is contrasted with no

such instruction at all. Nonetheless, Connell and Turner (in

press) were able to assume mundane realism even in this second

context because students knew there were so few health education

teachers that not all classes could receive Instruction in the

same quarter. Turn-taking was the norm. Al though treatments are

very salient to researchers and curriculum developers, they

should not assume that the treatments they hold dear are as

salient to students as they are to themselves. Ultimately, the

issue of treatment seepage is empirical and deserves the

considerable effort being expended on it during pilot research.

It is important to note that inferences about treatment effects

can be biased, not only because of the seepage of treatments, but

also because of the seepage of effects. Consequently,

within-school comparisons do not make sense (1) if one is trying

to influence school-wide norms; or (2) if one’s substantive

theory supposes that peers from different classes within the same

school are a potent cause of other students taking up smoking.

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in each these cases, treatments that are effective in reducing

smoking will also reduce smoking in "control" classes that have

never been exposed to the treatment being evaluated.

Underestimates of a true effect will then result.

If the assumption is made that seepage of either a treatment or a

dependent variable is likely to be widespread within a school,

then assignment and analysis need to be between schools rather

than between classes or grades. It will not be possible to

assign individual students. For students to be viable as units

requires no seepage and either "pull-out" prevent ion programs

like those found in bilingual and remedial education or programs

that are exclusively based on giving different children different

homework assignments. Such individual-level programs would not

only be obtrusive and expensive; they might also be of such a

restricted range that only weak treatments would be possible.

Breaking the set in which the unit problem is conceptualized. I

have tried to show above that there is no single unit of

assignment or analysis that is "correct" or "best". The

preferred choice depends on many factors, including: The nature

of the treatment and its presumed diffusability, the

configuration of classrooms, the likelihood of influencing school

norms, tradeoffs between the sample size of schools, classes, and

students, and the assumptions one makes about the likelihood of

different forms of statistical interaction. While no easy

answers are possible about the selection of units, the two

principles I have outlined from classical theory should

nonetheless be important inputs into the process of deciding what

level of assignment and analysis to choose.

In school and community studies where the nature of the treatment

dictates studying a few, large aggregates, one way to break out

of the traditional set in thinking about unit selection is to

assume that Principle 1 can be violated. Asymmetry between the

units of assignment and analysis is least serious in its negative

consequences when the sample of higher-order aggregates (e.g.,

communities or schools) is "large" and extensive on-site

monitoring has shown that no outcome-related idiosyncracies

occurred during the study to affect more of the units from one

treatment group than another. Under these conditions, one might

indeed assign communities or schools to treatments but analyze

the data as though they came from individuals.

While asymmetry between the units of assignment and analysis is

currently widespread in prevention research, it rarely occurs

under the favorable conditions outlined above. Indeed, my

Judgment is that such asymmetry is most likely to occur precisely

because the small number of communities or schools precludes

statistically powerful analysis. But even if hundreds of

children change their behavior when few schools are assigned to

each treatment, the possibility always exists that these changes

are the result of a single theoretically irrelevant force unique

to one or two of the sites--e.g., a local smoking drive, a

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particular principal who forbids teachers to smoke on the

premises, or a local celebrity who dies of emphysema, etc.

Although necessity is a not irrelevant justification for the

assymetry of units of assignment and analysis, it seems to me

that nearly all individual research reports would profit by

providing more commentary about the gains and losses that follow

from having violated Priciple 1.

A second way to break out of the traditional set implied by

Principles 1 and 2 is to conclude that no single study with a

small sample of schools is going to provide convincing inferences

about the effectiveness and transferability of prevention

treatments. Instead, progress is to be expected from studies

using methods of quantitative research synthesis, among which the

most visible today is metaanalysis. I suspect that dependable

know I edge of the ongoing multi-risk, communitywide prevention

studies being conducted at Stanford, Minnesota, and Rhode Island

will come, not from the individual trials now underway with their

small samples of communities, but from combining the studies.

Such a synthesis would use community means as the basic unit of

analysis to create for each study a set of pretest/post-test means

per treatment that will be used as the basic data for inferential

analyses. In school research, metaanalyses would use school or

class means as the basic input.

The advantages and disadvantages of metaanalysis have been

outlined many times elsewhere (e.g., Cook and Leviton 1980), and

I will not go into them here. But if a sufficient sample size of

smoking prevention studies exists, the feasibility of a

metaanalysis might be worth exploring since the units of

assignment and analysis would not clash. One would therefore

escape from the conundrum associated with most individual

studies: Either a small number of schools is assigned to

treatments and the resulting data are analyzed correctly, but

with little statistical power and some likelihood of bias from

“local history" (Cook and Campbell 1979); or else the data are

analyzed incorrectly in ways that provide more degrees of freedom

but that also bias estimates of both standard errors and

treatment effects.

This is not to suggest that I am against all individual level

analyses. They are absolutely required to explore interactions

between treatment and student characteristics. It is merely to

suggest that such exploratory analyses have to be done together

with analyses that use the appropriate units of analysis. These

are the units of original treatment assignment.

CONSTRUCT VALIDITY AND VARIETIES OF CAUSAL STATEMENT

Biglan and Ary point out that most of the interventions tried to

date are more like multivariate treatment packages than

unidimensional constructs with an obvious theoretical referent;

that prevention research requires important but difficult

judgements be made about how far along hypothetical chains of

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causal influence (Flay and Cook 1978) one should go before

declaring that a treatment is "successful"; and that it would be

useful if prevention studies could specify the causal processes

that occur between treatments being implemented and impacts being

observed.

These are all sensible points, and they speak to a crucial

strategic issue. If one follows through on the implications of

Biglan and Ary one would multiply measure each individual

component of each of the treatment constructs invoked in each of

the many causal models that could easily be developed from all

the current substantive theories of relevance to smoking

prevention. Then, one would analyze the data using some form of

causal modeling, perhaps LISREL. While I generally support such

a plan, I would like to point out its side effects, particularly

with respect to expense, the obtrusiveness of measurement, and

the opportunity costs of sinking so much into the fine-grained

measurement of process.

In basic research we seek to identify causal explanations for

phenomena, hoping to achieve simple results. lnitially, we ask

questions Iike: “How do humans grow physically?” We I earn to

answer: “Because our bodies contain DNA and RNA that genetically

control the messages sent to cells through a process in

which....” We also ask: “Why do we see?” And we learn to

answer: “Because our eyes are constructed in such and such a way

and are connected to the brain in such and such a way so that

when light falls on the retina, such and such happens.” We learn

to ask: “Why does flicking the lightswitch cause the room to

illuminate?" An electrician might respond: “Because a house Is

wired in such and such a way; its wiring is connected to an

external source of electricity that enters the house; and so on.”

In all of these cases we equate causal explanation with knowledge

of micromediating causal pathways that bring about some important

result; and these pathways are typically specified at a level

which seems more reductionistic than the phenomena they are being

used to explain. Nobel Prizes are awarded for explanations of

this type, and scientists are taught to seek such explanation as

the primary goal of their work.

Contrast such know ledge of causal explanation with the following

examples of knowledge of descriptive causal relationships:

Rubbing two sticks causes fire; flicking the light switch causes

the room to illuminate; taking aspirin causes headaches to go

away; and taking chlorpromazine causes the symptoms of

schizophrenia to diappear. These examples all illustrate

dependable knowledge of causal relationships, and we can use this

knowledge to light fires, get rid of the dark, alleviate

headaches, and obviate the socially uncomfortable manifestations

of schizophrenia. Yet few of the lay persons who know of these

causal relationships can explain them. For explanation we turn

to scientists and relevant professionals. Unfortunately,

scientists and professionals cannot fully explain all of the

causal relationships above. I am told we still do not know why

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aspirin or chlorpromazine are effective. They were discovered as

side effects in Investigations of other issues; they are not the

product of deductions from basic knowledge of explanatory

processes.

Moreover, it seems reasonable to assume that homo sapiens had

dependable, useful knowledge of the consequences of rubbing two

dry sticks together long before anybody could explain why the

process of rubbing sticks results in sparks that can set tinder

alight. Causal explanations of micromediation are not required

for knowledge of useful and dependable causal connections.

Indeed, utility can easily be demonstrated to be independent of

explanation. For instance, we not only do not know why

chlorpromazine works; we know that it fails to cure and only

suppresses symptoms. Yet symptom suppression is often socially

useful. We al so know that chlorpromozine works better with some

schizophrenics than others. Its efficacy is probabilistic, not

deterministic. Even so, the drug is efficacious often enough to

be socially useful.

I do not want to argue against the utility of causal

explanations, for they often suggest totally novel causal

relationships that lead to the development of causal manipulanda

of practical value. Indeed, the major economic justification for

basic science has always been that the explanatory knowledge it

generates helps Identify practical and useful causal agents.

Actually, causal explanatory knowledge does more than this. It

also implies knowledge of the contigencies on which more molar

causal relationships depend, helping predict when a causal agent

will and will not be effective. Thus, once one knows the

processes whereby rubbing sticks causes sparks, one can then

infer that rubbing wet sticks together will not result in sparks

unless one has rubbed so hard and for so long that the sticks

have dried out.

Despite these very real advantages, knowledge of micranediating

processes is not necessary for knowledge of contingent causal

relationships. Knowledge that dry sticks cause sparks, but wet

ones do not, can be acquired through practical problem solving

designed to understand why rubbing sticks has sometimes caused

sparks in the past but at other times has not. A curious

ancestor of ours many generations ago might well have

deliberately experimented with various kinds of stick, various

ways of rubbing, and various forms of tinder In a number of

different social contexts before discovering through

trial-and-error that only dry sticks lead to sparks. While

knowledge o f contingent causal connections can follow from the

complete causal explanation o f micromediating processes, such

explanation is not required for identifying either causal agents

or the contigencies on which their efficacy depends.

In prevention research, the causal agents can be theoretical

constructs, individual components of a global treatment package,

or individual treatment packages In their entirety. My working

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assumption is that in most prevention research the program

activities actually implemented are imperfect realizations of

imperfect substantive theories. It follows from this that

implemented treatments are influenced by many factors not in the

relevant substantive theories. Indeed, it is well-nigh

inevitable that practitioners will bring their own discretion to

bear to fill in theoretical gaps and to mold treatments to what

their own experience has taught them are the unique and important

attributes of the particular schools, children, and teachers with

whom they are associated. In the world of action, treatments

reflect many origins and are inevitably multicomponential. They

are not the presumed unidimensional causal forces of most basic

research, although they may include such components as part of

the total treatment package.

The above discussion implies four

Play in amellorative social research

types of causal knowledge at

(1) knowledge of the effects of substantive theoretical forces

that are embodied as part of a total program design and are

believed to be unidimensional;

(2) knowledge of the effects of a global, multivariate treatment

package that includes many components not specified in formal

substantive theory;

(3) knowledge of contingent causal relationships that specify the

conditions under which a given global treatment differs in

effectiveness; and

(4) explanatory causal knowledge that specifies both the causally

efficacious components of the treatment and the particular

micromediating processes through which Influence is transmitted

to the causally impacted components of the dependent variable.

Although these four types of knowledge are related to each other

in multiple, complex ways, they are heuristically distinct. In

the context of smoking prevention programs for school settings,

knowledge of theoretical antecedents is equivalent to learning

about the consequences of, say, innoculation against peer

pressure to smoke. Knowledge of causal relationships Is

equivalent to learning about the effects of a global

program--e.g., Smith’s program to prevent smoking. Knowledge of

contingent causal realationships is equivalent to knowing about

the conditions under which Smith’s program has the effects it

sometimes has. Finally, knowledge of causal explanations is

equivalent to specifying the causal pathways through which

Smith’s program has its effects--e.g., the program is effective

because, on the one hand, it promotes an innoculation that leads

to resisting peer pressure to smoke and because, on the other

hand, the program also increases the social support parents

provide to their children. This illustrates only two causal

pathways to decreased smoking, and very simple ones at that.

Many more paths are possible, as are many more necessary events

on each path.

These distinctions between types of causal construct raise

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consciousness about what should be the priority form of causal

knowledge in prevention research. In much basic research in the

social sciences the hope is to manipulate or measure

unidimensional causal agents derived from substantive theory

about, say, dissonance or communicator credibility. At issue are

tests of the antecedents and consequences of presumed novel

entities, and in this tradition construct validity is equated

with the construction of research operations that fully reflect

formal theoretical definitions. However, in more applied

research the abstract concepts to which one wants to generalize

are less precise and might be more like a methadone maintenance

or Headstart center than like the theoretical entities of

dissonance or communicator credibility. While the concepts of a

methadone maintenance or a Headstart center may include some

theory, they typically include many other components that may or

apparent unidimensional forces abstracted from substantive

may not be necessary or sufficient for bringing about effects.

And their construct validity does not depend on a fit with

substantive theory. Instead, It depends on the extent to which a

plan for a program is implemented in practice.

One problem with studying treatment packages like Smith’s program

or a Headstart center is that, by themselves, they rarely permit

identification of the conditions under which a treatment is

effective. Yet such knowledge is vital if one assumes a social

reality where the same apparent treatment may be implemented

differently in different settings or where reactions to the same

treatment may be different with different types of people.

Knowledge o f such contingencies is believed to be crucial, not

on I y among scholars, but also among planners who want to be able

to plan more exactly and among practitioners who want to tailor

their activities to Important sources of variability in clients

and settings. Thus, knowledge of causal contigencies enhances

prediction, explanation and control.

Even so, it does not offer total prediction, explanation or

control. These require a full understanding of all the processes

that occur after a cause has varied and before an effect has been

measured. Only with such knowledge can one identify all the

necessary, and some of the sufficient, conditions for bringing

about an effect (Cook and Campbell, in press).

Since the different conceptions of cause promise different types

of knowledge and different degrees of prediction and control, we

have to ask: Which is to be preferred in prevention research at

this time. Various groups with a stake in social programs assign

different utilities to these types of causation (Cook 1984).

Scholars who work in university settings have been trained to

appreciate the development and testing of substantive theory, and

are inclined to assign a higher priority to theorytesting than to

the study of multivariate treatment packages. Since they are

also trained to appreciate the advantages of explanatory theory,

the also tend to place a higher value on identifying molecular

causal explanations than on describing more molar causal

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relationships. This last preference leads them towards the study

of causal contingency and especially towards the identification

of micromediational processes. Few basic researchers value

learning about the effects of a treatment package that is so

global (1) it cannot be fully described in theoretical terms, (2)

its consequences are produced only intermittently, and (3) its

causal mechanisms are not understood.

Many high-level Federal administrators and Congressional

officials have a different set of priorities, particularly if

they work for action agencies. In addition to wanting to keep

their jobs and protect their agency budgets, they al so want to

see some amelioration of the acknowledged social problems for

which their agency or office is held accountable. At the same

time, most of them appreciate the long time lines that may be

required to develop, test, and modify substantive theories and to

ferret out the most important contingencies and causal pathways.

They also know that, in designing programs for widespread

implementation, logistical, political, and economic realities

restrict what they can promote.

In particular, they often cannot use fine-grained knowledge. For

instance, while it might be useful to target an intervention that

works only with middle-class children at predominantly

middle-class schools, administrators know that the intervention

will often have to be made available to all schools, or at least

to all those that want it. Despite the political pressures

towards universal distribution, there are nonetheless some

occasions when Federal or state resources are targeted at poorer

schools. But when this happens, local superintendents and school

boards often anticipate that parents will object to more being

done for poorer children. In the past their anticipation has

sometimes led them to provide discretionary resources they control

to the more affluent schools in their districts. While this

helps them avoid the political repercussions stemming from

Federal funds that are to be unequally distributed, it can

obliterate planned "treatment” contrasts.

The moral is that the fine-grained, contingent knowledge to which

science aspires cannot always be applied with the same degree of

fineness in the more coarse-grained world of social action.

Educators are not like engineers. They cannot take

theory-derived, deterministic processes and neatly pack them into

closed systems, as occurs with car engines placed under hoods or

heating units placed in houses. In the open system world of

social policy, statistical main effects have more currency for

practical action than statistical interactions. Indeed, certain

interactions have to be treated as though they do not exist even

when it is known they do. Whether deliberate or Inadvertent, the

overlooking of statistical Interactions usually has trivial

consequences if the interactions are of the form in which all

groups or regions benefit from a treatment, but some more than

others. The consequences of overlooked interactions can also be

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tolerated in many instances when some groups benefit from a

treatment, but others do not even though they are not harmed by

it.

The major problem arises when policy makers are forced to

implement course-grained changes but the more fine-grained social

reality is characterized by some groups gaining from a treatment

while others are actually hurt by it. Our speculation at this

time is that, In prevention research, statistical interactions in

which some groups gain and others lose are much less common than

interactions in which (1) all groups gain, but differ in the

amount of gain; or (2) some groups gain, but other groups neither

gain nor lose. In any event, both the mandate of government

officials and the political realities in which they operate argue

for the primacy of knowledge about what dependably works, even

when one is totally or partially ignorant about the construct

validity of the causal agent, about the conditions under which

the agent is effective, or about the processes that make the

agent effective.

Cronbach (1982) has sought to bridge the gap between academic and

government priorities about cause, arguing (1) that policymakers

want knowledge of transferrable programs that can be implemented

from site to site across the very heterogeneous USA; (2) that

knowledge about transfer can best be inferred from knowledge

about causally efficacious theoretical constructs, contingent

causal relationships, and explanatory micromediating processes;

but (3) since policymakers do not require the same level of

uncertainty reduction as academics, the time-and labor-intensive

methods that are traditionally used in science to assess

knowledge of causal constructs, causal contingency, and causal

understanding are not required to meet the information needs of

policymakers and practitioners. Cronbach aspires to a

"reasonable handle" on theoretical knowledge rather than the

complete uncertainty reduction that motivates scientists. With

this knowledge he hopes to achieve the educational equivalent of

going to a house without lights, "roughly" knowing how to run

electricity into it, how to set up the wires, and how to

construct switches and bulbs. With this knowledge he can then

make light.

While Cronbach’s general thesis is useful in identifying the

primacy of learning about transferrable knowledge, it fails in

three crucial particulars. First, causal explanation is not the

only means of learning what is transferrable, even if it is the

most reliable of all the means available. We can also learn what

is transferrable by empirical demonstrations that a particular

cause-effect relationship has been repeatedly found in the past,

either in the particular type of setting to which we desire

transfer or across a wide variety of different times, settings,

respondent populations, and realizations of the treatment and

outcome measures. In this context, I suspect that the popularity

of metaanalysis

stubbornly dependable causal relationships that have been

is because it has led to identifying many

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replicated across a heterogeneous collection of studies and so

may be transferrable to novel sites and respondent populations.

Certainly, the appeal of metaanalysis cannot be based on

providing knowledge about causal contingency or micromediation,

for few metaanalyses have resulted in claims about such

knowledge. And of those that have, few are convincing. The

predominant finding in metaanalysis is of a coarse-grained, but

demonstrably dependable, main effect of some treatment.

Cronbach’s answer also fails to specify the degree of causal

explanation that is required for transfer to be reliable enough

to be useful. While we used the physical example of light to

make points about causation, the reality is that few theories in

the social sciences have been successful in coming up with

explanatory knowledge that is as valid and detailed as what we

know about electricity. Most social theories are more primitive

and fail to deal well with the vast contextualism in human

affairs, with the reality that important outcomes operate in open

systems and are nearly always multiply determined, and with the

fact that the relevant theories are very young. As a result, it

would be unrealistic to expect social science theories to be as

elegant, parsimonious and predictive as theories in the natural

sciences. If this is true even with theories tested using the

best social science methods, think what confidence we would have

In the results generated using methods of lesser stringency than

the best current methods of the social sciences!

Finally, it is possible to take Issue with Cronbach’s assertion

that professional practice and Federal and state policy require a

lower level of uncertainty reduction than formal scholarship.

A I though our knowledge of the issue is scant, some case study

information suggests that policymakers will fail to use knowledge

claims that are credibly contested (e.g., Boeckmann, 1976). The

assumption is they look to science for knowledge that is beyond

dispute and can play “definitive" roles in policy deliberations.

While these expectations may be unrealistic, they do not suggest

an existing willingness to settle for lower standards of

inference.

The implication of this critique of Cronbach is that the utility

of knowing about reliable, but ultimately unexplained, causal

connections may provide enough of a pragmatic justification for

orienting social research towards identifying such connections.

This does not preclude adding to the measurement, sampling, and

analysis frameworks of a study to probe the theoretical forces

responsible for treatment efficacy. But it does suggest that

such additions should not consume so many financial and psychic

resources that they detract from answers about the implementation

and effects of global treatment packages.

The degree of justification for claims about the consequences of

such packages Increases as a function of the quality of research

design, the frequency with which the same results have been

obtained in the past, and the degree of heterogeneity in the

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times, settings, and populations across which successful

replications have taken place. Replications that vary In time

nearly always require synthesizing many Independently conducted

studies. However, desirability in settings and populations can

be achieved without studies staggered in time, implying the

viability of some form of large scale, multisite study.

Yet such studies have acquired a bad reputation in the past

because a large sample of sites can lead to logistical problems

In data collection, to low quality treatment implementation, to

poorly implemented random assignment, and to Inadequate knowledge

of what has actually gone on in schools and of what measures

actually represent. These problems are exacerbated if several

different treatment packages are explicitly contrasted. The

“horse race” that results can arouse political tensions,

especially since the advocates of some treatments are likely to

believe that the dependent variables by which evaluation is made

are more relevant to some treatments than others.

My own belief is that the criticisms above were more valid for

the first generation of large-scale experiments conducted until

about the middle 1970s. The lessons that were learned from them

are now being widely disseminated (see Cook et al. 1985 and Cook,

in press), and the present generation of ongoing large-scale

experiments is much more sophisticated (e.g., Connell and Turner,

in press; Young 1984). Many of the objections to large-scale,

multisite experiments that contrast several models now seem

irrelevant, and we have begun the move from the era of horse

races to an era of yacht races. Yacht races decrease the level

of counter productive competition because many winners are

possible, each by different criteria. Since prevention projects

are typically evaluated by multiple criteria anyway, it is not

difficult to imagine some projects doing better than others in

some respects while other projects do better in other respects.

That is not to say that all the past objections to large-scale

studies are irrelevant. Three still seem potent. First is the

danger of premature experimentation using models that have not

been adequately pilot tested. Unfortunately, we have no way of

knowing what degree of treatment maturity is sufficient to

warrant a serious "clinical trial.” The second danger stems from

Federal officials needing premature feedback, so that not enough

time is available for planning a study, getting all the

stakeholders committed to its goals and methods, and getting the

results fully probed and critiqued before they are released. The

third danger follows from different stakeholders having different

information needs. Some might especially want to learn about the

treatment and its component parts as theoretical entities; others

might want to learn how well a treatment is being implemented;

others might want to know what immediate effects the treatment

has on one set of indicators; others might want to learn about a

quite different set of measures, or a quite different time period

of demonstrated effectiveness. Many types of questions about

intended and unintended influences should be asked in any single

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evaluation, and

only one type.

there is rarely justification for focussing on

Nonetheless, priority orderings have to be made and have to be

specified so clearly that a high likelihood exists of meeting

those research objectives considered most crucial.

Unfortunately, no algorithm exists for arriving at such

priorities for a single study, even though it is obvious that

pursuing one research objective as central can take resources

away from examining other objectives and can actually lower the

quality of answers to some questions. The nature of the

trade-off between question types has been actively debated in the

evaluation literature (c.f. Cronbach; 1982; Cook and Shadish, in

press; Guba and Lincoln 1981), and it is clear that multiple

issues should be probed in any one study--but with an exquisite

sense of priorities.

I have tried to argue that a compelling rationale exists for

learning how well a global treatment has been implemented and for

identifying the effects it has had across a heterogeneous array

o f settings and student populations.In the absence of a large

number of studies to be synthesized, such a rationale calls for

multisite studies, preferably those that have learned the

mistakes of past studies of this type. A lesser emphasis should

be placed on identifying the effective components of the

treatment and on identifying the conditions under which the

treatment or its parts are effective. And least emphasis should

probably be placed on identifying micromediational processes.

However, clues about micromediation should be forthcoming from

probes of the implementation data, from the prior literature and

professional wisdom, and from whatever analyses have been

conducted to identify both the causally efficacious components of

treatments and the conditions under which treatments and their

component parts seem to be most effective.

ATTRITION

According to Biglan and Ary, the students most likely to be heavy

smokers (and so presumably at greatest risk of heart and lung

disorders) are those least likely to stay in a study,

irrespective of the treatment to which they were originally

assigned. The presumption I make is that this higher overall

attrition rate Is due to heavier smokers being more prone to drop

out of school or to attend class less regularly. I would be

surprised if it were due to a greater likelihood of refusing to

be in a study during days when the student was actually in

school.

The attrition process Biglan and Ary discuss constitutes a

serious threat to external validity, for it means that treatments

are tested less well with the very high school populations most

likely to begin smoking. Thus, the treatments are tested on

those who need them least. One consequence of this is

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uncertainty about whether the treatments so developed are as

effective with the groups that need them most as they are with

others. A more disquieting consequence, advanced by McKnight

(1982), is that the treatments so developed will be totally

ineffective with the populations at greatest risk because they or

their representatives may refuse to cooperate with treatments

that are inadvertently impregnated with a set of cultural

assumptions they find unacceptable.

Biglan and Ary also present data about a quite different form of

attrition. They suggest that students who experience smoking

prevention treatments are more likely to drop out of a study when

compared to the students In no-treatment control groups. At

issue here is treatment-correlated attrition rather than the

overall attrition discussed above which is not a causal

consequence of smoking prevention treatments. If we assume that

the Biglan and Ary finding is not due to chance, it is difficult

to interpret. It does not seem likely that a simple smoking

prevention program would increase the rate at which students stay

away from school or leave school for good. A more likely

possibility is that the prevention treatment caused more students

to drop out of the measurement framework. Even so, it is unclear

why students would refuse measurement because they had earlier

experienced a treatment. Hence, it is important to examine

whether treatment-correlated attrition happens in future smoking

prevention studies. If it does, one of its technical

consequences will be quite troublesome, for researchers will have

to analyze data as though they came from a quasi-experiment

rather than a randomized experiment. Data analysis is much more

problematic with quasi-experiments, and only with Interrupted

time-series studies is there anything even approaching consensus

about analysis (Cook and Campbell 1979).

Another issue deserves attention when considering sample

attrition. This is the practical problem of following up high

school dropouts to collect long term data. For nearly all

researchers, the poor constitute one of the most difficult to

reach social groups in this nation. Thls is especially true of

young, inner-city males who tend to drop out of school early and

take to the streets in rates that exceed those of other

adolescents and other poor people. Yet the stakes involved in

tracing such youths are particularly high for prevention

researchers, since they are among the groups with the highest

risk of the heart and lung problems that smoking causes. Yet

keeping these youths in the treatment and measurement framework

of a study creates logistical and financial headaches. It also

leads to technical trade offs resulting from the youths’ only

partial exposure to experimental materials.

The issue of dropouts being particularly in need of the health

outcomes smoking prevention is trying to attain relates to a

secular trend that is now taking place. For reasons of which we

are not yet fully aware, prevention is part of the current

Zeitgeist in many health related areas, and the probability of

216
smoking is already declining among high school students. Thus,

the escalator is already going in the direction prevention

researchers want to take It. In light of this, we need to ask:

What should the objectives of prevention research be if larger

social forces are already leading to a decrease in smoking?

A number of possibilities come to mind. Prevention research

might continue with its current priorities and the school

populations it currently serves in the hope of accelerating the

downward escalator. If it is successful in this, many lives and

dollars will be saved, the exact magnitudes of which cannot be

estimated.

However, a more Important result would be if prevention research

not only speeded the decrease but also lowered the baseline

eventually reached. This would entail a lower level of eventual

smoking and medical complications than would have arisen from the

Zeitgeist alone. But to achieve a lower baserate entails

persuading some young persons not to smoke who would otherwise

have done so despite the Zeitgeist.

Who are these persons? While we cannot identify them all, one

subgroup stands out: The “hard-to-reach” youngsters who now

leave school early or attend only sporadically from ninth grade

on. They smoke more than most other demographic groups, and they

suffer more often than others from the physical consequences of

smoking. Reaching and changing such persons will almost

certainly lower the baseline compared to what it might have been,

also decreasing the personal misery and costs to society

associated with the poorer physical condition of these young

people.

Nearly all smoking prevention efforts have been developed by

middle-class white intellectuals and mostly tested in schools

with a similar profile. It is not clear how well the programs

and research experience so developed transfer to schools in

poorer neighborhoods where smoking may be embedded in unique

cultural contexts and may be uniquely related to the use of other

drugs. Will the programs be Implemented as widely in these

schools as in middle-class ones? Will they be implemented as

well? W ill they be as effective if implemented as well? These

are serious questions to which we do not now have an answer.

One precondition for probing these issues is that prevention

researchers include in their studies populations of poor, urban

adolescents. A second precondition is that they tackle, head-on,

the problems of maintaining contact with these youths after they

have left school. While the difficulties associated with each of

these taskes are legion, they are not insurmountable and have to

be broached if we are to (1) demonstrate long-term abstinence

from smoking in these young people, despite all the social

pressures in their social environment that impel them to it; and

(2) probe whether the final smoking rate stabilizes at a lower

rate than would have been the case if the Zeitgeist has done its

217
work with only the current level of school-based smoking

prevention.

CONCLUSION

Things can be done to improve the design of individual studies

that have schools as the unit of analysis, but where few schools

are available for study. Some of them are outlined in the first

section of this paper. However, the conclusion is reached that,

despite such Improvements in research design and analysis--which

we would like to see institutionalized-confident inference about

reliable causal connections involving smoking treatments will

depend on reviews of multiple studies rather than on single

studies. Such reviews are called for on the most Important

substantive issues in the field.

Four different types of causal knowledge can be gained from field

research on smoking prevention and cessation. In the second

section of this paper I argue that the highest-priority causal

information is needed about “what works” in a global sense. The

next highest priority is to begin identifying what it is about

global treatments that makes them effective, including analyses

of the conditions on which effectiveness Is contingent. I

suggest that the lowest level of priority should be accorded to

knowledge about causal explanatory processes--defined as the

identification of micromediating causal mechanisms. Scholars

will undoubtedly object to these priorities; and we can be sure

that, even if research was funded to meet the priorities

designated above, researchers’ preferences would nevertheless

lead them to expend considerable effort to define treatments

better, to identify causal contigencies, and to understand causal

micromediating processes. This would not necessarily be

counter productive, for if some knowledge of these types of

causation can be obtained without compromising knowledge of the

causal connections associated with ameliorative treatment

packages, it would be useful indeed.

The priority ordering I prefer leads to the advocacy of

large-scale, multisite studies, preferably contrasting maximally

different global smoking prevention treatments, and including a

heterogeneous collection of schools, implementation measures, and

outcome variables. Such studies do not totally conflict with

modest expectations about the interpretability of Individual

studies, since such studies would have multiple schools in each

treatment condition and would therefore avoid at least the

problems associated with few schools per treatment. Moreover,

the studies could be designed to avoid many of the problems

recently identified in past multisite studies. And they need not

Involve a single research contractor carrying out the research.

Both Cronbach (1982) and Campbell (1984) have suggested setting

up several smaller studies of an issue rather than relying on a

single large experiment. The key is multiple repliction, whether

through metaanalysis, primary data collection done in one large

study, or primary data collection conducted simultaneously in

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several smaller studies of what appears to be the same issue.

It seems that the high school students most likely to smoke

heavily are those least likely to remain In prevention studies.

This is serious prima facle. It is doubly serious If one

acknowledges that per capita smoking is going down among young

people in general. Given this decrease, how can more prevention

efforts be Justified? One justification Is that such efforts

will speed up the decrease that is already taking place; a second

justification is that such efforts may lead to a lower eventual

baserate of hard-core smokers; and a third justification is that

prevention efforts are most likely to lower this baserate if

prevention efforts are targeted at the urban poor who, as a

group currently suffer most from smoking. The second and third

justifications are related. If prevention efforts are not

targeted at the heaviest smoking groups that are also least

likely to stay in school, it will be all the more difficult to

use school-based programs to lower the national base of smokers

in general and of heavy smokers in particular.

Work is therefore needed to examine-and, if necessary,

develop--treatments that are appropriate for poorer youths. We

will also need to ask whether schools might be the most

appropriate setting for such studies. If they are--even as only

part of the total armamentarium of efforts--the current set of

smoking prevention researchers may need to be expanded, or may

need new skills, in order to be able to operate in the special

ecology of schools in poor neighborhoods.

REFERENCES

Campbell, D.T. Can one be scientific in applied social science?

In Conner, R.F., Altman, D.G., Jackson, C. Evaluation Studies

Review Annual (Vol. 9). Beverly Hills, CA: Sage Publications,

1984.

Cannell, L., and Turner, G. Results from The evaluation of

school health curricula. International Journal of

Education, in press.

Cook, T.D. Post-positivist critical multiplism. In: Shotland,

L.L. and Mark, M.M., eds. Social and Policy.

Beverly Hills, CA: Sage Publications, 1985.

Cook, T.D. Evaluation: Whose questions should be asked? In:

Gilbert, G.R., ed. Making and Managing Policy:

Formulation, Analysis, and Evaluation. New York:

Marcel Dekker, 1984.

Cook, T.D. Evaluating health education curricula: An exemplary

evaluation that should have failed. International Journal of

Education, in press.

Cook, T.D., and Campbell, D.T. Quasi-experimentation: Design

and analysis issues for research in field settings.

Boston: Houghton-Mifflin, 1979.

Cook, T.D. and Campbell, D.T. The causal quasi-foundations of

quasi-experimentation. Synthese, in press.

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Cook, T.D., and Leviton, L.C. Reviewing the literature: A

comparison of traditional methods with metaanalysis. J Pers,

48:449-472, 1980.

Cook, T.D.; Leviton, L.C.; and Shadish, W.R. Program evaluation.

In: Lindzey, G., and Aronson, E., eds. Handbook of Social

Psychology, 3rd ed. Reading, MA: Addison-Wesley, 1985.

Cook, T.D. and Pearlman, B. The relationship of economic

growth to inequality in the income distribution. In Lerner,

M.J. & Lerner, S., eds. The Justice Motive in social

Behavior: Adapting to times of Scarcity and Change.

New York: Wiley, 1981.

Cook, T.D. and Shadish, W.R. Program evaluation: The worldly

science. Annual Review of Psychology., in press.

Cronbach, L. J. Designing Evaluations of Educational and

Social Programs. San Francisco: Jossey-Bass, 1982.

Guba, E.G. and Lincoln, Y.S. Effective Evaluation: Improving

the Usefulness of Evaluation Results Through Responsive and

Naturalistic Approaches. San Francisco, CA: Jossey-Bass,

1981.

Flay, B.R. and Cook, T.D. The evaluation of mass media

prevention campaigns. In Rice, R.E. & Paisley, W.J., eds.

Public Communication Campaigns. Beverly Hill, CA:

Sage Publications, 1985.

McKnight, J. Health in the post-medical era. Health and

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Young, M. Plans for Evaluation in Bilingual Education.

Arlington, VA: Development Associates, 1984.

AUTHOR

Thomas Cook, Ph.D.

Center for Urban Affairs and

Policy Research

Northwestern University

2040 Sheridan Road

Evanston, Illinois 60201

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Future Directions in Drug Abuse

Prevention Research

Robert J. Battjes, D.S.W., and Catherine S. Bell, M.S.

Preventive interventions exist today that were unknown a decade

ago. These interventions go beyond simple demonstration of the

health consequences of smoking and alcohol and drug abuse to

approaches theoretically based in human developmental and behavioral

psychology. A number of researchers have become interested in

testing prevention approaches to drug abuse behavior, and rapid

changes have resulted, not only in intervention content, but also in

research design and methods of analysis. These changes have

provided many answers, as well as new and challenging areas for

future research.

The preceding chapters have reviewed research related to three

approaches to smoking prevention: social inoculation, social

skills, and cognitive-developmental. The first two approaches have

been studied extensively by a number of scientists. These

approaches share much in common. Both focus on skills development

and emphasize the importance of role play and extensive practice in

the skill development process. Both stress the importance of social

influences, especially of peer pressures, in the initiation of

tobacco smoking and other drug abuse behaviors, and they utilize

similar techniques to help youth recognize and deal with these

influences.

The two approaches differ in the extent to which they focus directly

on substance use. The social inoculation approach, as described by

Flay, focuses narrowly on substance use and the skills needed to

resist social influences to use. The social skills approach, as

described by Botvin and Wills, is based on the notion that other

factors in addition to social influences explain drug use. Thus,

this approach focuses on a variety of social skills in addition to

social resistance skills. Many of these skills do not directly

relate to substance use. By helping youth deal with other developmental challenges and, thus, feel more confident and comfortable

with themselves, it is assumed that substance use can be prevented.

The third approach reviewed i n this monograph, the cognitivedevelopmental approach described by Glynn, Leventhal, and Hirschman,

221
has not yet received the same degree of scrutiny as the other two.

It is included in this volume because it provides a contrasting

approach. It pays relatively little attention to the social

influences which motivate the initiation of tobacco smoking.

Instead it focuses on perceptions of use, experiences with initial

use, and how cognitive processes regarding the smoking experience

can be altered to discourage use.

This chapter will focus largely on the social inoculation and social

skills research, which are similar not only in program focus but

also in research methods employed and issues confronting the

research. The purpose of this concluding chapter is to identify

priorities for future research based on the state-of-the-art reviews

in the preceding chapters.

As noted above, the social inoculation and social skills approaches

to smoking prevention have been studied by a number of investigators. While early research in this area, begun in the mid 197Os,

had a number of serious methodological flaws, the research has since

become increasingly sophisticated. Data from a number of studies

suggest that these approaches can prevent or delay tobacco use for

as much as 3 years post intervention.

However, even the best of studies has limitations which confound

interpretation of the results. Additional research is needed to

address limitations in previous studies and to further develop and

refine these prevention approaches. Research is also needed to

confirm preliminary evidence of short-term effectiveness in preventing alcohol and drug use in addition to tobacco use.

The efforts of the social scientists reviewed in the preceding

chapters suggest that the use of tobacco can be reduced among those

adolescents participating in the preventive interventions. Moreover, the evidence suggests that similar interventions may be

effective in reducing or delaying the onset of other drug abuse

behaviors.

A number of challenges to the research appear to be shared among

these projects. The remainder of this chapter will summarize these

challenges and provide suggestions for future research directions.

First, three general considerations concerning the magnitude,

duration, and generalizability of program effects will be presented.

GENERAL CONSIDERATIONS

The first consideration deals with the magnitude of the intervention

effect. As noted in the chapters by Botvin and Wills, and Flay, a

number of authors have reported a reduction in adolescent smoking

initiation of approximately 50 percent. Often the actual rates of

initiation are not reported, leaving the interpretation of results

unclear. Smoking has a low frequency onset in junior high school.

Therefore, a reduction of 50 percent may reflect a program effect on

a small proportion of the students exposed to the program. The

immediate effect of the program on these students may ultimately be

222
less important than the potential effect of the program on the

remainder. Thus, the interpretation of initial findings must be

approached cautiously with many populations of young adolescents.

It will often be necessary to follow subjects for an extended period

of time before enough subjects are at risk to permit the assessment

of the intervention's practical significance.

The second consideration addresses the question of how long is it

reasonable to expect the program impact to be sustained. Unfortunately, the effects of the interventions appear to dissipate over

relatively short periods of time. This has led investigators to add

booster sessions in subsequent years to sustain behavioral change

into the high school years. Such efforts, of course, require the

expenditure of funds and resources, raising cost-benefit questions.

Future studies should validate the need for, cost effectiveness of,

and appropriate timing of booster sessions.

The final consideration deals with the potential for dissemination

and the possibility of deterioration with general application. To

date, junior high schools with well motivated, predominately white

middle class students have been the site for the psychosocial

intervention research. Moreover, these projects have usually been

implemented by highly motivated scientists with the assistance of

Federal funds not available to schools in general. Future research

must go beyond the laboratory environment and address questions

related to acceptance and utility of the preventive interventions by

traditional educators in typical school settings.

SPECIFIC CONSIDERATIONS

The following concepts were culled from the preceding chapters and

from the discussion during the RAUS review meeting. They represent

not only a summary critique, but also a series of guidelines for

future research. This section has been broken down into three

categories: (1) major threats to the validity of existing research;

(2) other issues that compromise the validity, interpretability, or

generalizability of existing research findings; and (3) additional

areas of research that warrant attention.

There appear to be three major threats to the validity of research

on the psychosocially based interventions:

Attrition of subjects has been identified as a problem in a

few studies, whereas many studies have not addressed this

question at all. Attrition can present problems in terms

of both the external and internal validity of a study.

Research evidence suggests that subjects who are lost to

the study represent a disproportionately large number of

users of tobacco and other substances. Thus, high

attrition rates may limit the generalizability of study

findings to individuals who are at relatively low risk of

use. If there is differential attrition among conditions,

an apparent treatment effect may actually be due to the

loss of high-risk subjects from the treatment group(s).

223
Existing data from completed studies should be examined to

assess possible effects of attrition, looking both at rates

of attrition and characteristics of subjects who have

dropped out of each condition. Future studies and followups on existing studies should carefully attend to subject

tracking to minimize attrition. Without special efforts,

attrition is likely to be an increasingly serious problem

in longer term followups and in research with low-income

populations.

As Flay has pointed out, previous research has not

controlled for possible Hawthorne effects. While some

studies have included comparison treatment conditions,

these conditions have not been comparable to the experimental condition in terms of intensity or instructional

methods. Research is needed which compares the effectiveness of psychosocial approaches with programs that are

as similar as possible to the experimental treatment

without including the program elements presumed to be

responsible for change.

Especially of concern is the possibility that the special

attention provided in the program would lead to an underreporting of substance use rather than actual reduced

levels of use, a concern regarding the validity of selfreport data on substance use. Most of the social

inoculation and social skills studies have included

biochemical validation or a bogus pipeline procedure to

increase honesty in self-report. However, the objective

biochemical evidence has not been reported in many

studies. Indeed the lack of sensitivity of commonly

utilized testing procedures to detect experimental smoking

makes validation of such smoking unlikely. Small-scale

studies of biochemical validation procedures utilizing

saliva cotinine, expired carbon monoxide, or combinations

of measures should be conducted to assess further the

validity of self-report data.

Additional methodological and analytical issues follow:

Most studies have utilized schools as the unit of assignment to treatment conditions. Until recently the number of

schools assigned has been so small that random assignment

does not assure comparability. Even in the larger studies

the number of schools in any condition is often relatively

small. Both initial differences among treatment conditions

and differences that may emerge during the intervention or

followup periods have received relatively little attention

in most prior studies. Careful attention to and, where

possible, control for differences need to be incoorporated

in all future studies.

Although schools have been used as the unit of assignment

in most studies, individual subjects or classrooms have

224
been used as the unit of analysis. As Cook has pointed

out, the unit of analysis should be the same as the unit of

assignment for major analyses of program effects, although

subanalyses of differential effects may require using

subjects as the unit of analysis. Where numbers of units

permit, schools should be used as the unit of analysis for

major analyses. Where numbers do not permit this, the

research must be considered quasi-experimental, and

appropriate precautions must be taken to assess possible

threats to the validity of the results.

Existing studies have paid relatively little attention to

differential program effectiveness for various subcategories of students. More needs to be know about the

characteristics of students who respond favorably versus

those who fail to respond to these programs.

Some studies have presented results only for subjects who

have never smoked at pretest, whereas other studies have

reported on nonsmokers and experimenters, and yet others

have reported on all subjects. To understand the impact of

an intervention program, it is essential that results be

reported for all categories of pretest smoking. Comparison

across programs would be facilitated by the use of similar

categories across studies.

There is also considerable variability in the way in which

the magnitude of program effects is reported. As noted

above, a number of investigators report a percentage

reduction in smoking initiation, e.g., the rate of

initiation in the experimental group was 50 percent less

than in the control group. Often not reported are the

actual rates of initiation. Other investigators have

reported differences in average cigarette consumption,

e.g., a mean consumption rate of 2 cigarettes per month in

the experimental group versus 4 cigarettes per month in the

control group. Such reporting leaves unspecified the

nature of the program impact. Are there fewer smokers or

smokers using less? Is the program having a small impact

on many subjects or is it having a substantial impact on a

few? Greater clarity is needed in reporting the magnitude

of program effect. Consistency across studies would again

facilitate program comparisons.

With long-term followups the possibility of reactivity due

to repeated measurement exists. Consideration should be

given where feasible to controlling for repeated

measurement by using subsamples on various measurement

occasions.

Additional areas of research that have received insufficient

attention thus far warrant further attention:

225
To date most of the research has been conducted with

primarily white middle-class students. The extent to which

these approaches may generalize to low-income and ethnic

minority populations is unknown. Some research to address

this question is currently in progress, but more is needed.

A number of the preceding authors have emphasized the need

for increased attention to mediating variables in order to

assess the processes by which program effects are

achieved. For example, if it is hypothesized that smoking

can be prevented by teaching refusal skills, then the

extent to which such skills are learned and utilized needs

to be measured, and change in refusal skills must then be

related to change in smoking behavior. Focus on mediating

variables is necessary to determine if the program is

working as it is presumed to work and to differentiate

effective from ineffective program components. The

technology to measure mediating variables needs further

refinement with attention to avoiding monomethod bias in

measurement procedures used. While the measurement of

mediating variables should be a part of any large- scale

field trial, small-scale studies of program components can

help to refine intervention approaches economically.

In addition to the dissemination issues identified above,

research also needs to address such questions as the

acceptability of instructional methods to teachers,

packaging of programs to facilitate adoption, and teacher

training modules.

A few issues that have received attention in previous

studies require further exploration. One concerns the

critical age(s) for intervention and the appropriate

content and approach for different grade levels. A second

issue concerns peer leaders. There is some support for the

use of peer leaders, but the evidence is not conclusive.

Research is needed to clarify the value of peer leaders,

characteristics of effective peer leaders, and roles

appropriate to peer leaders versus teachers.

The interrelationship between intervention programs and the

environments in which they occur has received relatively

little attention. The environmental factors that contribute to the success or failure of an intervention should

be consistently explored. Similarly, the effect of the

intervention on the environment, especially on the social

contingencies that support substance use or abstinence,

should be considered. Measurement technology to accomplish

this needs to be refined.

Emphasis on long-term followup in the social inoculation/

skills research is laudable. Followups as long as 3 years

post intervention have been conducted. However, since many

programs target sixth and seventh graders, and since many

226
youth initiate smoking and other substance use during high

school, students should be followed through the end of

their high school careers. The higher levels of smoking by

the senior year of high school will also permit a more

effective use of biochemical validation.

Research has been conducted primarily with schools as the

unit of assignment on the basis of two assumptions. One

assumption is that a key element of the intervention is its

influence on the school environment. The second assumption

is that interaction between experimental and control subjects will contaminate program effects. Neither assumption

has been tested. Given the implications of the unit of

assignment on the cost and rigor of the research, these

assumptions should be verified.

The social skills approach contains the essential elements

of the social inoculation approach plus additional program

elements. Class time required for this approach is considerably longer than for social inoculation. Research

should compare these approaches to assess whether the

additional program elements result in incremental effectiveness and whether there are differences in the target

groups with whom the approaches are effective.

SUMMARY

For most youth, substance use appears to be the result, in large

part, of social influences. Thus, teaching youth to resist these

influences appears to be a reasonable approach to the prevention of

use. However, it is not realistic to assume that all youth use for

the same reason or respond to the same prevention approach.

Moreover, identification of factors that act to promote or deter the

transition from experimental or occasional use to abuse has not been

addressed by these studies. While the social inoculation and social

skills approaches appear to hold considerable promise for many

youth, the research results indicate that a sizeable number of youth

initiate and escalate use in spite of these programs. It appears

that those youth who are most at risk for compulsive drug use are

those who use drugs for reasons other than social influences (Robins

and Przybeck 1985).

Thus there is a need not to focus on any single prevention approach,

but to explore multiple strategies. Identifying effective

prevention approaches also requires the ability to target programs--

to identify which types of individuals are effectively reached with

a specific approach. Alternative programs, such as the cognitivedevelopmental approach described by Glynn, Leventhal, and Hirschman,

warrant additional attention.

A host of areas needing further research have been identified

above. While the RAUS review participants did not establish

priorities among areas, some attempt to do so is necessary since

funds available for research are limited. Most important is the

227
need for research on the long-term efficacy of social inoculation

and social skills programs in the prevention of alcohol and other

drug abuse, research that would extend through high school. Another

important priority is the assessment of program effects with

low-income and ethnic minority populations. Also of importance is

research designed to control for possible Hawthorne effects. Of

somewhat less importance is research to compare social inoculation

and social skills programs or research to identify the effective

components of interventions.

A number of points raised by the authors serve as guidelines for all

future research. Important among these are: (1) attention to

attrition; (2) differences among schools; (3) differential effects

for various groups; and (4) the ways in which data are analyzed and

reported.

As has been noted in the preceding chapters, even the best of

studies have limitations that confound interpretation of the

results. It is important to recognize, however, that if the

short-term results reported by these groups of investigators are of

sufficient magnitude, and if they are replicable and sustainable, it

could justify dissemination of preventive intervention programs to

the educational community. With the relative success of the current

research efforts, the development of more sensitive measurement

techniques and noninvasive verification measures, and the ability to

identify and strengthen intervention components, it is likely that

future efforts will result in a substantial reduction in the

incidence and prevalence of drug abuse among children and

adolescents.

REFERENCE

Robins, L.N., and Przybeck, T.R. Age of onset of drug use as a

factor in drug and other disorders. In: Jones, C.J., 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, D.C.: Supt. of

Docs., U.S. Govt. Print. Off., 1985.

AUTHORS:

Robert J. Battjes, D.S.W.

Catherine S. Bell, M.S.

Division of Clinical Research

National Institute on Drug Abuse

5600 Fishers Lane

Rockville, Md. 20857

228
LIST of PARTICIPANTS

Robert J. Battjes, D.S.W.

Associate Director for Planning

Division of Clinical Research

National Institute on Drug Abuse

5600 Fishers Lane

Rockville, Maryland 20857

Catherine S. Bell, M.S.

Acting Chief

Prevention Research Branch

National Institute on Drug Abuse

5600 Fishers Lane

Rockville, Maryland 20857

Anthony Biglan, Ph.D.

Oregon Research Institute

195 West 12th Avenue

Eugene, Oregon 97401

Gilbert Botvin, Ph.D.

Cornell Univ. Medical College

Department of Public Health

411 East 69th Street

New York, New York 10021

Barry S. Brown, Ph.D.

Acting Director

Division of Prevention and

Communications

5600 Fishers Lane

Rockville, Maryland 20857

Thomas Cook, Ph.D.

Center for Urban Affairs and

Policy Research

Northwestern University

2040 Sheridan Road

Evanston, Illinois 60201

Jack Durell, M.D.

Director, Office of Science

National Institute on Drug Abuse

5600 Fishers Lane

Rockville, Maryland 20857

Brian Flay, Ph.D.

John Stauffer Pharmacology

Sciences Center

Health Behavior Research Inst.

Univ. of Southern California

1985 Zonal Avenue

Los Angeles, California 90033

Russel Glasgow, Ph.D.

Department of Psychology

North Dakota State University

Fargo, North Dakota 58105

Kathleen Glynn, Ph.D.

Mt. Sinai Medical Center

950 North 12th

Milwaukee, Wisconsin 53233

Charles L. Gruder, Ph.D.

University of Illinois

at Chicago Circle

Department of Psychology

Box 4348

Chicago, Illinois 60680

Jerome Jaffe, M.D.

Acting Director

National Institute on Drug Abuse

5600 Fishers Lane

Rockville, Maryland 20857

Harry Lando, Ph.D.

Department of Psychology

Iowa State, W112 Quadrangle

Ames, Iowa 50011

Jacqueline Ludford, M.S.

Chief, Research Analysis Branch

National Institute on Drug Abuse

5600 Fishers Lane

Rockville, Maryland 20857

William McCarthy, Ph.D.

Univ. of California, Los Angeles

Department of Psychology

1282 Franz Hall

Los Angeles, California 90024

229
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Institute on

monograph series

While limited supplies last, single copies of the monographs may be

obtained free of charge from the National Clearinghouse for Drug

Abuse Information (NCDAI). Please contact NCDAI also for information about availability of coming issues and other publications of

the National Institute on Drug Abuse relevant to drug abuse research.

Additional copies may be purchased from the U.S. Government Printing

Office (GPO) and/or the National Technical Information Service

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and prices may not be shown because they had not been assigned when

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Microfiche copies, at $4.50, are also available from NTIS. Prices

from either source are subject to change.

Addresses are:

NCDAI

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GPO

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1 FINDINGS OF DRUG ABUSE RESEARCH. NCDAI out of stock

Vol. 1: GPO out of stock NTIS PB #272 867/AS $32.50

Vol. 2: GPO out of stock NTIS PB #272 868/AS $29.50

2 OPERATIONAL DEFINITIONS IN SOCIO-BEHAVIORAL DRUG USE RESEARCH

1975. Jack Elinson, Ph.D., and David Nurco, Ph.D., eds. NCDAI out

of stock GPO out of stock NTIS PB #246 338/AS $16

3 AMINERGIC HYPOTHESES OF BEHAVIOR: REALITY OR CLICHE? Bruce J.

Bernard, Ph.D., ed. NCDAI out of stock

GPO out of stock NTIS PB #246 687/AS $16

230
4 NARCOTIC ANTAGONISTS: THE SEARCH FOR LONG-ACTING PREPARATIONS.

Robert Willette, Ph.D., ed.

GPO out of stock NTIS PB #247 096/AS $8.50

5 YOUNG MEN AND DRUGS: A NATIONWIDE SURVEY. John A. O'Donnell,

Ph.D., et al. NCDAI out of stock

GPO out of stock NTIS PB #247 446/AS $16

6 EFFECTS OF LABELING THE "DRUG ABUSER": AN INQUIRY. Jay R.

Williams, Ph.D. NCDAI out of stock

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7 CANNABINOID ASSAYS IN HUMANS. Robert Willette, Ph.D., ed.

NCDAI out of stock

GPO Stock #017-024-01151-7 $5 NTIS PB #251 905/AS $14.50

8 Rx: 3x/WEEK LAAM - ALTERNATIVE TO METHADONE. Jack Blaine, M.D.,

and Pierre Renault, M.D., eds.

Not available from GPO NTIS PB #253 763/AS $14.50

9 NARCOTIC ANTAGONISTS: NALTREXONE PROGRESS REPORT. Demetrios

Julius, M.D., and Pierre Renault, M.D., eds. NCDAI out of stock

GPO out of stock NTIS PB #255 833/AS $17.50

10 EPIDEMIOLOGY OF DRUG ABUSE: CURRENT ISSUES. Louise G. Richards,

Ph.D., and Louise B. Blevens, eds. NCDAI out of stock

GPO out of stock NTIS PB #266 691/AS $22

11 DRUGS AND DRIVING. Robert Willette, Ph.D., ed. NCDAI out of

stock

GPO Stock #017-024-00576-2 $5.50 NTIS PB #269 602/AS $16

12 PSYCHODYNAMICS OF DRUG DEPENDENCE. Jack D. Blaine, M.D., and

Demetrios A. Julius, M.D., eds. NCDAI out of stock

GPO out of stock NTIS PB #276 084/AS $17.50

13 COCAINE: 1977. Robert C. Petersen, Ph.D., and Richard C.

Stillman, M.D., eds. NCDAI out of stock

GPO out of stock NTIS PB #269 175/AS $19

14 MARIHUANA RESEARCH FINDINGS: 1976. Robert C. Petersen, Ph.D.,

ed. NCDAI out of stock

GPO out of stock NTIS PB #271 279/AS $22

15 REVIEW OF INHALANTS: EUPHORIA TO DYSFUNCTION. Charles Wm. Sharp,

Ph.D., and Mary Lee Brehm, Ph.D., eds.

GPO out of stock NTIS PB #275 798/AS $28

16 THE EPIDEMIOLOGY OF HEROIN AND OTHER NARCOTICS. Joan Dunne

Rittenhouse, Ph.D., ed. NCDAI out of stock

GPO out of stock NTIS PB #276 357/AS $20.50

231
17 RESEARCH ON SMOKING BEHAVIOR. Murray E. Jarvik, M.D., Ph.D., et

al., eds. NCDAI out of stock

GPO out of stock NTIS PB #276 353/AS $29.50

18 BEHAVIORAL TOLERANCE: RESEARCH AND TREATMENT IMPLICATIONS.

Norman A. Krasnegor, Ph.D., ed.

GPO out of stock NTIS PB #276 337/AS $16

19 THE INTERNATIONAL CHALLENGE OF DRUG ABUSE. Robert C. Petersen,

Ph.D., ed.

GPO out of stock NTIS PB #293 807/AS $28

20 SELF-ADMINISTRATION OF ABUSED SUBSTANCES: METHODS FOR STUDY.

Norman A. Krasnegor, Ph.D., ed.

GPO out of stock NTIS PB #288 471/AS $22

21 PHENCYCLIDINE (PCP) ABUSE: AN APPRAISAL. Robert C. Petersen,

Ph.D., and Richard C. Stillman, M.D., eds.

GPO out of stock NTIS PB #288 472/AS $25

22 QUASAR: QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIPS OF

ANALGESICS, NARCOTIC ANTAGONISTS, AND HALLUCINOGENS. Gene Barnett,

Ph.D.; Milan Trsic, Ph.D.; and Robert Willette, Ph.D.; eds. NCDAI

out of stock

GPO out of stock NTIS PB #292 265/AS $35.50

23 CIGARETTE SMOKING AS A DEPENDENCE PROCESS. Norman A. Krasnegor,

Ph.D., ed. NCDAI out of stock

GPO Stock #017-024-00895-8 $6 NTIS PB #297 721/AS $19

24 SYNTHETIC ESTIMATES FOR SMALL AREAS: STATISTICAL WORKSHOP PAPERS

AND DISCUSSION. Jos. Steinberg, ed. NCDAI out of stock

GPO out of stock NTIS PB #299 009/AS $23.50

25 BEHAVIORAL ANALYSIS AND TREATMENT OF SUBSTANCE ABUSE. Norman A.

Krasnegor, Ph.D., ed.

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26 THE BEHAVIORAL ASPECTS OF SMOKING. Norman A. Krasnegor, Ph.D.,

ed.

GPO out of stock NTIS PB #80-118755 $17.50

27 PROBLEMS OF DRUG DEPENDENCE, 1979: PROCEEDINGS OF THE 41ST

ANNUAL SCIENTIFIC MEETING, THE COMMITTEE ON PROBLEMS OF DRUG DEPENDENCE, INC. L.S. Harris, Ph.D., ed. NCDAI out of stock

GPO Stock #017-024-00981-4 $9 NTIS PB #80-175482 $37

28 NARCOTIC ANTAGONISTS: NALTREXONE PHARMACOCHEMISTRY AND

SUSTAINED-RELEASE PREPARATIONS. Robert Willette, Ph.D., and

Gene Barnett, Ph.D., eds. NCDAI out of stock

GPO out of stock NTIS PB #81-238875 $23.50

232
29 DRUG ABUSE DEATHS IN NINE CITIES: A SURVEY REPORT. Louis A.

Gottschalk, M.D., et al. NCDAI out of stock

GPO Stock #017-024-00982-2 $6.50 NTIS PB #80-178882 $17.50

30 THEORIES ON DRUG ABUSE: SELECTED CONTEMPORARY PERSPECTIVES. Dan

J. Lettieri, Ph.D.; Mollie Sayers; and Helen Wallenstein Pearson,

eds. NCDAI out of stock

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31 MARIJUANA RESEARCH FINDINGS: 1980. Robert C. Petersen, Ph.D.,

ed.

GPO out of stock NTIS PB #80-215171 $20.50

32 GC/MS ASSAYS FOR ABUSED DRUGS IN BODY FLUIDS. Rodger L. Foltz,

Ph.D.; Allison F. Fentiman, Jr., Ph.D.; and Ruth B. Foltz.

GPO out of stock NTIS PB #81-133746 $19

33 BENZODIAZEPINES: A REVIEW OF RESEARCH RESULTS, 1980. Stephen I.

Szara, M.D., D.Sc., and Jacqueline P. Ludford, M.S., eds.

GPO Stock #017-024-01108-8 $5 NTIS PB #82-139106 $13

34 PROBLEMS OF DRUG DEPENDENCE, 1980: PROCEEDINGS OF THE 42ND

ANNUAL SCIENTIFIC MEETING, THE COMMITTEE ON PROBLEMS OF DRUG

DEPENDENCE, INC. Louis S. Harris, Ph.D., ed. NCDAI out of stock

GPO out of stock NTIS PB #81-194847 $34

35 DEMOGRAPHIC TRENDS AND DRUG ABUSE, 1980-1995. Louise G.

Richards, Ph.D., ed.

GPO out of stock NTIS PB #82-103417 $13

36 NEW APPROACHES TO TREATMENT OF CHRONIC PAIN: A REVIEW OF MULTIDISCIPLINARY PAIN CLINICS AND PAIN CENTERS. Lorenz K.Y. Ng, M.D.,

ed.

GPO out of stock NTIS PB #81-240913 $19

37 BEHAVIORAL PHARMACOLOGY OF HUMAN DRUG DEPENDENCE. Travis

Thompson, Ph.D., and Chris E. Johanson, Ph.D., eds.

GPO Stock #017-024-01109-6 $7 NTIS PB #82-136961 $25

38 DRUG ABUSE AND THE AMERICAN ADOLESCENT. Dan J. Lettieri, Ph.D.,

and Jacqueline P. Ludford, M.S., eds.

GPO Stock #017-024-01107-0 $4.50 NTIS PB #82-148198 $14.50

39 YOUNG MEN AND DRUGS IN MANHATTAN: A CAUSAL ANALYSIS.

Richard R. Clayton, Ph.D., and Harwin L. Voss, Ph.D.

GPO out of stock NTIS PB #82-147372 $19

40 ADOLESCENT MARIJUANA ABUSERS AND THEIR FAMILIES. Herbert

Hendin, M.D., Ann Pollinger, Ph.D., Richard Ulman, Ph.D., and

Arthur Carr, Ph.D. NCDAI out of stock

GPO out of stock NTIS PB #82-133117 $13

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41 PROBLEMS OF DRUG DEPENDENCE, 1981: PROCEEDINGS OF THE 43RD

ANNUAL SCIENTIFIC MEETING, THE COMMITTEE ON PROBLEMS OF DRUG

DEPENDENCE, INC. Louis S. Harris, Ph.D., ed. NCDAI out of stock

Not available from GPO NTIS PB #82-190760 $41.50

42 THE ANALYSIS OF CANNABINOIDS IN BIOLOGICAL FLUIDS. Richard L.

Hawks, Ph.D., ed.

GPO Stock #017-024-01151-7 $5 NTIS PB #83-136044 $16

43 PROBLEMS OF DRUG DEPENDENCE, 1982: PROCEEDINGS OF THE 44TH

ANNUAL SCIENTIFIC MEETING, THE COMMITTEE ON PROBLEMS OF DRUG

DEPENDENCE, INC. Louis S. Harris, Ph.D., ed. NCDAI out of stock

GPO out of stock NTIS PB #83-252-692/AS $40

44 MARIJUANA EFFECTS ON THE ENDOCRINE AND REPRODUCTIVE SYSTEMS.

Monique C. Braude, Ph.D., and Jacqueline P. Ludford, M.S., eds.

GPO Stock #017-024-01202-5 $4 NTIS PB #85-150563/AS $14.50

45 CONTEMPORARY RESEARCH IN PAIN AND ANALGESIA, 1983. Roger M.

Brown, Ph.D.; Theodore M. Pinkert, M.D., J.D.; and Jacqueline P.

Ludford, M.S., eds.

GPO Stock #017-024-01191-6 $2.75 NTIS PB #84-184670/AS $11.50

46 BEHAVIORAL INTERVENTION TECHNIQUES IN DRUG ABUSE TREATMENT. John

Grabowski, Ph.D.; Maxine L. Stitzer, Ph.D., and Jack E.

Henningfield, Ph.D., eds.

GPO Stock #017-024-01192-4 $4.25 NTIS PB #84-184688/AS $16

47 PREVENTING ADOLESCENT DRUG ABUSE: INTERVENTION STRATEGIES.

Thomas J. Glynn, Ph.D.; Carl G. Leukefeld, D.S.W.; and

Jacqueline P. Ludford, M.S., eds.

GPO Stock #017-024-01180-1 $5.50 NTIS PB #85-159663/AS $22

48 MEASUREMENT IN THE ANALYSIS AND TREATMENT OF SMOKING BEHAVIOR.

John Grabowski, Ph.D., and Catherine S. Bell, M.S., eds.

GPO Stock #017-024-01181-9 $4.50 NTIS PB 84-145184 $14.50

49 PROBLEMS OF DRUG DEPENDENCE, 1983: PROCEEDINGS OF THE 45TH

ANNUAL SCIENTIFIC MEETING, THE COMMITTEE ON PROBLEMS OF DRUG

DEPENDENCE, INC. Louis S. Harris, Ph.D., ed.

GPO Stock #017-024-01198-3 $12 NTIS PB 85-151553/AS $22

50 COCAINE: PHARMACOLOGY, EFFECTS, AND TREATMENT OF ABUSE. John

Grabowski, Ph.D., ed.

GPO Stock #017-020-01214-9 $4 NTIS PB 85-150381/AS $14.50

51 DRUG ABUSE TREATMENT EVALUATION: STRATEGIES, PROGRESS, AND

PROSPECTS. Frank M. Tims, Ph.D., ed. NCDAI out of stock

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52 TESTING DRUGS FOR PHYSICAL DEPENDENCE POTENTIAL AND ABUSE

LIABILITY. Joseph V. Brady, Ph.D., and Scott E. Lukas, Ph.D., eds.

GPO Stock #017-024-01204-1 $4.25 NTIS PB 85-150373/AS $16

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54 MECHANISMS OF TOLERANCE AND DEPENDENCE. Charles Wm. Sharp,

Ph.D., ed.

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55 PROBLEMS OF DRUG DEPENDENCE, 1984. PROCEEDINGS OF THE 46TH

ANNUAL SCIENTIFIC MEETING, THE COMMITTEE ON PROBLEMS OF DRUG

DEPENDENCE, INC. Louis S. Harris, Ph.D., ed.

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56 ETIOLOGY OF DRUG ABUSE: IMPLICATIONS FOR PREVENTION. Coryl LaRue

Jones, Ph.D., and Robert J. Battjes, D.S.W., eds.

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57 SELF-REPORT METHODS OF ESTIMATING DRUG USE: MEETING CURRENT

CHALLENGES TO VALIDITY. Beatrice A. Rouse, Ph.D., Nicholas J.

Kozel, M.S., and Louise G. Richards, Ph.D., eds.

GPO Stock #017-024-01246-7 $4.25

58 PROGRESS IN THE DEVELOPMENT OF COST-EFFECTIVE TREATMENT FOR DRUG

ABUSERS. Rebecca S. Ashery, D.S.W., ed.

GPO Stock #017-024-01247-5 $4.25

59 CURRENT RESEARCH ON THE CONSEQUENCES OF MATERNAL DRUG ABUSE.

Theodore M. Pinkert, M.D., J.D., ed.

GPO Stock #017-024-01249-1 $2.50

63 PREVENTION RESEARCH: DETERRING DRUG ABUSE AMONG CHILDREN AND

ADOLESCENTS. Catherine S. Bell, M.S.; and Robert J. Battjes,

D.S.W., eds.

IN PRESS

53 PHARMACOLOGICAL ADJUNCTS

Grabowski, Ph.D., ed.

IN SMOKING CESSATION. John

60 PRENATAL DRUG EXPOSURE: KINETICS AND

Ph. D., and Charles C. Lee , Ph.D., eds.

DYNAMICS. C. Nora Chiang,

61 COCAINE USE IN AMERICA: EPIDEMIOLOGIC AND CLINICAL

PERSPECTIVES. Nicholas J. Kozel, M.S., and Edgar H. Adams, M.S.,

eds.

62 THE NEUROSCIENCE OF DRUG ABUSE

David P. Friedman, Ph.D., eds

Roger M Brown, Ph.D., and

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