Health Hazards in Adolescence 9783110847659, 9783110124484

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Prevention and Intervention in Childhood and Adolescence 8

Special Research Unit 227 - Prevention and Intervention in Childhood and Adolescence An interdisciplinary

project of the University of Bielefeld

conducted by Prof. Dr. Günter Albrecht, Prof. Dr. Peter-Alexis Albrecht, Prof. Dr. Otto Backes, Prof. Dr. Michael Brambring, Prof. Dr. Klaus Hurrelmann, Prof. Dr. Franz-Xaver Kaufmann, Prof. Dr. Friedrich Lösel, Prof. Dr. Hans-Uwe Otto, Prof. Dr. Helmut Skowronek

Health Hazards in Adolescence Edited by Klaus Hurrelmann, Friedrich Lösel,

w DE

G Walter de Gruyter • Berlin • New York 1990

Klaus Hurrelmann Professor of Education and Sociology, University of Bielefeld Friedrich Losel Professor of Psychology, University of Erlangen-Niirnberg

With 57 Figures and 53 Tables

Library of Congress Cataloging-in-Publication Data Health hazards in adolescence / edited by Klaus Hurrelmann, Friedrich Lösel. X,528 p. 17x24 cm.--(Prevention and intervention in childhood and adolescence ; 8) "The papers have their origin in the international exchange network and regular conferences of the research center '[Special Research Unit 227 - ] Prevention and Intervention in Childhood and Adolescence' at the University of Bielefeld"~Pref. Includes bibliographical references and index. ISBN 0-89925-691-0 (U.S. : acid-Free paper) 1. Health bahavior in adolescence-Congresses. 2. Stress in adolescence-Congresses. 3. Health promotion-Congresses. I. Hurrelmann, Klaus. II. Lösel, Friedrich. III. Sonderforschungsbereich 227-Prevention and Intervention im Kindes- und Jugendalter. IV. Series. RJ47,53,H43 1990 613', 0433—dc20 89-23518 CIP

Deutsche Bibliothek Cataloging-in-Publication Data Health hazards in adolescence / ed. by Klaus Hurrelmann ; Friedrich Lösel. - Berlin ; New York : de Gruyter, 1990 (Prevention and intervention in childhood and adolescence ; 8) ISBN 3-11-012448-3 NE: Hurrelmann, Klaus [Hrsg.]; GT

© Printed on acid free paper © Copyright 1990 by Walter de Gruyter & Co., D - 1 0 0 0 Berlin 30. All rights reserved, including those of translations into foreign languages. No part of this book may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Printed in Germany Printing: WB-Druck GmbH, Rieden am Forggensee / Binding: Lüderitz & Bauer GmbH, Berlin/ Cover Design: Hansbernd Lindemann, Berlin.

Preface At first glance, we may think that adolescents are endowed with extreme vitality and flexibility and hence have few health problems. But at second glance, we observe that problems of health in adolescence are generally underestimated. As the papers in this volume show, health problems in adolescence differ from those in other life stages. Moreover, adolescence is a key period for problems that emerge later in adulthood. This is not only the case with respect to the long-term consequences of specific diseases; it is even more important for learning and consolidating health-related values, attitudes, self-concepts, behaviors, and life-styles. Smoking, alcohol abuse, lack of physical exercise, and other habits are often shaped in adolescence. The consequences for health, however, are usually only visible in later life. In dealing with adolescence as a key period for health-related behavior, it is important to note that health-endangering behavior is an integral part of the adolescent's daily life. Often it is not perceived as a problem by the adolescents themselves. Their focus is on coping with demands within the family, school, peer group, leisure activities, and so forth. Consequently, they choose forms of behavior that they experience as rewarding and appropriate in a social and psychological sense. In choosing such behavior, they are normally unaware that in the long run it may be health endangering for themselves or others. The papers in this volume deal with various forms, antecedents, and consequences of such behavior. The volume combines theoretical and empirical papers on (1) social, psychological, anthropological, and ecological antecedents of adolescents' health behavior; (2) the coping with stressful life events and environments; and (3) approaches to social support and to education for the development of health promotion. The papers have their origin in the international exchange network and regular conferences of the Research Center "Prevention and Intervention in Childhood and Adolescence" at the University of Bielefeld. We want to express our thanks to all contributors, to the German Research Association (Deutsche Forschungsgemeinschaft) for the grants that made the exchanges and conferences possible, to Jonathan Harrow and Liam Gilmour for their careful translation of several of the articles in this volume, and to Marcus Freitag and Monika Liebherr for editorial assistance. Bielefeld, May 1990

Klaus Hurrelmann Friedrich Lösel

Contents 1.

Basic Issues and Problems of Health in Adolescence Klaus Hurrelmann and Friedrich Losel

Part I Antecedents of Adolescents' Health Behavior 2.

Personality, Perceived Life Chances, and Adolescent Health Behavior Richard Jessor, John E. Donovan and Frances Costa

3.

Parent and Peer Effects on Adolescent Health Behavior Steve Hansell and David Mechanic

4.

Young Adults' Health and its Antecedents in Evolving Life-styles Lea Pulkkinen

5.

Subject's Implicit Anthropology. A Determinant of Mental and Physical Health Rolf Oerter

6.

Parental Child Rearing and Anxiety Development Heinz W. Krohne

7.

Youth Unemployment and Health. Results from a Five-Year Follow-Up Study. Anne Hammarstrom

8.

131

Health Impairment, Failure in School, and the Use and Abuse of Drugs Elisabeth Nordlohne and Klaus Hurrelmann

9.

115

149

Smoking and Drinking: Prospective Analyses in German and Polish Adolescents Rainer K. Silbereisen, Ute Schonpflug and Helfried T. Albrecht . . . .167

Part II: Coping with Stressful Life Events and Environments 10. Youth in Dangerous Environments: Coping with the Consequences James Garbarino 11. Antecedents and Consequences of Deviant Behavior Emmy E. Werner

vra 12. Disruptive and Antisocial Behavior in Childhood and Adolescence: Development and Risk Factors Rolf Loeber

233

13. Bullying Among School Children Dan Olweus 14. Resilience in Adolescence: A Study on the Generalizability of Protective Factors Friedrich Lösel and Thomas Bliesener

259

299

15. Behavioral/Emotional Problems in Adopted Adolescents Frank C. Verhulst and Herma Versluis-den Bieman

321

16. Coping and Health-Related Behavior. A Cross-Cultural Perspective Inge Seiffge-Krenke

339

Part m Social Support and Education for Health Promotion 17. Social Support, Health, and Health Behavior Ralf Schwarzer and Anja Leppin

363

18. Social Network Participation and Problem Behavior in Adolescence Nicholas Hopkins and Nicholas Emler

385

19. The Role of Parent and Peer Contacts for Adolescents' State of Health Birgit Holler and Klaus Hurrelmann 20. Social Networks as Resources: Relationships between Background Variables and Social Behavior Inge Bö

409

433

21. Competence Enhancement and the Prevention of Adolescent Problem Behavior Linda Dusenbury and Gilbert Botvin

459

22. Problems and Challenges in Health Education for Young Adults Gabriele E. Dlugosch and Lothar R. Schmidt 23. Innovative Approaches to Youth Information and Counseling Willi Fâché

479 503

Contributors

Albrecht, Helfried T., Universität Gießen, Fachbereich Psychologie, Otto-Behaghel-Str. 10/F1, D-6300 Gießen, FRG

Garbarino, James, Erikson Institute for Advanced Study in Child Development, 25 W. Chicago Avenue, Chicago, IL 60610, USA

Bliesener, Thomas, Universität Bielefeld, SFB 227, Universitätsstr. 25, D-4800 Bielefeld 1, FRG

Hammarström, Anne, Samhälls Medicin, Köpmangatan 36 B, S-95132 Lulea, Sweden

Bö,

Hansell, Steve, Institute for Health, Health Care Policy and Aging Research, 30 College Avenue, New Brunswick, NJ 08903, USA

Inge, Hogskolesenteret i Rogaland, P.O.B. 2557, Ullandhaug, N-4004 Stavanger, Norway

Botvin, Gilbert, Cornell University Medical College, 411 East 69th Street, KB-201, New York, NY 10021, USA Costa, Frances, Institute of Behavioral Science, University of Colorado, Campus Box 48, Boulder, CO 80309-0483, USA Dlugosch, Gabriele, Fachbereich Psychologie, Universität, Postfach 3825, D-5500 Trier, FRG Donovan, John E., Institute of Behavioral Science, University of Colorado, Campus Box 483, Boulder, CO 80309-0483, USA

Holler, Birgit, Universität Bielefeld, SFB 227, Universitätsstr. 25, D-4800 Bielefeld 1, FRG Hopkins, Nicholas, Department of Psychology, University of Dundee, Dundee DDI 4HN, UK Hurrelmann, Klaus, Universität Bielefeld, SFB 227, Universitätsstr. 25, D-4800 Bielefeld 1, FRG Jessor, Richard, Institute of Behavioral Science, University of Colorado, Campus Box 483, Boulder, CO 80309-0483, USA

Dusenbury, Linda, Cornell University, Medical College, 411 East 69th Street, KB-201, New York, NY 10021, USA

Krohne, Heinz W., Johannes GutenbergUniversität, Psychologisches Institut, Abt. Persönlichkeitspsychologie, Staudingerweg 9, D-6500 Mainz 1, FRG

Emler, Nicholas, Department of Psychology, University of Dundee, Dundee DDI 4HN, UK

Leppin, Anja, Freie Universität Berlin, Fachbereich Psychologie, Habelschwerdter Allee 45, D-1000 Berlin 33, FRG

Fâché, Willi, Rijksuniversiteit Gent, Seminarie voor Jeugdwelzijn, Louis Pasteurlaan 2, B-9000 Gent, Belgium

Loeber, Rolf, WPIC, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA 15213, USA

X Lösel, Friedrich, Universität Bielefeld, SFB 227, Universitätsstr. 25, D-4800 Bielefeld 1, FRG

Schönpflug, Ute, Freie Universität Berlin, Fachbereich Psychologie, Habelschwerdter Allee 45, D-1000 Berlin 33, FRG

Mechanic, David, Institute for Health, Health Care Policy and Aging Research, 30 College Avenue, New Brunswick, NJ 08903, USA

Schwarzer, Ralf, Freie Universität Berlin, Fachbereich Psychologie, Habelschwerdter Allee 45, D-1000 Berlin 33, FRG

Nordlohne, Elisabeth, Universität Bielefeld, SFB 227, Universitätsstr. 25, D-4800 Bielefeld 1, FRG Oerter, Rolf, Lehrstuhl Entwicklungspsychologie und Pädagogische Psychologie, Universität München, GeschwisterScholl-Platz 1, D-8000 München 22, FRG

Seiffge-Krenke, Inge, Psychologisches Institut, Universität Bonn, Römerstr. 164, D-5300 Bonn 1, FRG Silbereisen, Rainer K., Universität Gießen, Fachbereich Psychologie, Otto-Behaghel-Str. 10/F1, D-6300 Gießen, FRG

Bergen, Bergen,

Verhulst, Frank C., Sophia Kinderziekenhus, Erasmus University, Gordelweg 160, NL-3038 GE Rotterdam, The Netherlands

Pulkkinen, Lea, University of Jyväskylä, Department of Psychology, Seminaarijkatu 15, SF-40100 Jyväskylä, Finland

Versluis-den Biemann, Herma, Sophia Kinderziekenhus, Erasmus University, Gordelweg 160, NL-3038 GE Rotterdam, The Netherlands

Schmidt, Lothar R., Universität Trier, Fachbereich Psychologie, Postfach 3825, D-5500 Trier, FRG

Werner, Emmy E., University of California, 123 AOB IV, Davis, California 95616, USA

Olweus, Dan, Oysteinsgate Norway

University of 3, N-5007

1.

Basic Issues and Problems of Health in Adolescence Klaus Hurrelmann Friedrich Lösel Research Center Prevention and Intervention in Childhood and Adolescence, Bielefeld, FRG

At first glance, the topic of "health hazards in adolescence" seems to suggest a paradox. We may think that adolescents are endowed with extreme vitality and flexibility and hence have less health problems. In fact, they do show rather low prevalence rates of cancer, coronary heart diseases, and other chronic illnesses, which are the main causes of death in modern societies. They are healthier than all other subgroups of the population, a fact that is reflected, for example, by age-related health insurance fees. However, these and other impressions may be misleading. Increasingly it appears that problems of health in adolescence are generally underestimated (Hurrelmann, 1989; Jessor, 1989). Therefore it is not adequate to focus mainly on adults and the elderly, as has until recently been the case in the literature on behavioral medicine, health psychology, medical sociology, and related disciplines.

1. Basic Aspects of Health Problems in Adolescence Adolescents show considerable prevalence and incidence rates in specific problems of bio-psycho-social health. Whereas the illness and mortality rates in almost all population groups have decreased within the last decades (particularly for the very old and the very young), the opposite is the case among the 10- to 25-year-olds. Recent developments in the United States are particularly alarming, where there has been a distinct increase in the figures for mortality and illness among this subpopulation in urban areas, above all for members of ethnic minorities and the socially disadvantaged. The Carnegie Corporation (1989) has published a depressing report on this phenomenon.

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Health problems in adolescence differ from those in other life stages. For example, the most frequent causes of death in adolescence are not illnesses but traffic accidents and other unintended injuries. The proportion of those who die as a result of risk behavior related to traffic is higher in this age group than in any other comparable group. Violence, murder, homicide, and suicide make up a second leading group of causes of death. Alcohol and drug abuse, smoking, the aquired immune deficiency syndrome (AIDS) and other sexually-transmitted diseases, early pregnancy, appetite disorders, malnutrition, allergies, and emotional and behavioral disorders are other widespread problems that clearly indicate that the image of "healthy adolescence" is inaccurate. As the examples show, adolescence is a key period for problems that only emerge later in adulthood and old age. This is not only the case with respect to the long-term consequences of specific diseases; it is even more important for learning and consolidating health-related values, attitudes, self-concepts, behaviors, and life-styles. Smoking, alcohol abuse, lack of physical exercise, and other habits are often shaped in adolescence. The consequences for health, however, are usually only visible in later life. In dealing with adolescence as a key period for health-related behavior, it is important to note that health-endangering behavior is an integral part of the adolescent's daily life. Often it is not perceived as a problem by the adolescents themselves. Their focus is on coping with demands within the family, school, peer group, leisure activities, and so forth. Consequently, they choose forms of behavior that they experience as rewarding and appropriate in a social and psychological sense. In choosing such behavior, they are normally unaware that in the long run it may be health endangering. During the transition period of youth, the positive functions of problem behavior may serve to facilitate personality growth and experiences of competence; such behavior does not necessarily lead to health problems or diseases at a later stage. However, in many cases the consequences of age-specific health-endangering attitudes and behaviors are irreversible, or they may dramatically restrict the potential for future development: For example, accidents may result in severe physical handicaps, antisocial behavior may lead to stigmatization, and heavy alcohol drinking may result in chronic illness. As an important phase for the development of health problems, adolescence is also a key period for prevention. Numerous programs and evaluations demonstrate the difficulties involved in changing established health-endangering problem behaviors and life-styles. This makes the borders between the concepts of primary, secondary, and tertiary prevention (respectively: prevention, treatment, and rehabilitation) fluid in many areas. Albee (1987) is only partly

Basic Issues and Problems of Health in Adolescence

3

right when he maintains that the only successful way to diminish prevalence is by reducing incidence via primary prevention. In line with humanistic, economic, and other considerations, improved measures in all three areas are valuable in their own right (Lösel, 1987; Taylor, 1990). Nevertheless, there is widespread consensus that deficits do exist particularly in the fields of primary prevention. Primary prevention and early intervention in adolescence have the advantage that bio-psycho-social disturbances and imbalances can be tackled before they become fully developed or chronic. Furthermore, the benefits of primary prevention not only impact on the health of the target generation but are transmitted on to their offspring. As they become parents, young people with manifest problem behavior and health-endangering life-styles directly (via modeling, reinforcing) or indirectly (via stressful or disadvantaged family conditions) influence the health development of their children. This is why it would be short-sighted to focus on health care that is too strongly oriented toward temporary demographic changes. When Kurz (1987, p. 297) states that ". . . t h e psychological and physical health of future generations of adults will depend upon the quality of today's child health psychology," then this applies equally to adolescents. As in other groups or contexts, "health" in adolescence is a comprehensive term. The World Health Organisation (1946) defined health as not only the absence of disease and impairment, but the state of complete physical, psychological, and social well-being. Taken literally, this concept is an idealization that does not take into account that temporary nonattainments of a state of well-being are important motivators of human action in normal life. It views health less as a process, and it lacks precision in respect to the specific components of health. However, by changing the focus to "positive" aspects of health and broadening its dimensional scope, the WHO definition has had a substantial impact. In modern interdisciplinary research, health is used as a comprehensive term to embody a physical, psychological, and social state in which an individual is capable of processing inner and outer reality in a productive and satisfying manner. This concept adheres to theoretical approaches to human development that are based on the assumption that in the process of socialization and personality formation, biological (physical), psychological (mental), and social (environmental) factors interact and have a combined effect on health (Featherman & Lerner, 1985). According to this concept, a healthy personality is continually shaped in a concrete, historically conveyed lifeworld throughout the entire length of the life span. The lifelong interplay between biological, psychological, and sociocultural potentials and constraints determines the individual's state of health.

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This concept of health emphasizes the integration of well-being into all of the dimensions of daily life. Self-responsible behavior and self-regulation are regarded as essential factors in the development of a healthy personality. Thus, health-conscious and health-promoting life-styles can only be expected when the prerequisites for such factors are available. Health, therefore, is both a personal and a social concept. It describes the objective and subjective state of well-being that is present when the physical, psychological, and social development of a person is in harmony with his/her own potentials, goals, and prevailing living conditions. Health is impaired when demands arising in one or more of these areas cannot be coped with by the person in his/her respective stage of life. The impairment may be manifest in symptoms of physical disease, psychiatric disturbance, or social deviance (Hurrelmann, 1989). Health is closely connected to the individual and collective value systems and behavior patterns manifest in personal life-styles. It is a state of equilibrium. Due to external or internal influences, fluctuations from this state occur more or less periodically (Werner & Smith, 1982; Pickenhain, 1989). However, in the long run, the state of equilibrium must be maintained during the life course, otherwise a process of chronically ill adaptation takes place. In this view, health is not a state that is passively experienced; instead, it is the result of actively pursuing the establishment and maintenance of a social, psychological, and physical capacity for action. The theoretical foundations of the health concept presented here have been developed by numerous authors, including, among others, Bronfenbrenner (1979), Engel (1962), Levi (1971), and Matarazzo, Weiss, Herd, Miller and Weiss (1984). By focusing on life-styles, hazard control, and resource allocation, this concept is not only oriented toward the individual but incorporates the most important issues in public health (Faden, 1987). Accordingly, modern theoretical approaches in social epidemiology, social and behavioral medicine, psychiatry, health psychology, social pediatrics, and social pedagogy stress the interdependency of human development on the one hand, and the development of the social and physical environment on the other. The criterion of a "healthy" development is viewed as the acquisition of physical, psychological, and social competences and resources that enable individuals to act adequately and develop an individual identity, at the same time taking into account their own needs as well as those of other persons.

Basic Issues and Problems of Health in Adolescence

5

2. On the Prevalence of Health Problems in Adolescence The risks to mortality due to accidents, violence, and suicide mentioned above represent only a fraction of the health problems affecting adolescents. Severe problems among adolescents in the industrial nations are prevalent in other areas, too. The following are examples of such problems: 1. The often stated decrease in infectious diseases in childhood and adolescence essentially applies only to bacterial infections. Nevertheless, tuberculosis still belongs to the 20 most frequent causes of death (Stehr, 1981). On the other hand, in West Germany, for example, viral infections such as measles, mumps, and pertussis are on the increase (Hartung, 1982; Stehr, 1988). A main cause of this trend can probably be found in the reduction in vaccinations due to inconsistent recommendations on the part of physicians within the last 20 years. 2. In addition to these "classic" infectious diseases, the problem of AIDS among adolescents has become very serious, particularly in the United States. As in the whole problem area of AIDS, prevalence estimations for youths are controversial. They mainly have to rely on the prevalence of anti-HIV(human immunodeficiency virus)-positive persons, as the incubation time can be as long as 10 years — making the manifest disease rate an inadequate indicator. According to the most recent studies of the Center for Disease Control in ethnic minority groups from urban areas, up to 1% of the 15- to 19-year-old population is estimated to be anti-HIV-positive (Frosner, 1988, 1989). In testing about two million applicants to the US army, 1.4 per 1,000 persons prove to be infected. Very high rates are reported in applicants from areas like Washington D.C. (11.4), Puerto Rico (8.7), New York State (3.6), and New Jersey (3.3). Most data suggest a rapid spread of HIV among heterosexual black and Latin-American minority groups. This is taking place because the rate of HIV-infections among young people is rather similar for both sexes, and there probably are less changes in the sexual practices of heterosexuals than in the high-risk group of homosexuals (e.g., the AIDS-cofactor syphilis is on the rise in the last years). 3. In the case of chronic diseases, the estimates of prevalence depend to a great extent on the inclusion or exclusion of disorders of sight, hearing, and memal functioning, as well as speech, learning, and behavior disorders. Even when restricting this category to organic diseases, we must nevertheless assume a prevalence rate of approximately 7-10% (Eiser,

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1985). In addition to rare illnesses such as cancer, celiac diseases, cystic fibrosis and hypothyroidism, we must include epilepsy, congenital heart defects, and diabetes mellitus, which occur at about a 0.5% level (Petermann, Noeker, & Bode, 1987, p. 21). 4. Among young people, the most frequent disease involving pathological organ changes is that of bronchial asthma, a disease that can be classified as a psychosomatic disorder. Statistical surveys estimate a prevalence rate of about 2% (von der Haardt & Hoffmann, 1985; Schüffei, Herrmann, Dahme, & Richter, 1986). Prior to puberty, the figures for males exceed those of females, whereas later the figures approximate each other. In addition to asthma, the most prevalent psychosomatic disorders involving organ change are peptic ulcer and neurodermatitis, whereby international statistical surveys report substantial figures of approximately 0.5 to 3.6% and 0.7 to 2.4% respectively for these two disorders (Steinhausen, 1989). In recent times, a specific problem has arisen in the form of appetite disorders. International figures are available for obesity, anorexia nervosa, and bulimia — disorders that are highly prevalent in childhood and adolescence. In the case of anorexia nervosa, in which more than 90% of the cases diagnosed are female, the prevalence rate is judged to be between 0.7 and 1.0% (Köhle & Simons, 1986; Eggers & Esch, 1988). The figures for bulimia are similar, whereby the DSM-III diagnostic criteria for this disorder are more strict. Temporary, probably not pathological bouts of bulimia are reported by 10-20% of female adolescents (Lösel, Bliesener, & Köferl, 1990; Schwartz, Thompson, & Johnson, 1985). 5. In respect to substance addiction, an ascending problem development can be registered among adolescents. As US studies show, alcohol use rose during the late 1970s. The large majority of high school seniors (two-thirds of the females and more than three-quarters of the males) reported some use during the month prior to questioning. The most serious drinking problem among adolescents is reflected in a different item: When asked how often they had taken five or more drinks in a row during the prior 2 weeks, 52% of the males and 31% of the females reported doing so on at least one occasion (Bachman, Johnston, & O'Malley, 1981, p. 60). Tobacco consumption is also widespread among adolescents (Engel & Hurrelmann, 1989). At the end of the second decade of life, the figures approximate those of the total adult population. According to relevant surveys, the average ages at which boys and girls in the USA begin to smoke is 9.7 and 12.2 years respectively. Cigarette use among high school seniors appears to have reached a peak in 1976 and 1977 and is now on a downward trend, at least for men. In the USA, the proportion of females who smoke now

Basic Issues and Problems of Health in Adolescence

7

exceeds the proportion of males. In most countries, the gender-specific differences in the distribution of smoking at the age of adolescence or adulthood have leveled out over the past years. 6. The use of illegal drugs also begins during adolescence. In the USA, marijuana use showed a dramatic rise during the 1960s and early 1970s. The data indicate that since 1979 there has been no further increase. Obviously, marijuana use has peaked for this age cohort. In contrast, there has been a slight upward trend in the overall proportion of adolescents involved in other illicit drug use in the late 1970s. From 1975 onward, just over one quarter of males and females reported any use of some illicit drug other than marijuana during the prior year. The most dramatic shift in popularity involves cocaine (Bachman, Johnston, & O'Malley, 1981, p. 61). In West Germany, 12% of all 14- to 17-year-old adolescents reported having experimented with illegal drugs in 1972 — in most cases, with marijuana. By 1982, this proportion had decreased to 5%. The proportions for the 18- to 20-year-olds were 12% and for the 21- to 24-year-olds 16% (Engel & Hurrelmann, 1989). 7. In addition, among adolescents, substantial figures can be seen in respect to the (legal) consumption of medical (prescription and nonprescription) drugs. This behavior, which receives little public attention, is alarming, particularly because it reflects patterns of problem solving that play an important role in adult life. Many studies point to a widespread use of psychotropic and analgesic drugs within recent years. According to West German figures, the one-year prevalence rates of the consumption of substances for the group of 15- to 17-year-old adolescents are 50% for analgesics, 9% for stimulants, and 11% for tranquilizers and sedatives (Nordlohne & Hurrelmann, in this volume). As recent research demonstrates, we have a trend toward a "medicalization" of deviant and problem behavior. Drugs are taken in order to suppress psychological problem behavior: During childhood and adolescence, parents and doctors overreact to social and psychological problem behavior (learning deficits, hyperactivity, aggressiveness, retardation) by resorting to the use of pharmacological substances. During adulthood, many persons attempt to suppress their disorders with drugs and thus impede their capacities for achievement and enjoyment. 8. Concerning psychological disorders, such as psychosis, emotional disorders, conduct disorders, and learning and performance deficits, prevalence rates of about one third of all children/adolescents are reported. However, such high figures are present only when individual symptoms are measured or when period prevalence is used in place of point prevalence. The majority

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K. Hurrelmaan and F. Lose1

of studies on the prevalence of psychological disorders among adolescents report estimates of 20% or less (Castell, Biener, & Artner, 1980; Rutter & Sandberg, 1987), whereby about 5% of all cases are in urgent need of treatment (Remschmidt & Walter, 1989). In most areas there remains a great deal of uncertainty in respect to the prevalence of health hazards in adolescence. Because they do not only consist of clearly defined symptoms or syndromes of disease, epidemiological questions are even more difficult to answer than is the case when dealing with distinct organic disorders. Data on the prevalence of particular health problems, respective regional distributions, and corresponding increases and decreases depend, among other things, on the following: 1. how representative the study samples are; 2. how the respective case definitions are set up (e.g., symptom lists, clinical diagnoses, empirically derived dimensions of health); 3. the extent to which unified diagnostic classification systems are used (ICD 9-CM, DSM-III-R, ICD-based multiaxial classification scheme); 4. diagnostic objectivity and reliability of the respective syndrome or health problem; 5. whether the research team refers only to "official" statistics and cases or to systematic assessments of undetected cases; 6. the context and persons involved in collecting responses (cf. the multisetting/multi-informant problem; Achenbach, McConaughy, & Howell, 1987); 7. the magnitude of the differences set between categories or cut-off values (e.g., when need for treatment is apparent or when alcohol use becomes alcohol abuse); 8. the extent to which the research team differentiates between various age groups, for example, between childhood and adolescence; 9. to what extent a particular problem represents a social taboo or is (temporarily) at the center of public attention; and 10. the selective refusal rates and the underlying motives for refusals. Even when we take these and other methodological problems into account, the following trends are obvious: 1. The prevalence of health problems among adolescents in the industrial nations has not decreased. On the contrary, in many areas the prevalence rates have probably increased within recent times.

Basic Issues and Problems of Health in Adolescence

9

2. A substantial proportion of the respective problems do not manifest themselves independently of each other but are to a greater or lesser degree interrelated. For example, there are consistently strong correlations between different types of substance use (e.g., smoking, drinking, drug usage), externalizing problem behavior (e.g., aggressiveness, delinquency, social deviance), and different types of health-compromising activities (e.g., precocious sexual behavior, risk-taking activities). 3. This substantial part of adolescent problem behavior can be conceptualized as a kind of syndrome that is closely related to particular psychosocial risks in attempting to cope with developmental tasks (Butler & Corner, 1984; Elliot, Huizinga, & Ageton, 1985; Engel & Hurrelmann, 1989; Irwin & Millstein, 1986; Jessor & Jessor, 1977; Jessor, 1982; Mechanic & Hansell, 1988; Siddique & D'Arcy, 1984). Of course the concept of a "problem behavior syndrome" should not be overgeneralized. Many health problems — for example, obesity, hypertension, bronchial asthma, depression — are more specific and less influenced by adolescents' behavior patterns and their respective risks. The correlations between health behaviors may decline with age, thus weakening the evidence for a syndrome (Mechanic, 1979). Each health problem has a differentiated pattern of etiology, maintenance, change, and relapse. From the perspective of behavioral science, however, the problem behavior syndrome has proven to be particularly important (Jessor, 1989). Furthermore, even problems of a more internalizing, emotional type are partially correlated with externalizing types and other aspects of the above-mentioned concept (Achenbach, 1989; Losel et al., 1990).

3. Developmental Tasks and Risk Factors In our culture, we define adolescence as a transitional phase between childhood and adulthood. We characterize adult status as the achievement of self-determination and autonomy in respect to occupation, legal rights, politics, culture, religion, the institution of the family, partnerships, and sexuality. Accordingly, adolescence is characterized by the attempt to cope with basic developmental tasks that prepare one for adult status. These include coping with changes in body experience; separating from one's parents; making contact to peers; developing personal norms and value systems; increasing intellectual competence; learning to take care of one's financies; gaining vocational skills, and so forth (Silbereisen, Eyferth, & Rudinger, 1985).

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Since today's adolescents belong to those sections of the population in which symptoms of health impairment are on the increase, this is a signal that they are having difficulties in coping with developmental tasks. Under present-day conditions, the development of personality via the coordination of the various developmental tasks and their incorporation into a personal identity proves difficult. Many adolescents are affected by a lack of social orientation that results in less structured and distinct life-stages. Typical questions are, for example: What are the relevant criteria in the transition from childhood to adolescence? Which criteria determine whether a young person is seen as an adolescent or as an adult? In view of the increasing duration of vocational training, critical changes in the structure of the family, and the widespread problems involved in attempting to enter the employment sector, it is difficult for today's adolescents to determine their social status during the transition toward adult status (Hurrelmann, 1988; Hurrelmann & Engel, 1989). During adolescence, the process of personality development is made difficult by the tendency toward pluralism and loss of tradition in respect to norms and values, the latter having become "negative trademarks" within our postmodern society. The process whereby daily experience is "de-sensualized," as well as the increasing influence of the media, result in extensive demands being made on adolescents' ability to structure and evaluate information and behavior. The dissolution of numerous traditional aspects of daily life and the complex relationships of daily existence are a strain for many adults. Such factors are clearly overtaxing the adaptive capacities of adolescents, particularly because the latter are still involved in the process of developing a personal system of orientation. Due to the dissolution of tradition and all-encompassing, obligatory role norms, today's adolescents have the opportunity to create an individual life-style. Simultanously, however, there is an increase in expectations from family and peer-group members concerning the adolescent's ability to establish such a unique and individual form of life — which, at the same time, is compatible with specific social role norms. In this respect, many adolescents feel an overwhelming pressure to achieve originality and, at the same time, experience a lack of personal identity. The task of solving the difficult and complex developmental tasks may be the "price" they have to pay for the openness and diversity of the modern life course — a potential for personality development that is without historical precedence. However, the various developmental tasks may become risk constellations, and we must make allowance for them if we are to succeed in explaining social, psychological, and physical disorders and impairments to health among adolescents.

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If health-enhancing as well as health-damaging behaviors in adolescence are viewed as being part of the process of solving developmental tasks, problem behavior should not only be regarded as "negative" or "dysfunctional." Instead, it has to be conceived as being instrumental, purposeful, and goal-directed (Jessor, 1984). Behavior such as cigarette smoking, alcohol drinking, engaging in unprotected sexual intercourse, unhealthy eating habits, risk-taking activities, and illicit drug use can fulfill important functions for a young person, even though such behavior is likely to compromise that young person's health. Being accepted by the peer group, feeling more grown-up, expressing opposition to adult authority, dealing with frustration and anxiety, and so forth, are patterns of behavior that are chosen because they provide a way of defining a specific social and self-image, or of achieving social status in specific situations. In this respect, problem behavior can be a signal of "stress;" of a biopsycho-social state of tension resulting from an overload of developmental tasks confronting adolescents daily in peer groups, family, school, and work (Coleman, 1989). Only when such stressful tasks are appropriate in terms of timing and level of difficulty will adolescents be able to master them and thus achieve improved competence and productive personality development. In such cases, the personal and environmental changes connected with development are more likely to be viewed as challenges in the sense of coping theory (Lazarus & Folkman, 1984). Problem behavior emerges in cases in which the structure and profile of the personal and social resources within the adolescent's life-setting are insufficiently developed. If the preconditions for self-efficacious and self-regulated behavior are lacking, the probability increases that problem behavior will develop that is physically and psychologically harmful or at odds with social norms (Garmezy & Rutter, 1983; Peterson & Ebata, 1987). Furthermore, there is growing evidence that an overload of uncontrollable stressors may not only lead to negative emotional states but influence the individual's health via a chronic disturbance of physiological homeostasis and an indirect impairment of the immune system (Elliot & Eisdorfer, 1982; Stein, Keller, & Schleifer, 1985). The theoretical approach presented here, which interprets health problems within the context of developmental tasks, is supported by various studies. In the Bielefeld research project, for example, we can demonstrate that psychosomatic complaints such as nervousness, headache, and lack of concentration, as well as clear-cut symptoms such as bronchial asthma and allergies, are correlated with academic difficulties in school and accompanying conflicts with parents about the future academic career. On the other hand, aggressive delinquent behavior and drug abuse are strongly associated with difficulties in the process of integration into peer groups: If adolescents are not

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successful in achieving an appropriate degree of acceptance from within the respective group, and if they suffer from a lack of popularity and recognition among their peers, a considerable insecurity in their social orientation and self-esteem results. Appearing to be at a disadvantage and not being able to keep up with the peer group's material standards serves as a decisive factor in the establishment of these types of problem behavior. In both cases, the strains and stressors on adolescents are particularly high when emotional tensions with parents exist. Those adolescents who report having conflicts with their parents in various areas of life are also those who have the highest risk of manifesting different types of problem behavior (Engel & Hurrelmann, 1989). Similar results are reported by other studies on the behavior problem syndrome. The symptoms of problem behavior correlate with various environmental and personality risk variables. The research findings indicate that there are underlying differences in adolescent's health-related values and ambitions (Jessor, 1984). At the same time, research shows that we should refrain from overgeneralizing risk constellations for problem behavior. Most health problems in adolescence result from mulifactorial causes, and the constellation of causal factors can vary from individual to individual. Therefore, reasoning in the main causal structures should always be accompanied by reflecting more differentiated, probably systemic interrelations. An example of the complexity of relevant factors and levels of impact can be found in anorexia nervosa. The cognitive-emotional attempts at coping with dramatic physical changes (especially among girls), the confrontation with the ideals of beauty conveyed by society, and the development of a "healthy" body image and self-concept represent central developmental tasks. Whether or not adolescents are able to deal with these tasks successfully can depend on a number of biological, personal, and social factors: Sociocultural factors are important framing conditions: for example, society's emphasis on being slender, which is reflected in fashion trends, the prevalence of exaggerated concepts of diet and fitness, and the demands for achievement and efficiency prevalent in the upper and middle classes, where levels of anorexia nervosa are particularly high. There is also strong evidence that anorexia nervosa is related to familial factors such as family history of psychiatric disorders or forced dieting; close, loyal, and mutually dependent relationships; family vulnerability to normal life-events; pronounced interest in food, body weight, and/or shape; excessive family involvement in the care of individual family members; as well as pronounced middle-class value systems (Bryant-Waugh, 1988). The importance of ideal body weight in Western

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societies is reflected by the fact that, for example, 40% of English schoolgirls report that they are overweight, which is much higher than the objective percentage (Davies & Furnham, 1986). Similarly, in our study in North Rhine-Westphalia, 42% of the girls reported at least occasional excessive eating (Losel et al., 1990). The importance of achievement orientation and its related stressors is shown, for example, in the fact that many anorectic girls perform well in school while at the same time experiencing school as stressful (Dally & Gomez, 1979; Slade, 1982). Premorbid personality factors form a third group of relevant influences, such as neuroticism, introversion, compulsive behavior, anxiety, perfectionism, lack of self-assertion, pronounced social conformity in childhood, and the avoidance of heterosexual contacts. Biological or medical factors related to anorexia are, for example, early obesity, premature or delayed menstruation, amenorrhoea, and disturbed functioning of the hypothalamus, whereby the latter may possibly offer an integrative, albeit partial, explanation of such effects (Bemis, 1978; Slade, 1982). However, it remains unclear whether these findings refer to a stress-induced functional disorder or to a primary defect in hypothalamic functioning.

4. Problems of Prevention How can we ensure that psychological disorders, psychosomatic complaints, drug usage, and inconsiderate aggressive and sexual behavior will be reduced or kept to a minimum low degree? Or, in other words, how can pedagogical, psychological, social, medical, legal, economic, and political measures ensure that excessive stress on social, psychological, and physical well-being will be avoided or — if unavoidable — effectively coped with? For some time now, educators and youth workers have hoped that by implementing "health education," they would be able to answer this question satisfactorily. In the meantime, findings on an informative-explanatory strategy of persuasion in respect to health behavior among adolescents have been reported (see Dusenbury & Botvin, in this volume). These findings are not necessarily discouraging; however, they explicitly show the limits of such a strategy. As we know from many other fields of social psychology, information does not necessarily change attitudes, which, in turn, are only loosely correlated with manifest behavior. Behavior is not strongly guided by cognitive knowledge regarding its negative effect on health. It is only under certain conditions that factors such as knowledge and information are able to influence behavior that is socially anchored and enmeshed with strategies of coping with daily life (Perry & Jessor, 1985).

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As has been shown, from the adolescent's point of view, it is not always appropriate to behave in a manner that is favorable to good health. Behavior that endangers health is closely tied up with routine daily life and is part of a general life-style. Therefore, behavior that from an objective point of view is damaging to health can also have a stress-reducing function in respect to other risk factors. Drug abuse, for example, is frequently a symptom of a more profound coping crisis. As a consequence, most drug-prevention programs, being based on informative and explanatory measures, prove to be inadequate in their approach, because they ignore the social functions of health-damaging behavior as well as the psychological and social significance of this behavior for the individual. For health-promoting measures to be effective, it is important that they be introduced within the context of the adolescent's familial, peer, leisure, academic, occupational, and other social relationships. Adolescent's smoking or alcoholic drinking for example, is strongly influenced by the social pressure of the peer group as well as parental tolerance (Taylor, 1986; Maes & van Veldhoven, 1989). Drug usage, for example, enables one to make an impression on the social environment to the effect that these desires appear to have been fulfilled. Drugs can only be replaced when alternative forms of satisfying such desires are made available. Since adolescents seek opportunities for communication that extend beyond the boundaries set by the institutions of socialization, they must be given the possibility of finding such opportunities. Thus, the central question of health-promoting measures is as follows: How can the adolescent's desires for independence, intensive experiences, companionship, personal relationships, self-knowledge, accomplishment, and self-confidence, (which might otherwise be motivations of health-endangering behavior) be satisfied? Health-promoting measures must attempt to support adolescents in their efforts to find an individual life-style. Adolescents assess their physical health in terms of their competence within daily life and their sense of psychological well-being (Mechanic & Hansell, 1988). For example, self-assessments of better health correlate with higher levels of competence, as measured by grades in school and participation in sports and exercise, and with greater psychological well-being, as indicated by lower levels of depressed mood. For adolescents, health is truly a social concept in the sense intended by the World Health Organization definition, and reflects competence in age-appropriate activities. If we form attitudes about ourselves by observing our own action . . . then adolescents may conclude that they are healthy in part because they are active and competent. (Mechanic & Hansell, 1988, p.371)

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As a consequence, health-promoting programs aimed at influencing problem behavior in adolescence must take account of the various facets of the social environment and the enmeshment of health factors with sociocultural and economic living conditions. Prevention and intervention can only be expected to succeed when health promotion is understood as an aid to coping with daily problems, and when the factors that play a part in the coping process are included (Hurrelmann, 1987). From this perspective we can deduce the following two strategies (Lösel et al., 1989): 1. Health can be promoted by reducing stress and strain at an individual and collective level. This in no way means that adolescents should be protected from all difficulties — for such an education would be a risk factor in its own right. Rather, one must prevent an all too massive accumulation of stressors and strains and ensure that developmental tasks are encountered at a reasonable pace and in reasonable doses, and that those living conditions that are burdensome do not overtax the adolescent's coping capacity (Coleman, 1989). 2. In addition to measures for reducing strain, approaches are expedient that increase the capacity to cope with those risks that are difficult to avoid completely. Here we refer in particular to the research into resilience, invulnerability, hardiness, and so forth. Resources for resilience include coping behavior that is oriented more toward action and less to avoidance; sufficient cognitive problem-solving abilities; a positive self-concept; a belief in one's self-efficacy; social support from parents and other reference persons; the availability of positive modeling and reinforcement behavior within the environment; advancement of autonomous problem-solving behavior and experiences of one's abilities; and a socially imparted sense of meaningfulness of various aspects of life that facilitates the adolescent's attempts to construct a "positive" identity (Rutter, 1985; Werner, 1989; see also Lösel & Bliesener, in this volume). Thus, intervention of a preventive and compensatory nature must take account of the prevailing environmental conditions that lead to disorders, as well as the specific individual reactions and symptoms that are connected with the latter. In both of these areas, equal importance must be given to measures directed toward institutions, social networks, and individual behavior. The measures to improve the physical, psychological, and social well-being of adolescents should follow an integrative perspective. They have to take into account the following main areas of prevention and intervention:

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1. In terms of familial areas of activity, intervention measures must ensure the provision of an adequate degree of emotional security, economic resources, and cultural stimulation. Satisfactory parent-child relationships are a prerequisite for such a goal. Thus, preventive measures must enable the family to remain a reliable reference group during situations of crisis. The family is also the most important source of health education during childhood and adolescence; it forms basic attitudes to future health-relevant behavior. Factors in day-to-day life, such as dental care, diet, medical treatment, hygiene, vaccination, clothing, sexual education, and accident prevention lay the foundations for concepts of body consciousness, a life-style conducive to good health, and self-esteem. 2. Within the school situation, an approach is needed that is based on a comprehensive, empirically based concept incorporating academic as well as pedagogical elements. The goal of such measures must be to allow school to become a stimulating component of adolescents' daily life, while at the same time creating space for satisfying experiences and personality development. In this sense, a good school is a social situation that is challenging but not distressing. Being an institution of organized education, the school also plays a leading role in translating informative programs of health education into practice. These programs should contribute to establishing connections between health and work, environment, culture, and social structures, and they should serve to accumulate information about factors that are detrimental to health. Furthermore, stimulation in the areas of music, art, and sports plays an important role in this respect. In school, body consciousness and sensory experience can be developed and incorporated into a comprehensive concept of health promotion. 3. In regard to leisure activities, situations must be created that offer adolescents experiences and encounters that distract them from the temptations of consumerism. Herein lies a dilemma, in that adolescents have access to many social and material resources but, at the same time, lack real challenges and means of satisfying their interests and needs due to the superficial satisfaction offered by present-day mass media and a consumer-oriented society. Such fulfilment often entails a false sense of adventure and experience; there exists a lack of personal experiences enabling a young person to utilize his/her physical skills and psychological and social competence. More situations should be created in which noncommercial, nonorganized, unsupervised, and "nonpedagogical" activities can take place that enable adolescents to test their potentials and limitations, and in which they are free to "experiment" with the limits set by conventions and laws. Herein lies a great challenge to youth work and youth

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support: An attempt must be made to "artificially" recreate those spaces that have been reduced by the organization of daily life that is typical of industrial societies. In health promotion, attention must be paid to the fact that social relationships that are experienced as being supportive directly affect well-being and are prerequisites for overcoming stressful living conditions. For this reason, support in establishing and maintaining social relationships is an integral part of youth work and youth counseling. Adolescents must be given the opportunity to articulate and fulfill their own needs through self-help groups, to participate in community projects, and to live in groups with common goals. 4. In the area of employment, preventive health promotion must aim at giving the term "work" a positive connotation that suggests the possibility of creating something worthwhile, of making a contribution to society, of developing and creating products, of expressing oneself as an individual, and of translating ideas and thoughts into concrete actions. Working conditions must be formed in accordance with the psychosocial possibilities and needs of the employees. Above all, the goal of present-day youth work must be to tackle youth unemployment. Even in our so-called "leisure society," self-concept and prestige are essentially determined by an individual's occupation. By not being able to guarantee employment, society places young people in enormous difficulties, particularly after completion of vocational training or university studies. It thereby destroys the necessary amount of confidence in the future. For decades, the entry into a field of occupation has, in addition to marriage and establishing a family, been a decisive and symbolic step into adulthood. If this step cannot be taken, we deprive adolescents of the social foundations of a healthy personality development. As this discussion shows, health must be regarded as an integral part of a person's entire life-style and personality development. It must be incorporated into comprehensive concepts of support that address the problems of physical environment, hygiene, eating habits, social security, orientation toward the future, and self-concept. According to this approach, health promotion is an interdisciplinary area that includes medicine, biology, epidemiology, psychology, psychiatry, sociology, and pedagogy. As yet, no integrated system of health promotion exists that incorporates health education, health information, and health counseling; instead, these fields are often divided into numerous areas. It is conceivable that the various activities could be better integrated if, as a first step, community-based health counseling institutions, health bureaus,

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and physicians were to cooperate with family counseling services, child guidance clinics, social work in schools, adolescent counseling, drug counseling services, crisis services, and so forth, (see Fâché, in this volume). Health promotion cannot be supported and maintained solely by the health sector in the narrow sense. Rather, it demands a coordinated effort on the part of all those who hold responsibility within the fields of education and social services, in nongovernmental and self-organized associations and initiatives, in institutions responsible for community affairs, and, finally, in industry and the media. Health promotion entails more than medical and social services; it must be actively pursued at all levels of sociopolitical activity.

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Köhle, K., & Simons, C. (1986). Anorexia nervosa. In: Uexkfill, T. von (Ed.): Psychosomatische Medizin. München: Urban & Schwarzenberg. Kurz, R.B. (1985). Child health psychology. In: Stone, G.C., Weiss, S.M., Matarazzo, J.D., Miller, N.E., Rodin, J., Belar, C.D., Follick, M.J., & Singer, J.E. (Eds.): Health psychology. A discipline and a profession. Chicago: The University of Chicago Press, 285-301. Lazarus, R.S., & Folkman, S. (1984). Stress, appraisal, and coping. New York: Springer. Levi, L. (Ed.) (1971). Society, stress, and disease. The psychosocial environment and psychosomatic diseases. London: Oxford University Press. Lösel, F. (1987). Psychological crime prevention: Concepts, evaluations and perspectives. In: Hurrelmann, K., Kaufmann, F.-X., & Lösel, F. (Eds.): Social intervention: Potential and constraints. Berlin: De Gruyter, 289-313. Lösel, F., Bliesener, T., & Köferl, P. (1989). On the concept of "invulnerability": Evaluation and first results of the Bielefeld Project. In: Brambring, M., Lösel, F., & Skowronek, H. (Eds.): Children at risk. Assessment, longitudinal research, and intervention. Berlin: De Gruyter, 186-219. Lösel, F., Bliesener, T., & Köferl, P. (in press). Erlebens- und Verhaltensprobleme bei Jugendlichen: Deutsche Adaption und kulturvergleichende Überprüfung der Youth Self-Report Form der Child Behavior Checklist. Zeitschrift für Klinische Psychologie. Maes, S., & van Veldhoven, M. (1989). Gesundheitspsychologie: Chancen und Kritik. In: Jakobi, P. (Ed.): Jahrbuch der Medizinischen Psychologie, Vol. 3, Berlin: Springer, 245-263. Matarazzo, J.D., Weiss, S.M., Herd, J.A., Miller, N.E., & Weiss, S.M. (Eds.) (1984). Behavioral health: A handbook of health enhancement and disease prevention. New York: Wiley. Mechanic, D. (1979). The stability of health and illness behavior: Results from a 16-year follow up. American Journal of Public Health, 69, 1142-1145. Mechanic, D., & Hansell, S. (1988). Adolescents' competence, psychological well-being, and self-assessed physical health. Journal of Health and Social Behavior, 28, 364-374. Perry, C.L., & Jessor, R. (1985). The concept of health promotion and the prevention of adolescent drug abuse. Health Education Quarterly, 12, 169-184. Petermann, F., Noecker, M., & Bode, U. (1987). Psychologie chronischer Krankheiten im Kindes- und Jugendalter. München/Weinheim: Psychologie-Verlags-Union. Petersen, A.C., & Ebata, A. (1987). Developmental transitions and adolescent problem behavior. In Hurrelmann, K., Kaufmann, F.X., & Lösel, F. (Eds.): Social intervention: Potential and constraints. Berlin: De Gruyter, 167-184. Pickenhain, L. (1989). The range of disturbance of higher nervous functions in man understood by synergetic principles. Paper presented at the first international conference on higher nervous functions, October 12-24, 1989, Osaka, Japan. Remschmidt, H., & Walter, R. (1989). Untersuchungen zur Prävalenz psychischer Auffälligkeiten bei Schulkindern. Abschlußbericht. Marburg: Klinik für Kinder- und Jugendpsychiatrie der Philips-Universität Marburg. Rutter, M. (1985). Resilience in the face of adversity. Protective factors and resistance to psychiatric disorder. British Journal of Psychiatry, 147, 598-611. Rutter, M., & Sandberg, S. (1987). Epidemiology of child psychiatry disorder: Methodological issues and some substantive findings. In: Chess, S., & Thomas, A. (Eds.): Annual progress in child psychiatry and child development. New York: Bonner & Mazel. Schüffei, W., Herrmann, J.M., Dahme, B., & Richter, R. (1986). Asthma bronchiale. In: Uexküll, T. von (Ed.): Psychosomatische Medizin. München: Urban & Schwarzenberg, 743-760.

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Schwartz, D.M., Thompson, M.G., & Johnson, C.L. (1982). Anorexia nervosa and bulimia: The sociocultural context. International Journal of Eating Disorders, 1, 20-26. Siddique, C.M., & D'Arcy, C. (1984). Adolescence, stress, and psychological well-being. Journal of Youth and Adolescence, 13, 459-473. Silbereisen, R.K., Eyferth, K., & Rudinger, G. (Eds.) (1986). Development as action in context. Berlin: Springer. Slade, P.D. (1982). Towards a functional analysis of anorexia nervosa and bulimia nervosa. British Journal of Clinical Psychology, 21, 167-179. Stehr, K. (1981). Die Bedeutung der Tuberkulose-Schutzimpfung in der gegenwärtigen epidemiologischen Situation. Monatsschrift für Kinderkunde, 129, 62-66. Stehr, K. (1988). Die Impfsituation in der Bundesrepublik Deutschland 1987. Der Frauenarzt, 1, 75-79. Stein, M., Keller, S.E., & Schleifer, S.J. (1985). Stress and immunomodulation: The role of depression and neuroendoctrine function. Journal of Immunology, 135 , 827-833. Steinhausen, H.-Ch. (1989). Zur Klassifikation und Epidemiologie "psychosomatischer" Störungen im Kindes- und Jugendalter. Praxis der Kinderpsychologie und Kinderpsychiatrie, 38, 195-200. Taylor, S.E. (1986). Health psychology. New York: Random House. Talor, S.E. (1990). Health psychology: The science and the field. American Psychologist, 45, 40-50. Werner, E.E., & Smith, R.S. (1982). Vulnerable but invincible. New York: McGraw-Hill. Werner, E.E. (1989). Vulnerability and resiliency: A longitudinal perspective. In: Brambring, M., Lösel, F., & Skowronek, H. (Eds.): Children at risk. Assessment, longitudinal research, and intervention. Berlin: De Gruyter, 157-172. World Health Organization (1946). Constitution. Geneva: WHO.

Part I Antecedents of Adolescents' Health Behavior

2. Personality, Perceived Life Chances, and Adolescent Health Behavior Richard Jessor John E. Donovan Frances Costa Institute of Behavioral Science, University of Colorado, Boulder, USA*

Introduction Both societal and scientific concern with health among young people has grown substantially in recent years. Indeed, the World Health Organization selected "The Health of Youth" as the topic for global attention during its 1989 Technical Discussions in Geneva (Jessor, 1989). Among biomedical and social scientists, there is now considerable consensus that adolescence is something of a crucible for the shaping of health in later life. Not only are many health-related behaviors — eating and exercise patterns, sanitary practices, safety habits, and substance use — initially learned and tried out in adolescence, but many of the values, beliefs, and self-concepts that influence and regulate the occurrence of health-related behaviors are acquired or consolidated in that period as well. Perhaps the most important advance has been the recognition that behavior plays a central role in health and that much of the variation in health derives from the actions and decisions and choices that individuals make. In short, there is now considerable agreement that behaviors are critically important risk factors for disease, disability, and death. The behavioral perspective on health has been generative in several respects, especially in relation to youth. It has stimulated a large body of research on the psychosocial determinants of health behavior, determinants that reflect individual difference variation and determinants that refer to the immediate context or setting in which health behavior occurs. It has also stimulated inquiry about the organization of health-related behaviors, their interrelatedness, and the degree

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to which they covary in the maintenance of health or the etiology of disease. The behavioral perspective has also put on the scientific agenda the question of the linkage of health behaviors to other domains of adolescent life, for example, to school achievement, or to interpersonal relations, or to problem behavior. Salutary as these developments have been, they have not as yet enabled scientific understanding to "exceed its grasp" by as much as may have been hoped. The key limitations of the research thus far would seem to stem from the unsatisfactory state of theory in the field of adolescent health. Much of the research appears to be entirely atheoretical. Where theory has been engaged, it has tended to be highly proximal, invoking concepts that are directly and immediately implicative of health, such as health beliefs and intentions, social support for health behavior, or health internal-external control. Although such work clearly advances understanding of factors that influence health behavior, the proximal nature of the concepts — their immediacy, and the commonsense obviousness of their linkage to behavior — does not yield a social psychology that can capture more remote regions of the causal network. Neither do such proximal concepts make apparent the relation of health behavior to other domains of adolescent behavior. Finally, such proximal conceptual efforts are unlikely to engage systematically the role of the larger social environment, an even more distal and yet enduringly important source of influence on behavior.

1. Problem-Behavior Theory and Adolescent Health Behavior Our own efforts over the past decade have sought to explore the reach and the relevance of a particular social-psychological framework — Problem-Behavior Theory — as an account of variation in adolescent health behavior (Jessor, 1978, 1982, 1984; Costa, Jessor, & Donovan, 1989; Perry & Jessor, 1985; Donovan, Jessor, & Costa, in press). Originally formulated for a study of alcohol abuse and other social problem behaviors in a small, rural, tri-ethnic community (Jessor, Graves, Hanson, & Jessor, 1968), the theory was later revised and elaborated to guide a longitudinal study of problem behavior among cohorts of adolescents who were followed well into young adulthood (Jessor & Jessor, 1977; Jessor, Donovan, & Costa, in press). Since the general framework of Problem-Behavior Theory has been explicated in other publications (e.g., Jessor & Jessor, 1977, Chapter Two; Jessor, 1987), only a brief description is warranted here. The theory is focused upon three major systems: behavior, both conventional behavior (e.g., church attendance, school achievement) and unconventional or problem behavior (e.g., problem

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drinking, illicit drug use, delinquency, aggression, precocious sexual intercourse, risky driving); personality (including values and expectations about achievement and autonomy, beliefs about the self and the social world, and attitudes about morality and normative transgression); and the perceived environment (perceived controls, and supports, models, and approval for problem behavior). Some of the concepts in the theory are theoretically proximal to problem behavior, for example, attitudinal intolerance of deviance, or perceived models for drug use, and others are distal, for example, value on academic achievement, or perceived parental support. All of the concepts in each of the systems have an explicit directional implication for the likelihood of occurrence of problem behavior and reflect the underlying idea of proneness to problem behavior. In the logic of Problem-Behavior Theory, it is possible to speak of personality proneness, or perceived environment proneness, or, when taken together, of overall psychosocial proneness to problem behavior. At whatever level, proneness is the fundamental explanatory notion in the theory. The theory has by now been employed in a wide variety of studies — both cross-sectional and longitudinal — dealing with a wide variety of problem behaviors in a number of different societies, and it has consistently shown itself to be at least modestly useful. The key personality and perceived environmental variables have proved predictive of both cross-sectional and developmental variation and, taken together, they usually account for between 30 and 50% of the variance in behaviors such as illicit drug use or delinquency among adolescents. In addition, the research has shown that there is significant co-variation among problem behaviors, and that they tend to be positively interrelated among themselves while related negatively to conventional behaviors. As mentioned earlier, the theory has been extended in recent years to explore its relevance for adolescent health behavior. Some comment needs to be made about the warrant for extending the theory beyond the problem behavior domain for which it was originally formulated; the rationale has been elaborated in more detail elsewhere (Jessor, 1984; Donovan, Jessor, & Costa, in press). First, it was argued at the very outset of our work (Jessor et al., 1968) that a theory of deviance or problem behavior was, necessarily and simultaneously, an account of conforming behavior. To the extent that health behavior can be seen as conforming or conventional behavior, the theory ought, logically, to be relevant. Second, it is clear that there are widely shared social norms for engaging in health-enhancing behavior and for avoiding health-compromising behavior. Those norms are promulgated by the institutions of conventional society, and youth are regularly exhorted by parents, schools, and the media to comport themselves in accord with them. To the extent that failing to engage in

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health-enhancing behavior or actively engaging in health-compromising behavior represents the transgression of or departure from norms, the theory should be apposite since accounting for normative transgression is, precisely, its primary aim. Third, several of the problem behaviors that the theory is concerned with, for example, cigarette smoking or alcohol abuse, are simultaneously defined as health-compromising behaviors by researchers in the health field. The theory's demonstrated utility in accounting for such health-compromising behaviors suggests the possibility of its relevance to other, nonproblem health behaviors. Finally, the Problem-Behavior Theory research showing the interrelatedness of various problem behaviors suggests the possibility of even larger organizations of behavior within an individual's repertoire, organizations at the level of life-style that may entail linkages between problem behaviors and health behaviors. Given these various considerations as warrant, the exploration of adolescent health behavior within the framework of Problem-Behavior Theory has the potential of providing a more distal account, one that embeds health behavior in a broader network of person-environment variables, one that illuminates the relation of health behavior to other domains of adolescent behavior, and one that can articulate its linkage with the larger social environment. These are the key issues in the present report.

2. Description of the Study The research to be presented here was only recently completed, and its data are not yet fully analyzed. Nevertheless, the study will enable us to address, at least in a preliminary fashion, the three key issues noted above. Data were collected during the Spring of 1989 in six middle schools (Grades 7-8) and four high schools (Grades 9-12) in a large metropolitan school district in a Rocky Mountain state. The city's population numbers over half a million residents, and it is ethnically heterogeneous with Hispanic citizens constituting its largest minority. Schools were assigned to the study by the school district central administration so as to maximize representation of Black and Hispanic students from inner-city areas. Letters explaining the nature of the study were written to each student in each school and to the student's parents, and active signed consent was requested from both student and parent. Participation rates varied from school to school and by whether it was a middle school or a high

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school. The overall participation rate for the middle schools was 67%; for the high schools, it was 57%. Data were collected in large group sessions, usually in the library or the cafeteria, with students being released from their regular classes if they had obtained signed parental permission to participate. A 37-page "Health Behavior Questionnaire" was given to each student to fill out; average time for completion was 48 minutes at the middle school level and 42 minutes at the high school level. Upon completing the questionnaire, each student received a token payment of $5.00. The Health Behavior Questionnaire was a revised and elaborated version of questionnaires used in our previous studies. It included well-established scales assessing the major variables in the personality, perceived environment, and behavior systems of Problem-Behavior Theory. In addition, it included a variety of measures of health behavior in such areas as eating, exercise, safety, and sleep, as well as measures of health-related psychosocial orientation such as Value on Health, Health Internal Control, and Models for Health Behaviors. At the end of the questionnaire, students were asked their evaluation of it, and the great majority thought it was interesting and a worthwhile experience. In the present report, the data are based upon all those participants for whom ethnic status could be determined and who were classified as either White, Black, or Hispanic. At the middle school level, there are 258 White males, 126 Black males, and 265 Hispanic males; among the female middle school participants, 262 are White, 173 Black, and 305 Hispanic. At the high school level, there are 349 White males, 193 Black males, and 425 Hispanic males; among the female high school participants, 457 are White, 308 Black, and 583 Hispanic. Overall, there were 1,389 middle school youth and 2,315 high school youth; 1,326 were White, 800 were Black, and 1,578 were Hispanic. The three key issues to be addressed in the remainder of this report rely on the data from responses to the Health Behavior Questionnaire by the samples just described. The first issue to be examined is the relationship of the distal measures in the personality system of Problem-Behavior Theory to variation in adolescent health behavior. The second issue is the relationship of health behavior to other domains of behavior, especially problem behavior, in this adolescent population. And the third issue is the linkage of variation in adolescent health behavior to the larger social environment.

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3. Linking Personality Variation to Variation in Adolescent Health Behavior The first step in examining all three issues was to establish an overall health behavior criterion measure. Measures were selected from four separate domains of health-related behavior: exercise, healthful eating practices, adequacy of sleep, and safety. Exercise was assessed by a four-item scale asking about the number of hours a week spent in organized sports participation, in working out as part of a personal exercise program, in pickup games, or in practicing physical activities (Cronbach's alpha = .70). Healthful Eating Practices were measured by a nine-item scale asking how much attention adolescents paid to seeing that their diet is healthy, to limiting the amounts of salt or fat eaten, to eating healthy snacks like fruit, and so forth (alpha = .87). Sleep Adequacy was assessed by a two-item scale focused on usual number of hours of sleep on school nights (alpha = .78). Safety was measured by a single question regarding how much of the time a seatbelt is used when riding in a car. The four measures correlate positively and significantly among themselves, but their correlations are small, generally less than .20. The measure of Healthful Eating Practices has the strongest and most consistent associations with the other measures. A summary index of involvement in health behavior was constructed by summing T-scores on the four component behaviors; higher scores on the Health Behavior Index reflect greater involvement in positive health behavior. Some indication of the construct validity of the Health Behavior Index can be found in its relation to five different measures of proximal psychosocial orientations to health: Value on Health, Health Internal Control, Health External Control, Parental Models for Health, and Friends' Models for Health. As expected, all of the relationships were positive. Multiple correlations (Rs) of these five measures of psychosocial orientations toward health with the Health Behavior Index were all above .50 for middle school and high school males and females. The relationship of the distal personality system variables in Problem-Behavior Theory to adolescent health behavior is shown in Table 1. Bivariate correlations between three personality measures and the Health Behavior Index are presented for males and females at the middle school and high school levels. The three personality measures — all of them distal from health behavior — are: (1) Value on Independence-Value on Academic Achievement Disjunction (a discrepancy score indicating the degree to which independence is valued more highly than academic achievement); (2) Expectations for Academic Achievement (a four-item scale indicating the subjective probability of doing well in schoolwork; Cronbach's alpha = .85); and (3) Intolerant Attitude Toward

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Deviance (a 10-item scale indicating the unacceptability of engaging in nonnormative behavior; Cronbach's alpha = .90). Table 1:

Pearson Correlations Between the Distal Personality System Measures and the Health Behavior Index Middle school

High school

Personality measures

Males

Females

Males

Females

Value on Independence-Value on Achievement Disjunction

-.29*

-.26*

-.31*

-.27*

Expectations for Academic Achievement

.36*

.35*

.30*

.30*

Intolerant Attitude Toward Deviance

.28*

.37*

.25*

.25*

* p < . 05 (two-tailed test)

It is clear in Table 1 that all three personality measures relate to the Health Behavior Index in the theoretically expected direction, and significantly, for all four subsamples. The more independence is valued relative to academic achievement, the less the involvement in positive health behavior; and the higher the expectations for academic achievement and the more intolerant the attitude toward transgression, the greater the involvement in positive health behavior. Although the magnitude of the correlations is modest, the consistency across the three measures, and across the different age and gender groups, is noteworthy. The predictiveness of the personality system as a whole can be determined from the multiple correlations of the three personality measures, taken together, with the Health Behavior Index. For the middle school males and females and the high school males and females, the respective Rs are: .42, .46, .41, and .38. Multiple correlations carried out within the three ethnic groups yield results that are similar, with the single exception of the high school Black males. With respect, then, to the first issue addressed in the present study, it is apparent that there are systematic relations between personality measures that are distal from health behavior and a composite measure of health behavior itself. The relationship shown when the three personality measures are combined is not trivial; the amount of variance accounted for in the Health

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Behavior Index ranges around 15 to 20 percent for the various gender-by-grade groups, as well as for the three different ethnic groups.1 These data provide the first replication of our previous findings (Donovan, Jessor, & Costa, in press). The present data extend those earlier findings to a large urban sample and to minority ethnic groups not represented in the previous study. What the results permit is the linkage of adolescent health behavior to a larger network of individual difference variation — individual difference attributes with no immediately obvious implication for health behavior. In addition, the findings show that measures originally designed to explain variation in problem behavior are also predictive of health behavior. Such findings strengthen the inference that involvement in health behavior — just as is true of involvement in problem behavior — is normatively regulated, and that variables that account for normative adherence or transgression can add a significant increment to understanding of variation in health behavior.

4. Linking Adolescent Health Behavior and Adolescent Problem Behavior In prior work on Problem-Behavior Theory, research that was focused on the behavior system has helped to illuminate its structure and organization. A significant degree of interrelatedness among different problem behaviors, and their negative relation with conventional behaviors, has been demonstrated in a variety of studies (e.g., Jessor & Jessor, 1977). More recently, it has been shown that co-variation among problem behaviors holds in young adulthood as well as in adolescence, and that a single underlying factor can explain the obtained pattern of correlations among them (Donovan & Jessor, 1985; Donovan, Jessor, & Costa, 1988). The second key issue to be addressed in the present study is whether involvement in health behavior has any systematic relation to involvement in problem behavior. To the extent that there is, indeed, evidence for co-variation between health behavior and problem behavior, it would contribute to an understanding of the larger organization of behavior in adolescence. To examine this issue, in a rather preliminary fashion, we correlated four measures of problem behavior (delinquent-type behavior, involvement with marijuana, frequency of drunkenness, and sexual intercourse experience) with the four measures of health behavior discussed earlier (exercise, healthful eating practices, adequacy of sleep, and seatbelt use). As expected, the correlation matrix shows negative associations between each of the problem behaviors and

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each of the health behaviors; the correlations are again small, generally about .20, but almost all are statistically significant. The exercise measure is the one with the smallest correlations, almost none significant, when the analysis is carried out by gender and school level. A more general and more stable appraisal of the issue is obtained by examining the relation between the summary Health Behavior Index and a comparable composite index of the four problem behaviors constructed in the same way as was done for the four health behaviors. The relevant data are presented in Table 2 by gender and school level for the total sample as well as for the three ethnic subgroups. Table 2:

Pearson Correlations Between the Health Behavior Index and the Multiple Problem Behavior Index Total sample

Whites

Blacks

Hispanics

Middle school Males Females

-.28* -.35*

-.22* -.29*

-.23* -.34*

-.31* -.33*

High school Males Females

-.31* -.29*

-.32* -.39*

-.13 -.14*

-.35* -.27*

• p < .05 (two-tailed test)

As can be seen, there are consistent and significant correlations between involvement in health behavior and involvement in problem behavior. These correlations between the Health Behavior Index and the Multiple Problem Behavior Index are negative, as expected, and they hold for all the gender-by-school-level groups and for all of the ethnic subgroups except for the high school Black males. The data, again, serve as an independent replication of earlier findings (Donovan, Jessor, & Costa, in press) and extend them to an urban and ethnically heterogeneous population. It is of further interest to examine, for the same groups, the relation of the Health Behavior Index and of the Multiple Problem Behavior Index to a measure of another behavioral domain, namely, involvement in school achievement. This measure of a conventional behavior is indexed by self-reported Grade-Point Average. The correlations of the Health Behavior Index are, as expected, all positive and significant; they range between .16 and .32 with Grade-Point Average. The correlations of the Multiple Problem Behavior Index are, again as expected, all negative and significant; they are higher and range between .17 and .46. These findings not only add to the

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construct validity of both indexes, but they also reveal the linkage, albeit modest, of health behavior to yet another domain of behavior, school achievement. The correlations in Table 2 are small in magnitude, the common variance being, at best, no more than about 15%, but the consistency of their direction and of their statistical significance across the multiple subgroups is of major theoretical importance. They strongly suggest that health behavior is not isolated from the rest of an adolescent's behavioral repertoire. Indeed, they suggest that a full understanding of health behavior will require consideration of an adolescent's involvement in other conventional behaviors, such as school achievement, as well as in the variety of youthful problem behaviors. Further analyses of the structure of health and problem behavior in this data set, using latent-variable procedures, are currently underway (Donovan, Jessor, & Costa, in preparation).

5. Linking Adolescent Health Behavior With the Larger Social Environment The third and final issue to be addressed in this report focuses on the role that Problem-Behavior Theory can play in articulating the relationship between adolescent health behavior and the larger social environment. In its earliest formulation (Jessor, Graves, Hanson, & Jessor, 1968), the theory sought to bridge between society and the person by elaborating isomorphic conceptual structures for both. The opportunity structure, the normative structure, and the social control structure were elaborated for the social environment, and, as parallels, the perceived opportunity structure, the personal belief structure, and the personal control structure were elaborated for the person. In that early research, an important personality variable referred to the "perception of life chances in the opportunity structure." It was a variable designed to reflect, at the subjective level, Max Weber's concept about the objective position that a person occupied with respect to access to societal rewards such as status, respect, income, power, and the like (see Dahrendorf, 1979). Objective position in the opportunity structure is often indexed by proxy measures of socioeconomic status. Because of our interest, in the present study, in the relation of health behavior to poverty and disadvantage, we have again given attention to the perception-of-life-chances variable, and we have developed a new measure to assess it. Our initial findings with this measure of Perceived Life Chances enable us to explore, in a preliminary fashion, the linkage of adolescent health behavior to the larger social environment.

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The 10-item Perceived Life Chances scale is shown in Table 3. It represents a variety of future states that are widely endorsed as desirable, and it assesses the subjective likelihood of their future attainment. Taken together, the items yield a measure of an adolescent's belief about the future and about the overall likelihood that it will be benign or malignant. In Problem-Behavior Theory, the Perceived Life Chances variable is considered to be a generalized expectancy and to occupy a place in the Personal Belief Structure of the Personality System. Table 3:

The Measure of Perceived Life Chances in the Opportunity Structure

Think about how you see your future. I think the chances are: Very high

High

About fifty-fifty

Low

What are the chances that:

Very low

1. You will graduate from high school?

O

O

O

O

O

2. You will go to college?

O

o

o

o

O

o

o

O

o

O

3. You will have a job that pays well? 4. You will be able to own your own home? 5. You will have a job that you enjoy doing? 6. You will have a happy family life?

o

7. You will stay in good health most of the time?

o

8. You will be able to live wherever you want to in the country? 9. You will be respected in your community? 10. You will have good friends you can count on?

O

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R. lessor, J. E. Donovan, and F. Costa

The Perceived Life Chances scale has excellent psychometric properties. Cronbach's alpha reliability ranges between .88 and .92 for the four gender-by-school-level subgroups. The relation of the Perceived Life Chances measure to variation in the Health Behavior Index is shown in Table 4. As can be seen, there is a consistent positive relation between Perceived Life Chances and the Health Behavior Index: the greater the perception of access to future opportunity, the greater the involvement in positive health behavior.2 Though modest, the correlations are statistically significant for all of the gender-by-school-level subgroups as well as for the three ethnic groups. The magnitude of the correlations is similar to that of the other three personality measures presented earlier in Table 1, and in the total sample, the Perceived Life Chances measure accounts for between 7 and 16% of the variance in health behavior. Perceived Life Chances constitutes, then, another distal personality measure that is systematically linked to health behavior in youth. Table 4:

Pearson Correlations Between the Measure of Perceived Life Chances and the Health Behavior Index Total sample

Whites

Blacks

Hispanics

Middle school Males Females

.35* .40*

.34* .35*

.20* .41*

.43* .36*

High school Males Females

.27* .30*

.31* .32*

.32* .26*

.23* .30*

* p < .05 (two-tailed test)

In order to establish whether this new measure contributes any unique personality variance beyond that accounted for by the other three distal personality measures discussed earlier, hierarchical regression analyses were carried out in which the Perceived Life Chances measure was added to the regression after the other three personality measures had been entered. The multiple correlations for the total sample and the three ethnic subgroups are shown in Table 5. The measure of Perceived Life Chances does, indeed, add a significant increment to the multiple correlations for all but two of the subgroups, the middle school Black males and the high school Hispanic males. Although the increases in the lis are generally small, they represent a relative increase in the amount of variance accounted for of as much as 39% (e.g., for the high school Black males).

Personality and Adolescent Health Behavior Table 5:

37

Multiple Correlations (Us) of the Distal Personality System Measures and the Perceived Life Chances Measure With the Health Behavior Index Total sample

Whites

Blacks

Hispanics

.42

.37

.46

.46

.47*

.42»

.46

.54*

.46

.46

.42

.43

.50*

.49*

.48*

.47*

.41

.43

.19+

.48

.43*

.46*

.32*

.48

.38

.42

.28

.37

Middle school Males Personality measures With Perceived Life Chances added Females Personality measures With Perceived Life Chances added High school Males Personality measures With Perceived Life Chances added Females Personality measures

With Perceived Life Chances added .41* .46* .33* .40* + This multiple correlation is the only one of the 16 based on the three distal personality measures that did not reach significance at the p = .05 level * The increment in R yielded by the addition of the Perceived Life Chances measure is statistically significant at p < .05

Having established, thus far, that the distal personality measure of Perceived Life Chances is relevant to variation in adolescent health behavior, we can turn to the issue of linking adolescent health behavior to the larger social environment. Our efforts in this direction are still quite preliminary, but as initial steps they are promising and of interest. They entail examining whether the Health Behavior Index and the measure of Perceived Life Chances both vary according to position in the social system. To the extent that that is indeed the case, it may be reasonable to consider Perceived Life Chances as mediating between the larger social environment and health behavior.

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The approach to indexing location in the social system was to employ three standard measures of socioeconomic status: Father's Occupation, Father's Education, and Mother's Education. The large amount of missing data on Father's Occupation led us to develop an Index of Socioeconomic Status that was based, for each participant, on the average of whichever of the three measures was available. All of the analyses to be reported were carried out using the Index but, in addition, also using the three component measures separately. The findings are almost identical, their robustness providing greater confidence in the Index. Table 6:

Mean Scores on the Health Behavior Index and the Measure of Perceived Life Chances by Low, Medium, and High Socioeconomic Status Index of Socioeconomic Status Low

Medium

High

F

Eta2

Middle school Males Females

194.7 193.0

199.5 198.5

205.0 206.5

9.3*** 18.3*»*

.031 .052

High school Males Females

196.5 195.1

199.1 199.9

204.9 204.4

10.0*** 15.6***

.021 .024

Middle school Males Females

41.0 39.8

42.0 42.8

44.5 44.1

13.6*** 27.7***

.046 .077

High school Males Females

40.4 40.7

42.5 42.0

43.2 43.9

15.3*** 27.9***

.033 .042

A. Health Behavior Index

B. Perceived Life Chances

Level of significance of F ratio: * p < .05 ** p < .01 *** p< .001

The data in Table 6 present mean scores on the Health Behavior Index by three categories of socioeconomic status, low, medium, or high, for the four gender-by-school-level subgroups. They also present a comparable appraisal of the Perceived Life Chances scale. As can be seen, both the Health Behavior

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Index and the Perceived Life Chances scale vary significantly with the measure of socioeconomic position. The higher the socioeconomic status, the greater the involvement in health behavior and the greater the perception of access to future opportunity. The findings are consistent for all four gender-by-schoollevel subgroups. Since we have already shown in Table 4 that Perceived Life Chances are linked to health behavior, the present findings suggest that the linkage between adolescent health behavior and the larger social environment may be mediated, at least in part, by the perception of life chances in the opportunity structure. In pursuit of greater conviction about the role of Perceived Life Chances as a mediator between the larger social environment and health behavior, we carried out analyses of covariance by gender and school level. In these analyses, Perceived Life Chances was controlled as a covariate while examining the relationship between the Index of Socioeconomic Status and the Index of Health Behavior. That relationship should be reduced by controlling for Perceived Life Chances if the latter is, in fact, mediating the relationship. The results of the analysis of covariance support the mediating role of Perceived Life Chances for all four gender-by-school-level groups. In all cases, the F ratio is sharply reduced, and the percentage of variance in health behavior accounted for by the measure of socioeconomic status is lowered by about half when compared to the Etas already shown in Table 6.

6. Summary and Conclusions The major aim of this report has been to enlarge understanding of adolescent health behavior by embedding it in a broader social-psychological framework. That framework, Problem-Behavior Theory, is concerned with distal as well as proximal determinants of behavior; it is concerned with the structure and organization of behavior; and it is concerned with the impact of the larger social environment on behavior. All three of those concerns were addressed in the present study. The findings show that personality measures that are distal from adolescent health behavior — values about academic achievement and autonomy, expectations for academic achievement, and attitudes about normative transgression — are all relevant to an account of its variation. The findings also show that involvement in health behavior is positively related to other conventional behavior such as school achievement, and negatively related to involvement in problem behavior. Finally, the findings suggest that the perception of access to future opportunity — another personality variable that is distal from health behavior — may mediate between a disadvantaged position in

R. Jessor, J. E. Donovan, and F. Costa

40

the larger social involvement and the lesser involvement in health behavior. Position in the opportunity structure was related to both involvement in health behavior and the perception of future life chances, and, as would be expected if it actually serves as a mediating variable, controlling for Perceived Life Chances weakens the linkage between the larger social environment and health behavior. Overall, the findings indicate that it is useful to consider adolescent health behavior as normatively regulated, as linked to other domains of behavior, and as reflecting the impact of location in society. To the extent that such knowledge enlarges our understanding of adolescent health behavior, it calls attention to the positive role that theory can play in research on social behavior among youth.

Notes *

The research reported in this paper was supported by Grant No. 88-1194William T. Grant Foundation. The data could not have been collected exceptional cooperation of the school district central administration and principals of the schools involved. The generous assistance of our colleague, Bos, in the data collection and, especially, in the analyses presented here acknowledged.

1

In this paper, we restrict our focus to the personality system and to its distal variables. A substantial increment in the account of variance in the Health Behavior Index could be achieved by engaging the distal variables in the perceived environment system as well. However, our aim in this presentation is not to try to exhaust the variance in adolescent health behavior but rather to illustrate the general point about the explanatory relevance of more remote regions of the causal network. For that purpose, reliance on the distal measures in the personality system alone is sufficient.

2

Since one of the items in the Perceived Life Chances scale. Item 7, refers directly to "good health," it could have inflated the correlations in Table 4. The correlations were run again with Item 7 deleted, and the magnitude of the difference in r is trivial, ranging from .00 to .03.

88 from the without the the building Jill Van Den is gratefully

Personality and Adolescent Health Behavior

41

References Costa, F., Jessor, R., & Donovan, J.E. (1989). Value on health and adolescent conventionality: A construct validation of a new measure in Problem-Behavior Theory. Journal of Applied Social Psychology, 19, 841-861. Dahrendorf, R. (1979). Life chances: Approaches to social and political theory. Chicago: University of Chicago Press. Donovan, J.E., & Jessor, R. (198S). Structure of problem behavior in adolescence and young adulthood. Journal of Consulting and Clinical Psychology, S3, 890-904. Donovan, J.E., Jessor, R., & Costa, F. (in preparation). Dimensions of health-related behavior in adolescence: A latent-variable approach. Donovan, J.E., Jessor, R., & Costa, F. (in press). Adolescent health behavior and conventionality-unconventionality: An extension of Problem-Behavior Theory. Health Psychology. Donovan, J.E., Jessor, R., & Costa, F. (1988). The syndrome of problem behavior in adolescence: A replication. Journal of Consulting and Clinical Psychology, 56, 762-765. Jessor, R. (1989). The health of youth: A behavioral science perspective. Proceedings, Technical Discussions on The Health of Youth. Geneva: World Health Organization. Jessor, R. (1987). Problem-Behavior Theory, psychosocial development, and adolescent problem drinking. British Journal of Addiction, 82, 435-446. Jessor, R. (1984). Adolescent development and behavioral health. In J.D. Matarazzo, S.M. Weiss, J .A. Herd, N.E. Miller, & S.M. Weiss (Eds.) Behavioral health: A handbook of health enhancement and disease prevention (pp. 69-90). New York: Wiley. Jessor, R. (1982). Critical issues in research on adolescent health promotion. In T.J. Coates, A.C. Petersen, & C.L. Perry (Eds.) Promoting adolescent health: A dialog on research and practice (pp. 447-465). New York: Academic Press. Jessor, R. (1978). Health-related behavior and adolescent development: A psychosocial perspective. In Adolescent behavior and health: A conference summary (pp. 39-43). Institute of Medicine Publication No. 78-004. Washington, D.C.: National Academy of Sciences. Jessor, R., Donovan, J.E., & Costa, F. (in press). Beyond adolescence: Problem behavior and young adult development. New York: Cambridge University Press. Jessor, R., Graves, T.D., Hanson, R.C., & Jessor, S.L. (1968). Society, personality, and deviant behavior: A study of a tri-ethnic community (pp. xi + 500). New York: Holt, Rinehart, & Winston. (Reprinted by Kreiger Publishing Company, Inc., Melbourne, Florida.) Jessor, R., & Jessor, S.L. (1977). Problem behavior and psychosocial development: A longitudinal study of youth. New York: Academic Press. Perry, C.L., & Jessor, R. (1985). The concept of health promotion and the prevention of adolescent drug abuse. Health Education Quarterly, 12, 169-184

3. Parent and Peer Effects on Adolescent Health Behavior Stephen Hansell David Mechanic Institute for Health, Health Care Policy, and Aging Research, Rutgers University, New Brunswick, USA*

Adolescence is a period of increasing independence from parents and experimentation with high risk behaviors in the company of peers. Many young people develop patterns of behavior that adversely affect health and adjustment and start them on life trajectories with adverse health consequences. Increasing efforts are being made to promote positive health behaviors (Tarlov, 1984; Lalonde, 1974; Surgeon General's Report, 1979). It is especially important to understand the determinants of positive health behavior among adolescents and to encourage such behavior before permanent health habits are firmly established.

1. Research on Health Behavior in Adolescence A growing number of studies have investigated parent and peer effects on smoking, drinking, and marijuana use among adolescents (e.g., Jessor, 1985; Kandel & Adler, 1982; Ensminger, Brown, & Kellam, 1982; Evans & Raines, 1982; Castro, Maddahian, Newcomb, & Bender, 1987). However, only a few studies have examined the determinants of other types of health behaviors such as exercise, seatbelt use, and eating habits (e.g., Gottlieb & Chen, 1985; Lau, Quadrel, & Hartman, 1989). Because most studies have examined only a small subset of health behaviors, the extent to which the same determinants influence a wide variety of important health behaviors is not well understood. Although diverse health behaviors originate from a variety of social contexts and are not

44

S. Hansell and D. Mechanic

associated strongly (Steele & McBroom, 1974; Williams & Weschler, 1972; Mechanic, 1979; Hays, Stacy, & MiMatteo, 1984; Langlie, 1979), it is possible that a relatively small set of especially important social factors influence a wide range of health behaviors. Some research has attempted to examine the characteristics of individuals who exhibit a wide variety of positive or negative health behaviors more or less consistently. Belloc and Breslow (1972) found that an index of diverse but common health practices predicted morbidity and mortality among adults controlling for socioeconomic status and physical health. In a study of young adults, Mechanic and Cleary (1980) reported that the associations among a global index of health behavior, the component health behaviors, and a variety of other measures supported the hypothesis that positive health behavior was part of a complex life-style involving overall concern about health, higher levels of education, and a sense of control over illness. Young adults higher on positive health behavior also reported greater well-being and were higher on conventional social orientations. However, Mechanic and Cleary (1980) were not able to identify factors in childhood and early adolescence that predicted later positive health behavior in young adults. These studies suggest that diverse health behaviors are influenced more by general styles of adaptation that underlie daily routines, and which are socially and culturally rewarding, than by specific motivations to be healthy. Much of the behavior associated with good health probably is integrated into complex behavioral repertoires that are sustained by interlocking networks of reinforcements (Mechanic, 1990). Drug and alcohol use, eating habits, exercise, and many other health-related behaviors are embedded in cultural patterns associated with religious and moral orientations, educational levels, and the values and expectations of particular subgroups in the population. Thus, investigating health behavior is, in an important sense, an exercise in investigating broad value orientations and the specific activities associated with them. Adolescents are influenced simultaneously by two value systems, one oriented toward parents and the other oriented toward peers. Although most adolescents interact with both parents and peers regularly, adolescents vary in the extent to which they assimilate parent-oriented and peer-oriented values, which may help explain wide variations in subsequent health behavior. Parents commonly value the current health, success, and well-being of their adolescents, as well as the development of skills and competencies that

Parent and Peer Effects on Adolescent Health Behavior

45

contribute to future life chances. Parents tend to be concerned about the long-term consequences of adolescents' immediate health-related behavior and often encourage positive health behavior. Thus, our first hypothesis is that adolescents who subscribe to parental values will have more positive health behavior. In contrast, the adolescent subculture generally emphasizes enjoyment of the present without much concern for the future or the long-term consequences of behavior and places value on peer-oriented social activities. Such activities can expose adolescents to substance abuse or risk-taking behaviors. Our second hypothesis is that adolescents who accept peer values will have more negative health behavior. We did not assess value orientations directly. Instead, these orientations are represented by proxy variables in four behavioral domains that are assumed to reflect parent-oriented values to some degree and in one behavioral domain that is assumed to reflect peer-oriented values. For example, adolescents who have stronger relationships with their parents are assumed to be more likely to accept parental values. Adolescents who feel that their parents are very interested in them and care about their lives are more likely to reciprocate this personal concern. Such adolescents are more likely to have harmonious relationships with their parents based on shared, parent-oriented values. Parents and adolescents with high quality relationships are more likely to agree about the appropriateness of a wide variety of conventional actions and behaviors, including positive health behaviors. A closely-related activity that partially reflects parent-oriented values is the participation of adolescents in family life. Adolescents who regularly spend more time with their parents are expected to form stronger relationships with them. In addition, they may be more likely to take up parental values and to learn parent-oriented styles of behavior, including health behaviors. For many families, dinnertime is the most consistent opportunity to interact. In addition, eating dinner with parents requires a time commitment that may interfere with peer-oriented activities outside of the family. In most families, success in school is consistent with parental values. Unfortunately, many adolescents dislike school because it is boring and it requires a time commitment that may interfere with peer-oriented activities (Csikszentmihalyi & Larson, 1984). Although grades are awarded for many reasons, achieving good grades clearly reflects some degree of acceptance of parent-oriented values. In addition, many schools include courses in health and well-being, and conscientious students probably learn more in such courses.

46

S. Hansell and D. Mechanic

A fourth activity that is assumed to reflect parental values to some degree is attendance at religious services. For adolescents, much religious activity probably is encouraged or required by parents, who may make regular attendance at religious services a family activity. The link between religious activity and better health among adults has been noted frequently, although the process underlying this finding remains uncertain (Levin & Vanderpool, 1987; Zuckerman, Kasl, & Ostfeld, 1984). Some religions teach positive health behavior directly or prohibit certain negative health behaviors. Also, religion can provide comfort and security in times of personal distress that may reduce substance abuse and risk-taking behaviors. In sum, we assume that perceived parental interest, eating dinner with parents, school achievement, and religious attendance are adolescent behaviors and perceptions that reflect parental values, and that such activities will be associated with longitudinal improvements in a wide variety of health behaviors. In contrast, peer-oriented social activities are expected to be associated with poorer health behavior over time. Although peer relationships and social activities provide much pleasure and many valuable learning experiences, they also expose adolescents to health risks and encourage them to experiment with smoking, drinking, and marijuana use. Adolescents are less inclined than adults to consider the implications of specific acts for future health and are more likely to feel relatively invulnerable, perhaps because most adolescents have not experienced serious illnesses. Much impulsive risk-taking behavior probably occurs in the context of adolescent social activities, either as a central goal of peer group activities or as the outgrowth of initially more benign activities. Thus, we assume that adolescent participation in peer social activities reflects peer-oriented values, and that such activities are associated with longitudinal increases in negative health behavior. Some evidence suggests that the effects of parents and peers on adolescent health behaviors may interact with age (e.g., Chassin, Presson, Sherman, Montello, & McGrew, 1986). While adolescents are struggling to disengage from their parents, they are becoming more involved in the world of their peers. On the average, high school freshmen spend more time with family than with peers, while the reverse pattern is true for high school seniors (Csikszentmihalyi & Larson, 1984). Thus, the relative influences of parents on health behaviors may diminish with age, while the relative influences of peers may increase with age. Although our data include only two age cohorts, we will explore possible interaction effects involving age and various parent-oriented and peer-oriented activities.

Parent and Peer Effects on Adolescent Health Behavior

47

Our two hypotheses emphasize the potential effects on adolescent health behaviors of engagement in activities that reflect parent and peer values to some degree. However, an alternative possibility is that parents directly influence the health behavior of their adolescents (e.g., Biddle, Bank, & Marlin, 1980). Adolescents may copy the actual health behaviors of their parents (Lau et al., 1989), and direct parental encouragement may affect adolescent health behaviors. Finally, as suggested above, parental expressions of interest in the adolescent may be associated with positive health behaviors. The data reported below include limited parental reports of their own health behaviors, the degree to which parents encourage certain health behaviors in their adolescents, and how often they express interest in the adolescent. Thus, our third hypothesis is that such parental behaviors have direct effects on adolescent health behaviors. It is possible that certain parental behaviors interact with, or buffer, the effects of adolescent value orientations. For example, adolescents who subscribe more fully to parent-oriented values may be influenced to a greater degree by parental modeling, encouragement, and expressed parental interest than other adolescents. Similarly, adolescents who participate in more peer-oriented activities may be especially resistant to the positive effects of parental modeling, encouragement, and expressed parental interest. In our analysis, we explore interaction effects involving parental behaviors and measures of adolescent parent-oriented and peer-oriented activities. A number of studies have provided support for one or more of these hypotheses with regard to alcohol abuse, marijuana use, and smoking. For example, Jessor and Jessor (1977) suggested that the single most important factor underlying marijuana use is the degree of unconventionality of adolescents' behavior. Conventional behavior generally reflects parent-oriented values and includes academic achievement, religious attendance, and interest in school. Kandel and Adler (1982) have shown that peer influences tend to increase alcohol and marijuana use, while parental influences tend to inhibit such substance abuse. McAlister, Krosnick, and Milburn (1984) have documented that peer smoking increases an adolescent's own smoking behavior. Bachman, Johnston, O'Malley, and Humphrey (1988) have suggested that evenings away from home, truancy, and lack of religious commitment are life-style factors associated with substance abuse. Finally, there is some intriguing evidence that adolescents who have poor relationships with their parents are more likely to abuse alcohol (Barnes, 1984).

48

S. Hansell and D. Mechanic

Lau et al. (1989) completed one of the few longitudinal studies of young people that examined such diverse health behaviors as alcohol use, seatbelt use, exercise, and eating habits. They found that parental modeling influences on health behaviors were strongest during the freshman year in college, while modeling influences of peers were relatively stronger among college sophomores and juniors. However, there is little comparable research on diverse health behaviors among adolescents.

2. Sample, Procedures, and Measures Longitudinal data were obtained from a three-wave study of the health of adolescents and their parents. We recruited adolescents from the 7th, 9th, and 11th grades of 19 public schools in five communities in New Jersey, which serve the inner-city as well as middle-class suburbs. All adolescents who were present in health or gym classes in the fall of 1984 were asked to volunteer, and approximately 80% (3,215) agreed to participate. Permission forms were mailed at least twice to their parents with a letter describing the study. We received written permissions from 48% (1,528) of the parents, and 81% (1,235) of these adolescents subsequently completed usable questionnaires in school under the supervision of our field staff. Ninety-seven percent (1,193) of the wave one sample was re-surveyed a year later in wave two, and 91% (908) of those in the two youngest cohorts who were still in high school were resurveyed two years later in wave three. The 908 adolescents in the three-wave sample are the focus of this analysis. In addition, we interviewed one parent, usually the mother, of 88% (842) of a random sample of 957 of the adolescents who were studied in the first wave. These telephone interviews lasted an average of 45 minutes, and parents were asked about their own health as well as about the health of their adolescent. Analyses reported here using parental data were based on the 608 adolescents in the three-wave sample whose parents were interviewed in wave one. Data obtained from the adolescent surveys included seven health behaviors: alcohol abuse, marijuana use, smoking, seatbelt use, participation in team sports, other physical exercise, and eating breakfast. Two items assessed alcohol abuse. One item asked how often in the past year the adolescent drank "to the point where you felt high (gay, drowsy, slight fuzziness)", and the second item asked how often in the past year you drank "to the point where you felt shaky walking or doing things." Response categories were never, once or twice, from time to time, and often (coded 1 through 4, respectively).

Parent and Peer Effects on Adolescent Health Behavior

49

Scores on these two items were added, and a log transformation was applied to this scale to reduce skewness. Marijuana use was assessed with a single item, "Have you used marijuana (pot, grass, hash)?" Response categories were never, tried it, and sometimes use it (coded 1 through 3, respectively). A log transformation was applied to this item. Smoking was assessed with two items. The first asked whether or not the adolescent smoked cigarettes (coded 0 for no, 1 for yes). If the answer was yes, they were asked how many cigarettes a day they smoked in the past week, and responses were truncated to a maximum of 60 cigarettes per day. These two items were added, and a log transformation was applied to this score plus one. Seatbelt use was assessed with a single item, "Did you wear seat belts the last time you were in a car?" Response categories were no and yes (coded 0 and 1). Participation in sports was assessed with a single item, "How much do you play on a sports team?". Response categories were none, a little, some, and much (coded 1 through 4, respectively). Exercise (other than on a sports team) was assessed with a single item, "How much do you get other physical exercise?" Response categories were none, a little, some, and much (coded 1 through 4, respectively). Eating breakfast was assessed with a single item, "Did you eat breakfast today?" Response categories were no and yes (coded 0 and 1).

The independent variables assessed on the adolescent surveys included five measures of adolescent participation in parent-oriented and peer-oriented activities. A scale of perceived parental interest was based on eight items, which were asked about each parent or stepparent who lived with the adolescent. For example, adolescents were asked, "This past year, how much did your mother or stepmother ... please you, show you she likes you, show interest in you as a person, talk about schoolwork with you, tell you when you did something well, listen to your ideas and opinions, love you, and spend time with you when you needed her." Response categories were never, not very much, some, and a great deal, which were coded 1 through 4, respectively. Identical questions were asked about the father or stepfather. Items were added to form subscales of mother interest and father interest. For adolescents who lived with both parents, the two subscales were averaged to form an overall scale of parental interest. The appropriate subscales were used for adolescents who lived with a single parent. Having dinner with parents was assessed with a single item, "Did you eat dinner with your parents or stepparents yesterday?" Response categories were

50

S. Hansell and D. Mechanic

no and yes (coded 0 and 1). Academic achievement was measured with a single item, "What grades have you usually gotten in school?" Response categories were A through D or lower (coded 4 through 1, respectively). Religious attendance was measured by a single item, "How often do you go to church or synagogue?" Response categories were none, a little, some, and much (coded 1 through 4, respectively). Finally, a scale of peer social activities was based on three items. Adolescents were asked how often they "hang around with friends", "talk with friends on the phone", and "go to parties." Response categories for each item were none, a little, some, and much (coded 1 through 4, respectively). Scores on these three items were added to form a scale. In addition, the adolescent survey included measures of sex, grade level, race and ethnicity, and an assessment of parents' education. Finally, adolescents were asked whether or not they lived with a father or stepfather, and whether or not they lived with a mother or stepmother (both variables were coded 1 for yes and 0 for no). These measures were included in the analysis to control for demographic and social structural effects on health behaviors. The parent telephone interview included questions about four specific health behaviors. Parents were asked about their own alcohol use, smoking, participation in sports, and participation in other physical exercise. A scale of alcohol use was based on two items that asked, first, whether the parent drank alcoholic beverages (coded 0 for no). If the answer was yes, a second question asked whether they considered themselves a light, moderate, or heavy drinker (coded 1 through 3, respectively). Responses to these two questions were added to form a scale. Smoking was assessed with two questions. The first asked whether or not the parent smoked cigarettes (coded 0 for no). If the answer was yes, they were asked how many cigarettes a day they smoked on average, and responses were truncated to a maximum of 60 cigarettes per day. These two items were added, and a log transformation was applied to this score plus one. Single items asked whether or not the parent participated in sports and engaged in regular physical exercise (coded 0 for no and 1 for yes). Parents' encouragement of specific health behaviors was assessed with three items. They were asked how much discussion they had had with their adolescent about the importance of engaging in regular physical exercise and eating breakfast regularly. Response categories were not much, some, much, and very much (coded 1 through 4, respectively). Finally, parents were asked how much they actively tried to get their adolescent involved in sports. Response categories were not much, some, much, and very much (coded 1 through 4, respectively).

Parent and Peer Effects on Adolescent Health Behavior

51

Finally, expressed parental interest in the adolescent was assessed with six items. The parent was asked "We are also interested in your relationship with your child. For example, during the last 12 months, how often did you talk to your child about his/her schoolwork?" Response categories were very often, often, sometimes, rarely, or never (coded 5 through 1, respectively). Other questions asked how often the parent told the adolescent he or she had done something well, talked to the adolescent about his or her ideas and opinions, put aside special time to spend with the adolescent, and shared activities with the adolescent in and outside of the home. Items were summed to form a scale of expressed parental interest.

3.

Results

Distributions of Predictors and Health Behaviors The distribution of adolescents by grade and sex in the three-wave sample was not significandy different from the distributions in the larger sample of adolescents who volunteered or in the larger sample for whom we received parental permission. In addition, the percentages of adolescents who volunteered, and of parents who gave their permission, were not significantly associated with measures of health across school districts. However, a variety of selection biases may have been operating, and it is likely that adolescents in the three-wave sample were somewhat healthier and happier than those in the larger sample of volunteers or the total school population. The three-wave sample included students with heterogeneous racial and ethnic backgrounds and sociocultural characteristics. Table 1 displays means and standard deviations for wave one predictors and the health behaviors in all three waves. Of the 908 adolescents in all three waves, 53% were female and 47% were male, and 51% were in the 7th grade in wave one and 49% were in the 9th grade. Also, 5% of their parents had less than a high school education, 23% graduated from high school, 15% had some college, 25% graduated from college, and 32% had postgraduate training. In addition, 82% of the adolescents lived with a father or stepfather, and 94% lived with a mother or stepmother. Finally, 12% of the adolescents were black, 5% were Hispanic, 4% were Asian, and 79% were non-Hispanic whites.

52

S. Hansell and D. Mechanic

Table 1:

Descriptive Statistics of Health Behaviors and Predictors

Variable

Wave 1

Log alcohol abuse*1* Log marijuana use1* Log smoking"*" Seatbelt use Sports team Other exerciseb Eating breakfast Sex Grade level Parent education Father home Mother home Black Hispanic Asian Perceived parental interest Dinner with parents Academic grades Religious attendance Peer social activities Parent alcohol use Log parent smoking Parent sports participation Parent exercise Parent encourages sports Parent encourages exercise Parent encourages breakfast Parent expressed interest Note:

.87 .17 .12 .60 2.54 3.14 -

.47 8.00 4.48 .82 .94 .12 .05 .04 55.06 .77 3.08 2.39 9.31 .86 .85 .42 .59 2.62 2.73 2.79 24.06

(.34) (.35) (.52) (.49) (1.33) (.96) -

Wave 2

.96 .19 .20 .62 2.47

(.39) (.36) (.66) (.49) (1.30) -

-

.63

(.48)

Wave 3

1.11 .22 .41 .60 2.52 3.02 .62

(.47) (.41) (.86) (.49) (1.26) (.97) (.49)

(.50) (1.00) (1.36) (.39) (.23) (.32) (.21) (.19) (7.55) (.42) (.76) (1.11) (2.14) (.57) (1.33) (.49) (.49) (Ml) (1.09) (1.19) (3.36)

For adolescent variables, univariate n's range from 784 to 908. For parent variables, univariate n's range from 606 to 608. Pairwise deletion of missing values was used in the paired r-tests. Sex was coded 0 for females and 1 for males. Dummy variables for blacks, Hispanics, and Asians were coded 1 for the relevant category and 0 otherwise.

* Wave 1 measure significantly different from wave 2 measure, p < .05. Wave 1 measure significantly different from wave 3 measure, p < .05. c Wave 2 measure significantly different from wave 3 measure, p < .05. Paired r-tests summarized in Table 1 indicated a general decline in adolescent health behavior during the two years of longitudinal follow-up. Specifically, four of the seven health behaviors became more negative. Alcohol

abuse,

marijuana use, and smoking all increased significantly over time, and exercise

Parent and Peer Effects on Adolescent Health Behavior

53

decreased significantly. However, three health behaviors did not change significantly, including seatbelt use, sports participation, and eating breakfast.

Correlates of Health Behaviors Most of the health behaviors were relatively stable in the year between waves one and two, as indicated by their autocorrelations (alcohol abuse r = .68; marijuana use r = .60; smoking r = .64; sports participation r = .64; seatbelt use r = .42). Exercise and eating breakfast were not assessed in wave two. Most of the health behaviors also exhibited moderate stability in the two years between waves one and three, as demonstrated by their autocorrelations (alcohol abuse r = .49; marijuana use r = .44; smoking r = .51; sports participation r = .58; eating breakfast r = .44; seatbelt use r = .32; and other exercise r — .39). A selection of the zero-order associations among the variables are shown in Table 2. Cross-sectional intercorrelations among the seven health behaviors measured in wave three revealed four clusters of health behaviors representing substance use, sports and exercise, seatbelt use, and eating breakfast. Specifically, alcohol abuse, marijuana use, and smoking were moderately to highly intercorrelated (r*s range from .45 to .57), but these measures of substance use were associated only modestly with the other measures of health behaviors (r*s range from -.05 to -.19). Sports participation was correlated moderately with other exercise (r = .48), but all of the other associations among seatbelt use, sports participation, other exercise, and eating breakfast were relatively weak (r's range from .03 to .14). Taken together, these data suggested that the various dimensions of health behavior measured in this study are relatively independent, and we therefore analyzed each health behavior separately.1 The intercorrelations among the five measures of parent-oriented and peer-oriented activities based on the adolescent surveys were relatively modest. For example, the largest positive association was between parental interest and religious attendance (r = .19), and the largest negative association involved peer social activities and grades (r = -.10). These data indicated that involvements in parent-oriented and peer-oriented activities were not highly associated or mutually exclusive. We therefore used all five measures as separate predictors in the analysis.2

54 Table 2:

S. Hansell and D. Mechanic Selected Intercorrelations Among Health Behaviors and Predictors 1

1. W3 Alcohol 2. W3 Marijuana 3. W3 Smoking 4. W3 Seatbelt 5. W3 Sports 6. W3 Exercise 7. W3 Breakfast Sex Grade level Parent education Father home Mother home Black Hispanic Asian Parental interest Dinner with parents Academic grades Religious att. Peer social act. Parent alcohol Log parent smoking Parent sports Parent exercise Parent enc. sports Parent enc. exercise Parent enc. breakfast Parent exp. interest Note:

.57* .45* -.09* -.09* -.05 -.12* .03 .30* .04 .03 -.02 -.17* -.04 -.10* -.11* -.10* -.19* -.16* .23* .09* .03 .04 -.04 -.03 -.02 -.10* -.05

2

.49* -.15* -.16* -.07* -.10* .02 .21* .01 .03 -.05 -.03 -.01 -.07* -.14* -.16* -.19* -.19* .18* .04 -.02 .04 -.01 -.05 -.04 -.12* -.12*

3

-.19* -.18* -.13* -.14* -.05 .14* -.22* .00 -.04 -.05 .03 -.05 -.15* -.10* -.21* -.15* .17* .04 .15* -.06 -.04 -.01 -.02 -.05 -.10*

4

.03 .06* .12* .00 .05 .22* .06* .05 -.14* -.09* .07* .06* .11* .13* .05 -.09* .09* -.08* .10* .00 -.03 -.04 -.07 .06

5

.48* .14* .29* -.16* .18* .07* .02 .02 -.09* .00 .16* .04 .16* .11* .04 .02 .01 .12* .11* .10* .07 .03 .06

6

.09* .15* -.05 .11* .09* .06* -.02 -.10* -.02 .14* -.02 .12* .11* -.02 .04 -.01 .12* .08* .12* .06 .00 .10*

7

.15* -.03 .10* .09* .04 -.04 .00 .04 .05 .15* .13* .08* .15* -.03 -.05 -.01 .05 .00 .00 .09* .07

For adolescent variables, univariate n's range from 784 to 908. For parent variables, univariate n's range from 606 to 608. Pairwise deletion of missing values was used in the correlations. Sex was coded 0 for females and 1 for males. Dummy variables for blacks, Hispanics, and Asians were coded 1 for the relevant category and 0 otherwise. * indicates a significant correlation, p < .05.

Correlations between the health behaviors measured in wave three and the wave one predictors also are shown in Table 2. In general, the significant zero-order associations between the health behaviors and the parent-oriented and peer-oriented activities were consistent with our expectations. Perceived parental interest was associated negatively with substance use, and positively with seatbelt use and sports and exercise (r*s ranged from -.15 to .16). Dinner with parents was associated negatively with substance use, and positively with seatbelt use and eating breakfast (r's range from -.16 to .15). Academic grades

Parent and Peer Effects on Adolescent Health Behavior

55

were associated negatively with measures of substance use, and positively with sports and exercise, seatbelt use, and eating breakfast (r*s range from -.21 to .16). Church attendance was associated negatively with substance use, and positively with sports, exercise, and eating breakfast (r*s range from -.19 to .11). Finally, peer social activities were associated positively with substance use and other exercise, and negatively with seatbelt use and eating breakfast (r's range from -.14 to .23). The correlations between parental and adolescent health behaviors were generally very weak, although several specific correlations were significant. For example, parent alcohol use and adolescent alcohol abuse were associated significantly (r = .09), as were parent and adolescent smoking (r = .15), parent and adolescent sports participation (r = .12), and parent and adolescent exercise (r = .08). Several of the correlations between parental encouragement and adolescent health behaviors also were significant. Parent encouragement of adolescent sports was associated significantly with both adolescent sports (r = .10) and adolescent exercise (r = .12), although parent exercise was not associated significantly with adolescent exercise. Also, parental encouragement of eating breakfast was associated significantly with adolescent eating breakfast (r = .09). Finally, three correlations between expressed parental interest and adolescent health behaviors were significant. Adolescents whose parents expressed high interest tended to smoke less (r = -.10), use marijuana less (r = -.12), and exercise more (r = .10). Interestingly, the correlation between adolescent perceptions of parental interest and expressed parental interest was significant, but relatively modest (r = .21).

Longitudinal Effects of Parent-Oriented and Peer-Oriented Activities Our analysis strategy employed two sets of regression equations. The first two hypotheses and associated interaction effects were examined with data from the adolescent survey, which utilized all of the adolescents who were surveyed in all three waves. The third hypothesis and associated interaction effects were examined with merged data from the adolescent survey and the parent telephone interview, which were available for a subset of the adolescents in the three-wave sample.

56

S. Hansell and D. Mechanic

The results of the first set of regression analyses are shown in Table 3. Each health behavior measured in wave two was regressed on background characteristics, parent-oriented and peer-oriented activities, and the initial value of the same health behavior measured in wave one. Similarly, each health behavior measured in wave three was regressed on the same set of predictors including the wave one measure of health behavior. Thus, these regressions revealed the predictors that were associated significantly with changes in each health behavior during one- and two-year longitudinal intervals. Table 3:

Regressions of Health Behaviors on Predictors

Predictors

W1 health behavior Sex

2

W3

W2

Ale

Ale

Marij

.57» -.01

Grade level Parent education

.15*

W3

W2

W3

W2

W3

W2

W3

W3

W3

Marij Smoke Smoke Seatblt Seatblt Sports Sports Exercis Brkfst

.35*

.50*

.36*

.00

.01

.00

-.01

-.02

.17*

.16*

.10*

.05

.05

-.10*

-.19*

.63*

.45*

-.01

.07*

.02

.09*

Father home

.02

.00

.01

.04

Mother home

-.07*

-.07*

-.06*

-.10*

-.03

-.09*

Black

-.12*

-.13*

.00

-.04

.01

-.07*

Hispanic

-.04

-.02

-.01

.01

-.05*

.07*

.39* -.09* .04

.05

.52*

.34*

.11*

.13*

-.01

-.13*

-.06

.39* .04 .02

-.02

.08*

.02

.00

-.01

.02

.05

.07*

.03

.00

.04

.04

.03

.02

.04

-.04

.07*

.07*

.03

.03

-.04

-.01

-.03

.00

-.03

-.03

-.01

-.03

-.05

.15*

.59* .15*

-.03

.04

.16*

.27* -.05

Asian

-.01

-.06*

-.01

-.05

-.01

.00

.01

.04

.06*

.03

Parental interest

-.06»

-.05

-.09*

-.09*

-.09*

-.08*

.04

.01

.09*

.06*

.08*

.01 .01

Dinner with parents

-.04

-.02

-.10*

-.07*

-.02

-.04

.04

.08*

Academic grades

-.09»

-.14*

-.09*

-.12*

-.02

-.08*

.08*

.03

.05

.09*

.08*

.07*

Religious attendance

.01

-.06

.00

-.07*

-.03

-.07*

.05

.04

.02

.03

.04

.01

Peer social activities

.08*

-.06

.01

-.03

.02

-.09*

.15*

.12*

.12*

.05*

.11*

-.08*

-.01

-.02

-.08*

.07*

Adjusted R2

.50

.33

.42

.27

.46

.35

.24

.14

.44

.39

.18

.21

N

781

727

780

727

794

708

805

746

808

743

737

749

Note:

Listwise deletion of missing values was used in the regressions. Sex was coded 0 for females and 1 for males. Dummy variables for blacks, Hispanics, and Asians were coded 1 for the relevant category and 0 otherwise. Non-Hispanic whites were the reference category. Standardized betas are shown. * indicates a significant beta, p < .05.

The results provided strong overall support for the first hypothesis that parent-oriented activities are associated with more positive health behavior over time. Specifically, perceived parental interest was associated significantly with longitudinal improvements in five of the seven health behaviors during at least one of the two longitudinal intervals. Higher levels of perceived parental interest were associated with decreases in alcohol abuse, marijuana use, and

Parent and Peer Effects on Adolescent Health Behavior

57

smoking over time, and with longitudinal increases in sports and exercise. Gating dinner with parents was associated with significant improvements in three out of seven health behaviors during at least one of the longitudinal intervals. Joining a parent for dinner was associated with decreased marijuana use, increased seatbelt use, and a greater likelihood of eating breakfast. However, there was one finding inconsistent with our hypothesis. Eating dinner was associated with decreased exercise in wave three. Higher academic grades were associated with significant improvements in all seven health behaviors during at least one of the longitudinal intervals. Higher grades were associated with longitudinal decreases in alcohol abuse, marijuana use, and smoking, and with longitudinal increases in seatbelt use, sports participation, other exercise, and eating breakfast. Finally, attending religious services was associated significantly with two positive changes in health behavior. Adolescents who attended religious services more often evidenced significant decreases in marijuana use and smoking over time during one of the longitudinal intervals. Although perceived parental interest and academic grades had somewhat more significant effects on the seven health behaviors than eating dinner with parents or religious attendance, the overall consistency of the results is impressive. Out of the total of 60 effects of parent-oriented activities that were tested over oneor two-year longitudinal intervals, 32 were significant and in the expected direction. Only one effect was significant and contrary to our hypothesis. The results also provided strong support for the second hypothesis. Peer social activities were associated with significant longitudinal changes in five of the seven health behaviors during at least one of the two longitudinal intervals, and 8 of the total of 12 effects that were tested over one- or two-year intervals were significant. Without exception, peer social activities were associated with more negative health behaviors over time. Specifically, higher levels of social activities with peers were associated with increased alcohol abuse, marijuana use, and smoking over time, and with lower levels of seatbelt use and eating breakfast during at least one of the longitudinal intervals. The possibility that the relative effects of parent-oriented and peer-oriented activities vary for adolescents of different age was assessed in a series of regressions that are not presented here. In each regression, a single multiplicative interaction term was added to the equation after all of the other predictors were entered. Interactions involving age and parent-oriented and peer-oriented activities were tested separately, and separate regressions were run for each health behavior.

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S. Hansell and D. Mechanic

There was no consistent evidence that parent-oriented activities have greater effects on health behavior for younger adolescents. Five out of a possible 35 interaction terms were significant, which is above the number that would be expected by chance. However, only two of the interactions were consistent with the hypothesis. Dinner with parents was associated with a significant decrease in alcohol abuse and marijuana use for younger adolescents. In contrast, parental interest and church attendance were associated with decreased smoking and increased seatbelt use, respectively, for older adolescents. The fifth interaction was not interpretable. The possibility that peer-oriented activities have stronger effects for older adolescents received some very weak support. Two out of a possible 14 interactions were significant and in the expected direction, which is slightly above the number that would be expected by chance. For older adolescents, high social involvement with peers was associated with a significant increase in marijuana use and a significant decrease in seatbelt use. However, the general absence of consistent interaction effects suggests that the processes captured in our measures do not vary greatly for the two age cohorts included in this study.

Longitudinal Effects of Parental Behaviors The third hypothesis that parental behaviors influence adolescent health behavior directly was not supported by the results. In regression analyses that are not shown here, parental smoking measured in wave one was added to the regressions predicting longitudinal changes in adolescent smoking. Also, parental drinking, sports participation, and exercise assessed in wave one were added to the relevant longitudinal regressions. However, none of the parental health measures had any significant longitudinal effects on adolescent health behaviors. Similarly, measures of parental encouragement of sports participation, exercise, and eating breakfast were added to the relevant longitudinal regressions, but none of these variables had any significant effects on adolescent health behaviors over time. Finally, expressed parental interest was added to each of the longitudinal regressions, but it did not have any significant direct effects on adolescent health behaviors. The possibility that adolescents who subscribe more fully to parent-oriented values are influenced to a greater degree by parental modeling, encouragement, and expressed interest was not supported by the results, which are not presented here. Similarly, there was no evidence that adolescents who

Parent and Peer Effects on Adolescent Health Behavior

59

participate more in peer social activities are especially resistant to parental influences. Using the same strategy described above, a total of 48 interaction effects were tested. However, only 2 were significant, which is approximately the number that would be expected by chance.

4. Discussion Behaviors that have the potential to undermine future health are numerous and varied, and efforts to modify them, one by one, are expensive, timeconsuming, and difficult to implement. If a generic behavioral or social orientation toward health promotion could be identified, then it might be possible to design a single behavioral intervention that could contribute to many kinds of positive health behavior. This study provides some preliminary clues about the direction such an intervention might take, but also suggests reasons why an effective intervention of this kind will be very difficult to implement. The results provided strong and consistent support for the first hypothesis that positive changes in diverse health behaviors are associated with higher levels of engagement in parent-oriented activities. In all of the analyses reported, there was only a single instance in which a parent-oriented activity had a significant negative effect on health behavior. Adolescents who ate dinner with their parents more often reported a significant longitudinal decrease in exercise not involving a sports team. In retrospect, it seems plausible that eating dinner with parents reduced the time available for exercise after school hours. Although religious attendance and eating dinner with parents were associated with a number of longitudinal improvements in health behaviors, perceived parental interest and academic grades appeared to be especially important. These findings are congruent with Pratt's (1976) hypothesis about the "energized family", which is characterized in part by high levels of parental interest in their children and in their children's education. These factors may help develop feelings of self-worth that encourage preventive behaviors (cf. Mechanic, 1980). The results also provided strong and consistent support for the second hypothesis that higher levels of social activities with peers were associated with more negative health behaviors over time. There was not a single instance in which peer social activities were associated significantly with longitudinal improvements in adolescent health behaviors. Social activities confer many social and psychological benefits and provide important learning experiences

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that cannot be duplicated within the family (e.g., Hansell, 1985). However, our results suggest that such activities also may expose adolescents to influences that increase potentially destructive health behaviors. The exploration of possible interaction effects involving age differences in the relative effects of parent-oriented and peer-oriented activities did not yield any consistent pattern of results. Although the restricted age range of our three-wave sample, sampling biases, or measurement artifacts may have obscured interaction effects involving age, these results suggest that there are no strong interaction effects across diverse health behaviors among the two age cohorts studied. The third hypothesis that parental behaviors affect adolescent health behaviors directly through modeling, encouragement, or expressed interest was not supported. Our data on parental health and encouragement were limited to a subset of health behaviors, and information was collected primarily from mothers rather than fathers. Thus, it is possible that more complete data on parental health behaviors and encouragement of adolescent health behaviors would yield somewhat different results. However, the absence of such effects replicated Mechanic's (1980) earlier finding that parental modeling and encouragement are less important than adolescents' perceptions of parental interest. Setting a good health example is an important goal for parents, but these results suggest that stimulating positive health behavior in adolescents requires more than direct parental modeling and encouragement. The finding that expressed parental interest was not associated with longitudinal changes in adolescent health behavior is consistent with the modest correlation between expressed parental interest and adolescent perceptions of parental interest. The lack of correspondence between adolescent and parental perceptions of their relationship raises important questions about the effectiveness of parental behavior. Although self-reporting biases may have attenuated the true association between these variables in these data, many well-intentioned parents may lack the communication skills necessary to convey personal interest to adolescents, and they may not be aware that their efforts are unsuccessful. Thus, while these results suggest the importance of perceived parental interest for adolescent health behavior, they also suggest that the successful communication of such interest may be problematic for many parents. These results suggest that identifying specific parental behaviors that increase adolescents' perceptions of parental interest is an important topic for further research.

Parent and Peer Effects on Adolescent Health Behavior

61

The exploration of interaction effects involving parental and adolescent behaviors was an attempt to examine more differentiated effects. We reasoned, for example, that the effects of parental modeling, encouragement, and expressed interest may depend on how the parent is perceived by adolescents. However, our results indicated that adolescents who perceived higher levels of parental interest were not more likely to emulate parental behaviors in the areas of smoking, drinking, or exercise, and were not more responsive to parental encouragement or expressed parental interest. More generally, there were no consistent patterns of interaction effects involving parent and adolescent behaviors. Thus, how the adolescent views the parent does not appear to condition the effects of parental modeling, encouragement, or expressed interest. Underlying our hypotheses was the assumption that, on average, parents have conventional values that are oriented toward positive health, academic success, and adolescent well-being, while adolescents place more value on immediate gratification at the possible expense of future health. However, there is certainly considerable variation in the values held by parents and adolescents. Some parents may be relatively indifferent toward health, and some peer groups may have health-promoting values. Because we did not measure values, the effects of such variations could not be assessed. Clearly, the values of parents and peers need to be investigated directly. We assumed that participation in certain activities reflects parent-oriented and peer-oriented values, but this assumption was not tested explicitly. Perceived parental interest, eating dinner with parents, school achievement, and religious attendance are crude proxy measures for adolescent acceptance of parental values, and these four areas hardly exhaust the behavioral domains that may reflect parental values. Similarly, adolescent social activities with peers reflect diverse and complex values, many of which are irrelevant to health. The simple relationship assumed here between specific perceptions and behaviors, and underlying values, is an obvious oversimplification despite its usefulness. Our relatively crude measures of participation in activities prevented us from distinguishing parent and peer influences from certain other causal factors. For example, although most students can perform well in school if they study hard, there are some who cannot obtain high grades or other types of conventional recognition regardless of their efforts. Our simple measure of academic achievement did not allow for the possibility that differences in performance may reflect factors other than attitudes or value orientations. Thus, our measures of parent-oriented and peer-oriented activities did not reflect the full range and heterogeneity of the corresponding underlying value systems, and

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more detailed specification and measurement of health-related values, activities, and behaviors is clearly needed to illuminate adolescent health behavior further. It is premature to suggest specific health interventions based on these data, but the overall pattern of results may have implications for parenting. Instead of admonishing adolescents to be healthy, parents might be more effective by increasing their expressions of general interest in their adolescents, and by establishing a positive atmosphere in the home that contributes to shared family value orientations. Of course, the results also suggest that many parental expressions of interest are ineffective, and that the quality of expressed parental interest may be a crucial mediating variable. High quality communication between parent and adolescent not only may induce the young person to meet parental standards, but also may instill the confidence and self-esteem necessary to aspire to high academic performance and resist peer group inducements to experiment with substance use and risk-taking behaviors (cf. Botvin, 1982). These findings suggest that parental influences on adolescent positive health behavior may be largely indirect, and that they may depend primarily on the overall quality of the relationship with adolescents. In principle, techniques of teaching parents to express interest in their children more effectively can be devised, and it may be possible to design an intervention with this goal. These results also suggest why it is so difficult to change adolescent health behavior unless such behavioral changes are supported by more general values that are accepted by young people. Adolescent peer groups can adhere to any system of values, but in American culture, peer groups tend not to value a concern for health or academic achievement, and instead reward athletic achievement, success in heterosexual activities, and mastery of popular youth culture (Coleman, 1959). This problem has concerned and perplexed many analysts, who see the task of changing peer group values as a preeminent challenge. Recent efforts with adolescent peer groups have attempted to encourage positive health values and behavior directly, and to employ adolescent models to teach other youth how to resist pressure to smoke or use drugs or alcohol. It is our speculation that the success of efforts to change peer group values will depend on the strength of supporting value orientations and reinforcements in families and in the larger society (Haggerty, 1977). Taken together, the results of this study suggest that adolescent health behaviors are embedded in the activities of everyday life that reflect parent and peer value orientations, and which are largely incidental to health. The health consequences

Parent and Peer Effects on Adolescent Health Behavior

63

that derive from such activities and their surrounding situations may be more powerful than those that arise from more direct health interventions. Thus, improving health behavior may require changing deeply-held value orientations.

Notes *

This research was supported, in part, by NIMH Grant No. 39590 and by a grant from the William T. Grant Foundation. Requests for reprints should be addressed to Stephen Hansell, Institute for Health, Health Care Policy, and Aging Research, Rutgers University, 30 College Ave., New Brunswick, NJ 08903, USA.

1

In our preliminary analyses, we explored the possibility of using the seven health behaviors as observed measures of a single underlying latent variable of health behavior within each wave. However, as reflected in the correlations reported above, an exploratory factor analysis of the seven health behaviors yielded four separate factors (substance use, sports and exercise, seatbelt use, and eating breakfast). In addition, we attempted a confirmatory factor analysis in which all seven measures were forced to load on a single latent variable within each wave. However, this model would not converge to an acceptable solution. Based on this evidence, we concluded that forming an overall scale of health behavior was inappropriate and potentially misleading, and we therefore examined the predictors of each health behavior separately.

2

We also explored the possibility that the four measures assumed to reflect parental values could be used as observed measures of a single underlying latent variable, using the same analytic strategy described in footnote 1. However, the four parent-oriented activities (perceived parental interest, eating dinner with parents, school achievement, and religious attendance) were not intercorrelated highly enough and were therefore used as separate predictors in the analysis.

References Bachman, J. G., Johnston, L. D., O'Malley, P. M., & Humphrey, R. H. (1988). "Explaining the recent decline in marijuana use: Differentiating the effects of perceived risks, disapproval, and general life-style factors." Journal of Health and Social Behavior, 29, 92-112. Barnes, G. M. (1984). "Adolescent alcohol abuse and other problem behaviors: Their relationships and common parental influences." Journal of Youth and Adolescence, 13, 329-348. Belloc, N. B., & Breslow, L. (1972). "Relationship of physical health status and health practices." Preventive Medicine, 1, 409-421. Biddle, B. J., Bank, B. J., & Marlin, M. M. (1980). "Parental and peer influence on adolescents." Social Forces, 58, 1057-1079.

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Botvin, G. J. (1982). "Broadening the focus of smoking prevention strategies." In T. J. Coates, A. C. Petersen, & C. Perry (Eds.), Promoting adolescent health: A dialog on research and practice (pp. 137-148). New York: Academic Press. Castro, F. G., Maddahian, E., Newcomb, M. D., & Bentler, P. M. (1987). "A multivariate model of the determinants of cigarette smoking among adolescents." Journal of Health and Social Behavior, 28, 273-289. Chassin, L., Presson, C. C., Sherman, S. J., Montello, D., & McGrew, J. (1986). "Changes in peer and parent influence during adolescence: Longitudinal versus cross-sectional perspectives on smoking initiation." Developmental Psychology, 22, 327-334. Coleman, J. (1959). "Academic achievement and the structure of competition." Harvard Educational Review, 29, 330-351. Csikszentmihalyi, M., & Larson, L. (1984). Being adolescent: Conflict and growth in the teenage years. New York: Basic Books. Ensminger, M. E., Brown, C. H., & Kellam, S. G. (1982). "Sex differences in antecedents of substance use among adolescents." Journal of Social Issues, 38, 25-42. Evans, R. I., & Raines, B. E. (1982). "Control and prevention of smoking in adolescents: A psychosocial perspective." In T. J. Coates, A. C. Petersen, & C. Perry (Eds.), Promoting adolescent health: A dialog on research and practice (pp. 101-136). New York: Academic Press. Gottlieb, N. H., & Chen. M. S. (1985). "Sociocultural correlates of childhood sporting activities: Their implications for heart health." Social Science and Medicine, 21, 533-539. Haggerty, R. J. (1977). "Changing life styles to improve health." Preventive Medicine, 6, 276-289. Hansell, S. (1985). "Adolescent friendship networks and distress in school." Social Forces, 63, 698-715. Hays, R., Stacy, A. W., & MiMatteo, M. R. (1984). "Covariation among health-related behaviors." Addictive Behaviors, 9, 315-318. Jessor, R., & Jessor, S. L. (1977). Problem behavior and psychosocial development — A longitudinal study of youth. New York: Academic Press. Jessor, R. (1985). "Bridging etiology and prevention in drug abuse research." In C. L. Jones & R. J. Battjes (Eds.), Etiology of drug abuse: Implications for prevention (pp. 257-268) (NIDA Research Monograph No. 56). Washington, DC: U.S. Government Printing Office. Kandel, D. B., & Adler, I. (1982). "Socialization into marijuana use among French adolescents: A cross-cultural comparison with the United States." Journal of Health and Social Behavior, 23, 295-309. Lalonde, M. (1974). A new perspective on the health of Canadians: A working document. Ottawa, Canada: Government of Canada. Langlie, J. K. (1979). "Interrelationships among preventive health behaviors: A test of competing hypotheses." Public Health Reports, 94, 216-225. Lau, R. R., Quadrel, M. J., & Hartman, K. A. (1989). "Development and change of young adults' preventive health beliefs and behaviors: Influence from parents and peers." Unpublished Manuscript. Pittsburgh, PA: Carnegie Mellon University. Levin, J. S., & Vanderpool, H. Y. (1987). "Is frequent religious attendance really conducive to better health? Toward an epidemiology of religion." Social Science and Medicine, 24, 589-600. McAlister, A. L., Krosnick, J. A., & Milburn, M. A. (1984). "Causes of adolescent cigarette smoking: Tests of a structural equation model." Social Psychology Quarterly, 47, 24-36. Mechanic, D. (1980). "Education, parental interest, and health perceptions and behavior." Inquiry, 17, 331-338. Mechanic, D. (1990). "Promoting health." Society, 27, 16-27

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Mechanic, D., & Cleary, P. (1980). "Factors associated with the maintenance of positive health behavior." Preventive Medicine, 9, 805-814. Pratt, L. A. (1976). Family structure and effective health behavior: The energized family. Boston: Houghton-Mifflin. Steele, J. L., & McBroom, W. H. (1974). "Conceptual and empirical dimensions of health behavior." Journal of Health and Social Behavior, 13, 382-392. Surgeon General's Report on Health Promotion and Disease Prevention. (1979). Healthy people. Washington, D.C.: Office of the Assistant Secretary for Health and Surgeon General, DHEW Publication No. 79-55071. Tarlov, A. (1984). "President's Report." The Henry J. Kaiser Family Foundation annual report for 1984. Menlo Park, CA. Williams, A. F., & Weschler, H. (1972). "Interrelationships of preventive actions on health and other areas." Health Services Reports, 87, 969-976. Zuckerman, D., Kasl, S. V., & Ostfeld, A. M. (1984). "Psychosocial predictors of mortality among the elderly poor." American Journal of Epidemiology, 119, 410-423.

4.

Young Adults' Health and its Antecedents in Evolving Life-styles Lea Pulkkinen Department of Psychology, University of Jyväskylä, Finland

1. Introduction Young adulthood is a period of physical fitness and health in an individual's life course. In spite of this, it was expected in the present study that there would be differences in young adults' state of health, and that differences are associated with long-term life-styles and life conditions. The study was part of the Jyvaskyla Longitudinal Study of Social Development in which the development of coping styles to life-styles has been followed from the age of 8 to 26 (Pulkkinen, 1982, 1989). The concept of life-style is defined here as an organized whole of an individual's activities, thoughts, and affects. It is rather stable and unconscious. Individuals' life-styles are important determinants of health, and "health life-styles practiced outside the health care delivery system have become common both between social strata and cross-culturally" (Cockerham, Kunz, & Lueschen, 1988, p. 125). Adoption of healthy life-styles varies among people for reasons other than an individual's socioeconomic status or the country's system of health care. These findings suggest that an individual's personality and life experiences are important determinants of health-related life-styles. According to Clausen (1987, p. 339), "there is a very substantial body of research indicating that certain types of social support can enhance health," and in referring to other researchers, he states that personality is related to social support. He has found a dimension for planful competence that describes adolescents' differences in thoughtfulness, self-confidence, and responsibility. It was associated with making wise decisions and moving ahead in individuals' careers. The bottom third on the index of planful competence often experienced

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L. Pulkkinen

severely negative and traumatic life events and dissatisfaction. A component of planful competence, self-confidence, was found to be consistently related both to self-ratings and to physicians' ratings of health at every adult age level. The theoretical framework of the present longitudinal study has been a model of impulse control. The point of departure was in the analysis of children's coping behavior in situations that instigate aggression. All children do not behave aggressively. In order to explain individual differences, it was hypothesized that there were aggression-inhibitory tendencies that explain four qualitatively different ways of coping with impulses: aggressive, constructive, anxious, and submissive behavior (Pulkkinen, 1982). The first two represent active reactions to a conflict and the rest passive. The coping styles also differ in the self-control of emotions, which is weaker in aggressive and anxious behavior than in the rest. Thus, for instance, constructive behavior is characterized by active reaction and strong self-control. Children's coping styles predicted adult life-styles. For instance, aggressive behavior preceded a pleasure seeking life-style, which comprised early experiments with alcohol, heavy drinking, and smoking, whereas submissive behavior predicted abstaining from drinking and refraining from other pleasures. Contractive behavior was related to school success and career development, whereas submissive behavior predicted experiences with failure and dissatisfaction. In other words, children who manifested strong self-control in their behavior (constructive and submissive) had adult life-styles that have been found to be related to health, whereas children who manifested weak self-control had adult life-styles that included risk to health. The concept of self-control can be seen as analogous to the concept of planful competence. The study of environmental conditions and upbringing in adolescence revealed that a dimension called child-centered guidance versus adult-centered (or selfish) treatment was strongly associated with the manifestations of the strength of self-control (Pulkkinen, 1982). Child-centered guidance included features of parental behavior that supported the child's growth: trust, interest, sympathy, justice, and consistency. In contrast, adult-centered guidance was oppressive: punishing, indifferent, inconsistent, and unjust. Socioeconomic status of a family was much less important to the child's social development than the quality of upbringing. The following questions were analyzed for the purposes of the present article: 1. Are there differences in young adult's health that could be described as different patterns of health?

Young Adults' Health and its Antecedents in Evolving

Life-styles

69

2. Does an individual's health have antecedents in behavior and living conditions that allow an interpretation of the gradual development of a pattern of health? The hypothesis was that there are differences evident in young adults' health, the precursors of which can be found in behavioral patterns from childhood onward. In other words, it was expected that an individual's "health path" is formed gradually, as a part of his/her life-style, which evolves in the interaction of an individual's personal characteristics and living conditions. Developmental trajectories for weak self-control contain more frequent features of life-styles, for instance, substance use, that stress the organism until impairment of health occurs.

2. Sample and Procedure The sample was drawn from 2nd-grade pupils (elementary school) in the town of Jyvaskyla in 1968. Jyvaskyla, with about 60,000 inhabitants, is the center of the province of Central Finland and is located approximately 300 km north of Helsinki. The subjects (196 boys and 173 girls) born in 1959 were followed from the age of 8. When the subjects were 14, a follow-up study of social behavior was conducted with 189 boys and 167 girls (96 and 97% of the original sample, respectively). A sample of 77 boys and 77 girls and one parent of each student was also interviewed. At the age of 20, 68 men and 67 women were interviewed. In 1986, 85% of the men and 90% of the women of the original sample were retrieved for further study at the age of 26. 167 men and 154 women filled in a mailed questionnaire, and 148 men and 142 women were interviewed.

Procedure The principal methods at the ages of 8 and 14 were peer nomination and teacher rating on social behavior and coping with conflicts. The questions were concrete, for constructive behavior, for example, "Who tries to act reasonably even in annoying situations?"; for submissive behavior, "Who is peaceable and patient?"; for anxious behavior, "Who easily starts crying if others treat them nastily?"; for aggressive behavior, "Who may hurt another child when angry, for example, by hitting, kicking or throwing something?"; for leadership skills, "Who would be a good leader of an excursion?"; and for school adjustment,

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L. Pulkkiaen

"Who tends to disobey the teacher?" There was a total of 33 questions (see Pitkanen, 1969; Pulkkinen, 1987). In reply to each question, the students selected three names from a list of students of their own sex. Teachers assessed each student on a scale from 3 to 0, giving a score of 3 to those students in whom the characteristic in question was very prominent, and 0 to those students in whom the teacher had never observed the characteristic in question. In addition, teachers were asked to make a few more general estimates of the students' development based on the teachers' understanding of early indicators of antisocial and prosocial development, for example "Which students is the teacher concerned about because of ensuing antisocial symptoms?" and "Which students does the teacher feel will certainly find their way later on in life?" The teachers were also asked to rank the students, girls and boys separately, on the basis of their school achievements up to that point in time. The socioeconomic background of the subjects was classified into three categories (higher-middle, lower-middle, and low) based on the parents' occupations. At the age of 14, peer nomination and teacher rating were used again, but the questions (10) were more complex, based on results obtained at the earlier stage, for example, "Who tries to solve annoying situations reasonably, negotiates, conciliates, and seeks to promote fairness?" In addition, teachers were asked to make estimations of school adjustment. The subjects' final reports from the period of compulsory education were examined in school archives. Semistructured interviews with both the subjects and one parent of each concerned environmental and childrearing conditions, school attendance, and leisure activities. At the age of 20, semistructured interviews concentrated on the subjects' activities. The procedures for the earlier stages of the longitudinal study have been described in detail elsewhere (e.g., Pulkkinen, 1982, 1983). At the age of 26, all the subjects in the original sample were first mailed a questionnaire and form asking whether they could be interviewed during the following month. About 40% of the subjects returned the completed questionnaire on the first call. As a result of renewing the call and contacting the subjects personally, the return rate climbed to 90% for women and 85% for men. Eighty-two percent of the women and 75% of the men were interviewed and given two personality inventories: the Eysenck Personality Questionaire and the Zuckerman Sensation Seeking Scale. All subjects were checked for criminal records. Data about health were collected in the interview. The semistructured interview covered 12 content areas that included smoking, drinking, and health. Each subject was asked to describe his/her present state of health; what problems she

Young Adults' Health and its Antecedents in Evolving Life-styles

71

had with it; whether she used any medicine regularly; whether she had been in any accident, what kind, and when; whether she had undergone surgery and why; whether she had headaches, sleeping disorders, or other feelings of being unwell; and whether she had suffered from stress and for what reason(s).

Data Analysis To code the interview data collected at the age of 26, coding scales were constructed by looking for variation in the data and then forming scales. The same method was used for coding the interviews at ages 14 and 20 (Pulkkinen, 1982). The following variables were formed for health. The variables numbered from 1 to 8 were used in the analysis of health clusters. 1. Health estimation. The subjects' estimation of their present status of health was coded in three steps: good (1), moderate (2), and weak (3). 2. Use of medicine was coded (0 = no, 1 = yes) considering the present regular use of medicine. 3. Number of operations consisted of all operations mentioned in the interview. Dysthonic symptoms. Headaches, sleeping disorders, dizziness, and other feelings of being unwell were coded (0 = no, 1 = one, 2 = several), considering the present and past situation separately. They were combined by calculating a sum score. Psychosomatic diseases. Migraine, allergic reactions, and asthma were coded in the same way as dysthonic symptoms. 4. UNWELL was a sum score of the variables for dysthonic symptoms and psychosomatic diseases. The occurrence of illnesses at present or earlier was coded (0 = no, 1 = yes) for seven categories: diseases or injuries of the locomotor system, respiratory diseases, diseases of the internal organs or the digestive system, diseases of the sensory organs or the nervous system, heart diseases or diseases of the circulatory system, genitourinery diseases, and skin diseases. 5. ILLNESSES was a sum score of the occurence of these categories. Traffic accidents. Traffic accidents were coded (0 = no, 1 = yes) separately for car accidents and cycling accidents (including both motorcycle and bicycle), the sum of which was a variable for traffic accidents. Other accidents was formed by summing the occurrence of the categories for work accidents, sport accidents, play accidents, miscellaneous (fire, drowning, army), and violence.

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6. ACCIDENTS was a sum of traffic accidents and other accidents. Consequences. Consequences of accidents were coded in four categories: 0 = no accidents, 1 = no consequences, 2 = minor consequences, 3 = rather serious or serious consequences. Present suffering. The number of injuries that affected the present state of health was coded as follows: 0 = no, 1 = one, 2 = several. 7. INJURIES was a sum score of consequences and present suffering. Feeling of stress was coded in three categories: 0 = no, 1 = sometimes earlier, 2 = at present. Causes. The number of causes of stress varied from 0 to 4 and was coded accordingly. Sources. The sources of stress were coded by estimating what level of needs in Maslow's need hierarchy the causes mentioned by the subject represented. The occurence of each level starting from physiological needs and ending with self-actualization was coded (0 = no, 1 = yes) for each subject. 8. STRESS was a sum score of feeling of stress, causes, and sources. Three group» of variables were selected from the longitudinal data to explain differences in the state of health at the age of 26: (a) Substance use, that is, smoking cigarettes and drinking alcohol. At the age of 14, teachers were asked to express their opinions on the subjects' smoking and drinking on a scale: not as far as I know, presumably, or yes. The subjects themselves were asked in the interview whether they smoked or used alcohol, and whether they had been drunk during the last year. Smoking was coded in four categories: never, has tried but does not smoke, smokes at times, and smokes regularly. Drinking was coded in six categories: never, has tried, once a year, some times in a year, once a month, once a week. Having been drunk was coded: never, once, sometimes, often. At the age of 20, variables for smoking, drinking, and having been drunk were coded from the subjects' interviews on the same scales as at the age of 14. At the age of 26, variables for smoking and drinking were included in the mailed questionnaire. Smoking was coded: never or has tried at most; has smoked for a short period; has smoked some times in a week, smokes every day. In addition, the number of cigarettes smoked daily was coded. For drinking, the frequency of drinking different quantities on one occasion, that is, (1) a bottle of beer or a glass of wine, (2) two to four bottles of beer or half of a bottle of wine, and (3) five bottles of beer or more, one bottle of wine or half of a bottle of liquor, was asked on the scale: not at all, once in a year at most, some times in a year, once a month, once a week, several times a week. The reasons for drinking (uses alcohol as

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medicine, drinks for depression and stress, drinks with friends, drinks to celebrate something) were also asked on the same scale. On the basis of the interview, a variable for problem drinking was also formed. Problem drinking was defined according to criteria suggested by McCord (1984) based on the CAGE questionnaire (Mayfleld, McLeod, & Hall, 1974) and convictions for drunken behavior (Pulkkinen, Kallio, & Romo, 1988). It covered the whole lifetime and not just the present situation. In addition, smoking and drinking were coded for each age from the age of 10 to 26 by employing all longitudinal data available. The scale for smoking was: no, at times, regularly. For drinking, a fourth category was added to depict heavy drinking. (b) Coping styles and adjustment. From data collected at the age of 8, peer nominations on coping styles were used by calculating sum scores of nominations (in percentages) for aggressive behavior, anxious behavior, constructive behavior, and submissive behavior (see Pulkkinen, 1987). In addition, peer nominations and teacher ratings of disobedience toward the teacher, teachers' estimations of the students' development, and school achievement were considered. From data collected at the age of 14, peer nominations on coping styles (aggressive, anxious, constructive, and submissive) and teachers' conceptions of the subjects' social characteristics, coping strategies, and school adjustment, as well as the grade point average in the subjects' final reports were included in the present analysis. From data collected at the age of 20, three variables were considered. They were scales for Weak Tolerance and Control, Social Tension, and Resilience (or Construedveness) based on a Self-Control Inventory (Pulkkinen, 1982). At the age of 26, three variables were formed to describe the subjects' adjustment, length of education, career development and employment, and criminality. The length of education was coded as follows: (1) compulsory education at most; (2) compulsory education and an employment course; (3) compulsory education and a vocational school; (4) senior secondary school and secondary-level education, and (S) senior secondary school and higher education. In addition, employment history was analyzed according to Sinisalo's (1985) findings on career lines: (1) Stable employment: The subject had worked in his/her field without interruption for at least half of the 7-year period or used it for education; (2) Unstable employment: the jobs had varied and mostly not corresponded to one's own field (e.g., subsidized employment work and unemployment not exceeding one quarter of 7 years), and (3) Unemployment: unemployment covered at least one third of the 7-year period and jobs had varied. For criminality, the total number of convictions as well as the number of convictions for different reasons (alcohol- and drug-related offences, traffic violations, larceny, and violence) were considered. (c) Environmental conditions and upbringing. Scales formed according to results at the age of 14 were as follows:

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L. Pulkkineo

Supportive upbringing. The scale consisted of 10 items that loaded on the factor for child-centered guidance (Pulkkinen, 1982), that is, the parents trust the child, know his/her leisure-time company, know where the child spends his/her leisure time, absence of conflict over leisure, encouragement to attend school, no physical assault (e.g., spanking or only in childhood), sympathetic with regard to failure at school, consideration of the child's opinion, holding of daily conversations between the parents and child, and implementation of reasonable restrictions and sanctions. Each variable contributed one point to the sum score, the maximum score being 10. Cronbach's alpha was 0.82. All items were coded from the child's interview. Oppressive upbringing. The scale consisted of the 10 variables as used in "supportive upbringing," but from a different perspective: the parents are suspicious, do not know or know little about the child's leisure-time company, do not know or occasionally know where the child spends his/her leisure-time, are indifferent toward or continually complain about the child's school attendance, are inconsistent in childrearing, use physical abuse even in adolescence, are indifferent or blame the child for failure at school, do not or only occasionally consider the child's opinion, employ unjust restrictions and sanctions, and assert an authoritarian atmosphere. Cronbach's alpha was 0.79. Mother's Concerned Control. The scale consisted of five items that loaded on the factor for concerned restrictiveness, that is the mother has spoken about the choice of friends, the parents have helped with homework when the child was younger, the mother has taken the child to concerts, the child has to return home before 10 o'clock, and the mother thinks that services should be improved for children's developmental leisure-time activities. Cronbach's alpha was 0.42. The items were coded from the parent's (mainly mother's) interview. Father-cbild relationship. The scale consisted of the following five items coded from the child's interview: no shared activities with the father, the father does not attend the parents' evenings at school, the child describes the father in negative terms, the father-child relationship is conflicting, and conversation rarely takes place between father and child. Cronbach's alpha was 0.64. Indifference. The scale consisted of the following four items: the parents are indifferent to or accept the child's use of alcohol, the family members do not spend leisure-time together in joint activities (passively at most), parents have not attended the parents' meetings at school, and the parents are indifferent to the child's success at school. Cronbach's alpha was 0.29. The items were coded from the child's interview. Family structure. The scale consisted of the following four items that described the degree to which the structure of the family was intact at the age of 14: the child was born in wedlock, no divorce, no single provider, and no stepparent. A low score on the scale included cases when a parent had died, the parents had divorced, the child was born to a single mother, the child had a stepparent, or when the child was in custodial care. Cronbach's alpha was 0.94. Socioeconomic status. The scale consisted of the following seven items that described the socioeconomic status of the family (coded separately for each parent): social valuation of

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occupation, length of education, quality of housing, density of dwelling, and whether the child has his/her own desk at home. Cronbach's alpha was 0.79. Both a person-oriented approach and a variable-oriented approach were aimed at in the analysis of data. For the former, the clusters for health were formed by employing a clustering technique (WARD), and the clusters for health were compared in antecedent variables by ANOVA and the Scheffe test. For a variable-oriented approach, regression techniques available in SPSS were employed to study the predictability of health variables. Firstly, some descriptive data on young adult's state of health are given.

3. Results Young Adults' Health The health of young adults was generally good, but women estimated their health to be better than men (p = .02); 86% of the women (73% of the men) regarded it as good; 13% (23%) as moderate; and 1% (4%) as weak. No sex differences were found in the number of operations (45% of the men and women had been operated on) or in the regular use of medicine; 11% of the women and 8% of the men used medicine regularly. There were no sex differences in psychosomatic diseases (migraine, allergic rhinitis, asthma, high blood pressure) from which one-fifth of the subjects suffered, but other feelings of being unwell were more common in women (p = .04); 72% of the women and 57% of the men suffered or had suffered from dysthonic syndromes, such as headaches, stomachaches, dizziness, and sleeping problems. The most frequent category for illnesses in young men comprised diseases or injuries of the locomotor system; 37% of the men either suffered or had suffered from them. This category of diseases was significandy less frequent in women (15%). No sex differences occurred in the frequency of the other categories of diseases. About 20% of the subjects had suffered from respiratory diseases and diseases of the internal organs or the digestive system, 10% from diseases of the sensory organs or the nervous system, and 3 - 4 % from heart diseases or diseases of the circulatory system, genitourinery diseases, or skin diseases. About 35% of the subjects had not had diseases belonging to any of these categories, 55 - 60% had had one or two types, and 2% of the women and 6% of the men had had diseases of three or four types. Men had been injured in an accident more often than women (p = .000); 20% of the men (5% of the women) mentioned that accidents had affected their state

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of health rather severely or severely. All types of accidents had been more frequent in men than women; 20% of the men (8% of the women) had been in a traffic accident and 30% of the men and 5% of the women in other accidents (sport, work, play, violence). Two-thirds of both women and men had a feeling of stress for one or more reasons. A few subjects (3%) mentioned three or four causes. Men were stressed by pressure at work and financial problems, whereas women were stressed by household chores, children's day-care arrangements, rearing small children, monotony of life, or studies, in addition to pressure at work. The sources of an individual's stress were mostly at one or two levels of Maslow's need hierarchy.

Clusters for Health Cluster analyses based on eight variables distinguished six clusters for health from men and women (Tables 1 and 2). The same clusters could be identified for both sexes expect for one. The clusters were titled as follows: 1. HEALTHY (39 men, 40 women). The subjects had always been well. The means of the groups in variables that described problems with health were very low. 2. WORRIED (35 men, 13 women). The subjects had feelings of being unwell, particularly dysthonic syndromes, and feelings of stress. Men estimated their health to be good, women weak. 3. MEDICATORS (13 men, 12 women). Medicators used medicine regularly and estimated their health to be weak. Medication was mainly used for psychosomatic diseases. Medicators had feelings of stress, and male Medicators had also some injuries. Accidents had mainly occured in childhood. 4. STRESSED (24 men, 28 women). The state of health was good. Stress was mainly caused by work in both sexes. Male Stresseds had been involved in accidents and had got some injuries, but none of them affected their present health. 5. RISKY (22 men); OPERATED (31 women). Male Riskys had been in several accidents, particularly in traffic accidents, which had caused injuries that did not, however, affect their estimation of the present state of health. These men did not feel stress. Female Operateds had had surgical operations for various reasons more often than other women. At present their health was good. 6. INJURED (13 men, 18 women). Male and female Injureds had all kinds of problems with their health. They had been in accidents that also included accidents other than traffic accidents. They had illnesses and injuries of the locomotor system often as a consequence of an accident, and surgical operations. They had injuries that affected their present health, which was estimated to be weak.

Young Adults' Health and its Antecedents in Evolving Life-styles Table 1:

77

Clusters for Health Obtained by a Clustering Technique (WARD) and the Means of the Clusters in the Variables for Health; Men Clusters for men

Variables n = Clustering variables: Health estimation UNWELL ILLNESSES Regular use of medicine Number of operations ACCIDENTS INJURIES STRESS

1

2

3

4

5

6

Risk

Worr

Heal

Med

Str

Inj

P >

.19 .39 .25

* * *

> > < >
>
< > >

.36 .37 .12 .31

.24

> > > >

Social climate Cohesion Openness/Frankness Tendency for conflict Autonomy Achievement orientation Planning of leisure time Religious orientation Organization Control

*

••

Empirical direction R:D

(«tests)

> > > > > > < > < > > >
> > >

.25 .40 .37 .18

> > < > < > > <
> >

> < >

.00 .03 .09

> > > >

> > < > >

.19 .29 .06 .31 .03

?

Coplnq behavior Active problem solving Economic handling Problem avoiding/Fatalism

?
>
< > >

> < > >

.19 .13 .33 .38

>

Mean effect size rm (corrected)

Social support Frequency Netsize Satisfaction Complexity Social climate Cohesion Openness/Frankness Tendency for conflict Autonomy Achievement orientation Planning of leisure time Religious orientation Organization Control

* *

* *

*•* * * * *

* * * * *

> < >

.03 .09 .21

> > < >
>
< > >

.20 .25 .34 .44

.20

> > > >

> > > >

.03 .25 .25 .24

> > < > > >

> > < > > > > > >

.28 .20 .29 .28 .10 .24 .21 .30 .22

? >

?

Mean effect size r m (corrected) *P > > >

.13 .20 .32 .14

> > < > > > > > >

.32 .17 .36 .30 .09 .21 .31 .22 .03 .22

* *

*• *• * *

•

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Results showed that forming groups with the YSR produced similar results in Stages 3 and 4. The correlation between the two columns of effect sizes was .69. We mostly found the anticipated pattern of results in both personal and social resources. The direction of group differences only occasionally deviated from the findings using the TRF in Table 1. Many of the significances and the sizes of the r m coefficients were also very similar. However, the values of the coefficients showed that the agreements between the two tables were lower than those within the tables. The effect sizes of the corresponding columns from Tables 1 and 2 only reached correlations of .22 or .21. Because of the small sample sizes and multiple testing, one should not assign too much importance to variations in the effect sizes and in the statistical significance. The consistence of the size and direction of the effects is particularly important. Here, some differences compared to Table 1 could be seen in the temperament scales and the educational climate scales. The most marked differences were for intelligence. When we used the YSR criterion for group formation, there were no longer any significant differences in the intelligence scales. The mean effect sizes dropped from .28 to .04.

Results of Model Testing To test our theoretical assumptions on the relations between the various resilience constructs, we used the original samples from the naturalistic group diagnosis (N = 148). We applied the structural equation model LISREL VI from Joreskog and Sorbom (1986) to analyze the structure postulated in Figure 1. The constructs of the theoretical model were operationalized through sum indices of the following z-standardized subscale scores: 1. social climate: cohesion, openness/frankness, conflict (negative value), autonomy; 2. self-regulating systems: self-esteem, achievement motivation; 3. behavior construction competences: intelligence; approach orientation, and flexibility in temperament; 4. social support: netsize, satisfaction with support; 5. generalized expectancies and evaluations: self-efficacy, helplessness (negative); 6. coping style: active problem solving, economic handling (negative), problem avoiding/fatalism (negative); and 7. behavioral/emotional problems: TRF total problem score, YSR total problem score.

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To estimate the theoretically specified parameters, the matrix of the product-moment correlations of these seven index variables was analyzed with the maximum likelihood method. However, an insufficient goodness of fit of the theoretically specified model indicated some false specifications. After inspecting the modification indices and the normalized residuals (Lomax, 1982), two further parameters were allowed. First, the null restriction of the path from social climate to the coping styles was removed, and then the restriction of the path from the generalized expectations and evaluations to the behavioral and emotional disorders. This modified model is shown in Figure 2.

GFI = .975 AGFI = .923

Figure 2:

Empirical test of the microlevel model (see text for a description of construct indicators)

All estimated path coefficients had the expected sign and the majority had substantial values. All coefficients were significant (p = .05). The total explanation of variance in the structural equations was almost 39% (J?2 = .387). The goodness-of-fit statistics confirmed the modified model (Chi-square = 13.73, df = 9, p = .132; GFI = .975; AGFI = .923).

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4. Discussion The bivariate group comparisons show how important it is to also orient the diagnosis of mental health versus disorder in resilience research toward the multiple-setting, multiple-informant approach. The results using the YSR criterion only partially agree with those for the TRF criterion. In some central variables, the observed differences between resilient and deviant adolescents are nevertheless remarkably consistent. In the personal resources, it is again shown that resilience is accompanied by a greater flexibility in temperament, reduced helplessness and stronger beliefs in self-efficacy, a more positive self-image, and higher achievement motivation, as well as more active-problem-oriented and less avoidance-oriented coping tendencies. The finding that the temperament variables receive more weight in the present study than in the earlier one could well depend on the methodology (self-report variables). The domain of intelligence is particularly notable in the personal resources. While our earlier findings confirmed at least moderate intelligence as a protective factor, there are now no significant differences in intelligence between the two groups. One reason for this is probably that the aspect of achievement plays a larger role in the diagnosis of mental health and behavioral/emotional disorders by the educators or through the TRF than it does in the adolescents' own perception of problems. This interpretation is partially supported by the results of the interviews (see below). If we look at the social resources, it can be seen that a larger network of supporting persons and a satisfactory kind of support has a protective impact. The former characteristic is probably more important in the institutional situation than in the family in which single reference persons can adopt more psychosocial functions. That the frequency of social support is less significant than its quality, is not very surprising. Curvilinear effects have to be assumed in which, for example, too much help leads to too great a dependence and thereby can hinder resilience. The resilient adolescents also experience a more open, cohesive, autonomous, and less conflict-ridden educational climate than the deviant group. This protective institutional atmosphere does not have to stand in opposition to a certain degree of structuring, as is shown by the tendential relationships in the scales on organization and the planning of leisure time. Even though the consistent relationships are mostly only low to moderate, the following has to be taken into account: (1) Effect sizes of this degree can be socially more important than they would appear at first sight (Rosenthal, 1983;

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Lösel & Köferl, 1989). (2) Our data sources (educators, adolescents) are only partially confounded through the access over the naturalistic group diagnosis. (3) Dichotomized groups instead of continous variation lead to an important loss of statistical power (Cohen & Cohen, 1983; Lösel & Wittmann, 1989). (4) The subjects' framework conditions in residential institutions are more homogeneous than those in the family and to some extent identical for both resilients and deviants. (5) Our index of the risk load is rather comprehensive, so that the possibility of explaining variance through further variables is restricted. From these perspectives, it is even highly remarkable that our bivariate effect sizes average over .20. A meta-analysis of the relationship between family characteristics and behavioral/emotional disorders in childhood and adolescence, for example, produced an average coefficient of .27 (Lösel & Breuer-Kreuzer, 1990). As this impact is held quasi-constant across the risk index through our procedure, the additional explanatory power gained from the resilience variables is substantial. The results on the model of the relationships between the various resilience concepts are also satisfactory. Although the original model could not be retained, it has to be considered that we had explicated it relatively strictly with only a few paths. The finally retained model in Figure 2 has only two more paths and is a good fit according to various criteria. The total variance explained is considerable, particularly when one reconsiders that we are only dealing with high-risk cases, that is, the breadth of variation is limited. In larger samples of unselected adolescents, the risk variable "controlled" here already explains circa 15 to 20% of the variance of the YSR without taking the intervening factors into account (Lösel et al., 1990b). A core domain of the personality constructs of resilience is confirmed that agrees with findings in other contexts (cf. Block & Block, 1980; Rutter, 1985; Anthony, 1987b; Werner, 1989). Behavior construction competences such as intelligence and a flexible, approach-oriented temperament are the most likely candidates for being innate protective factors. According to our model, the availability of a cognitive and emotional repertoire for the person-environment fit leads, on the one hand, in the direction of a generally more positive self-concept and a greater achievement motivation. On the other hand, expectancies and evaluations are directly and indirectly influenced in the sense of self-efficacy. All three core concepts of resilience from personality psychology are interlinked by substantial paths. The fact that self-regulation gains a special status here (see Mischel, 1973; Lösel, 1975) is also shown in the relations to the subjective representations of social resources. Not only the perceived social support but also the openness,

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cohesiveness, and so forth of the institutional climate are effective in the model through self-regulative systems. The intervening relationship to the self-related control beliefs agrees with findings in other institutions that show that a climate that is perceived as negative is accompanied by greater externality in the perception of control (see Krampen, 1987). There is also a path from social climate to the coping styles. This suggests that the tendency to approach stressors in a more active, problem-solving way is not only influenced by the personal control beliefs but also directly encouraged by a suitable social environment. Both provide support for a perspective according to which it is less the extent of single, personal or social characteristics but their "goodness of fit" that contributes to resilience (see Thomas & Chess, 1985). The markedly direct path between the belief of self-efficacy and mental health is conspicuous in our model. On the one hand, this underlines the central position attributed to this construct in cognitive-behavioral explanations of psychological disorders (e.g., Bandura, 1977). On the other hand, methodological aspects also have to be taken into account. As we regard resilience to be a relatively stable and general balance between stressors and available resources, we have not studied the coping behavior in individual situations. Our variant of Seiffge-Krenke's (1984) instrument is therefore less differentiated and possibly "fixes" less variance than would be the case in a situation-specific analysis. Such an analysis could lead to control beliefs being reflected more directly in the "outcome" of mental health or disorder. In this context, it also has to be taken into account that we have only dealt with cross-sectional data. As in many studies on risk models, we cannot say whether our variables are causal, evoking, maintaining, or simply symptomatic. The process analysis in our path model should therefore not be interpreted as a strict test but more heuristically. When the data from our current second wave are available, we will be able to make more conclusive statements. Nevertheless, prospective longitudinal data can also be ambiguous (see Remschmidt, 1988; Rutter, 1988), so that the significance of consistent cross-sectional findings should not be underestimated (Garmezy, 1988). Some of our previous findings are at least retrospectively longitudinal and validated by different informants. Insofar, they prove to be relatively consistent, as similar factors and processes of resilience are revealed to those that previously have been observed in less stressed milieus. This also applies to the more qualitative data from our interviews that are not presented here. For example, resilients more frequently continue into further education and have better grades. They identify more closely with the situation in the residential home, and, for example, more frequently consider it to be an improvement on

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their original homes. They are more willing to take on community responsibilities in the institution, yet they also make a greater attempt to create a private sphere of activity in some domains. They have more concrete and realistic ideas about their private goals, education, and career. They are more frequently still in contact with earlier reference persons outside the family and have a more positive evaluation of these contacts. Such naturalistic data are highly compatible with the findings we have presented on protective factors and processes. We will have to wait and see how far this is an expression of a balance of resilience that also remains stable during the further, difficult transition of adolescence.

Note *

This research was carried out in the Special Research Center "Prevention and Intervention in Childhood and Adolescence" (Sonderforschungsbereich 227 "Prävention und Intervention im Kindes- und Jugendalter") at the University of Bielefeld. The program is being funded by a grant from the German Research Association (Deutsche Forschungsgemeinschaft). We thank the administration and the staff of the youth welfare institutions for supporting our investigation. We also wish to thank our collègues, Peter Köferl, Petra Kolip, and Rosy Merks for their help in many aspects of this research program.

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15.

Behavioral/Emotional Problems in Adopted Adolescents Frank C. Verhuist Herma Versluis-den Bieman Department of Child Psychiatry, Academic Hospital, Rotterdam, The Netherlands

1. Introduction Since 1970, an increasing number of children born outside the Netherlands have been adopted by Dutch parents. Transracial, international adoptions have increased to 1,000 per year, a relatively large number for a country with only 175,000 births per year. The majority of children adopted in the Netherlands in the 1970s came from countries such as Korea, Colombia, India, Indonesia, Bangladesh, Lebanon, and Austria. Many international adoptees have been subjected to negative environmental influences such as discontinuous caretaking, sensory, linguistic, and emotional deprivation, or even abuse. These factors may make these children prone to develop behavioral/emotional problems. Conclusions from existing studies investigating the adjustment of international adoptees (Kim, 1977; Kim, Hong, & Kim, 1979; Rathbun, McLaughlin, Bennett, & Garland, 1965) are limited due to small or selected samples, lack of standardized assessment of problem behavior, and lack of comparison groups. Studies concerning mainly intraracial adoptions of usually less deprived children have shown somewhat more maladjusted behavior in adopted compared to nonadopted children (Bohman & Sigvardsson, 1980; Brodzinsky et al., 1984; Lindholm & Touliatos, 1980; Seglow et al., 1972; Tizard, 1977). However, variations in sample characteristics and assessment methods make it difficult to draw firm conclusions from the existing literature, leaving us with a rather confusing picture regarding the specific risks, or protective influences, of

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adoption. Therefore, our study was aimed at describing problem behavior and competencies of internationally and transracially adopted children in detail. We investigated the prevalence of behavioral/emotional problems and competencies in a sample of 2,148 international adoptees aged 10-15 years. The study consisted of two main parts: 1. An extensive phase (Stage 1) in which behavioral/emotional problems and competencies in the adopted sample assessed with the Child Behavior Checklist (Achenbach and Edelbrock, 1983) were compared with those in a same-aged sample of 933 children from the general population. 2. An intensive phase (Stage 2) in which we obtained indepth pictures by clinical interviews of 132 fourteen-year-old adopted children and their parents who were selected from the main sample on the basis of their CBCL scores.

2. Method Population Stage 1: Main sample of adopted children. For Stage 1 of the study, all children legally adopted by nonrelatives in the Netherlands (extrafamilial adoption) and born outside the Netherlands between January 1, 1972 and December 31, 1975 were selected from the central adoption register of the Dutch Ministry of Justice in 1986. Parents of 3,519 children were requested to participate in the study. Parents who consented were sent a CBCL with instructions and a questionnaire containing questions about the history of the child, health of the child, and contacts with mental health agencies. From the original sample, 162 children had moved abroad, 39 were untraceable, and 9 had died. Of the 3,309 children whose parents were sent the questionnaire, 2,148 (64.9%) usable CBCLs were returned by mail; parents of 238 children refused to cooperate, and for 923 children no response was received. For details on nonresponders, see Verhulst, Althaus, and Versluis-den Bieman (1989a). On a 6-step scale of parental occupation (Van Westerlaak et al, 1975), with 1 = lowest occupational level, the mean SES of 4.6 (SD = 1.41) of the

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adoption sample was much higher than the midpoint of 3.5. The respondents were 44.9% mothers, 23.3% fathers, 28.5% both mother and father, and 3.3% other. The distribution across native countries was: Korea, 32.0%; Colombia, 14.6%; India, 9.5%; Indonesia, 7.9%; Bangladesh, 6.7%; Lebanon, 4.9%; Austria, 5.0%; other European countries, 4.2%; other non-European countries, 15.2%. Stage 1: General population sample. The prevalence of behavioral/emotional problems in the adoption sample was compared with that in a comparison group of children from the general population. Using municipal registers that list all residents, a random sample of children with the Dutch nationality aged 4-16 was drawn. Parents were interviewed using the CBCL. CBCLs were obtained for 2,076 children. For the present study we selected all 10- to 15-year-olds (N = 933) for comparison with the adopted children. For this subsample of 933, the response rate was 82.9%. The respondents were 86.4% mothers, 10.7% fathers, and 2.9% other. The mean SES of parents in the sample of 933 was 3.54 (SD = 1.56), which was slightly above the midpoint. The mean SES of the adopted sample was significantly higher than that of the nonadopted sample (p < .001). For details of sample description, see Verhulst et al. (1989a) and Verhulst, Akkerhuis, and Althaus (1985a). Stage 2: Intensive interview sample of 14-year-old adoptees. On the basis of the previously obtained CBCL scores, 14-year-old adopted children were selected from the main sample. From the total sample of 412 14-year-olds, we obtained indepth pictures through clinical interviews for 67 well-adjusted and 65 nonoptimally functioning children according to their CBCL scores. For details on the selection of the sample, see Verhulst et al. (1989c).

Assessment Procedures Stage 1: The CBCL. We used the CBCL to obtain standardized parents' reports of children's competencies and behavioral/emotional problems. The CBCL consists of 20 competence items and 118 items concerning behavioral/emotional problems, plus two open-ended items for adding additional problems. For a detailed description of the CBCL and the Dutch confirmatory evidence of this instrument's good reliability and validity, see Achenbach and Edelbrock, (1983) and Verhulst et al. (1985a, b).

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Stage 2: Child interview. To interview each child, we used the Child Assessment Schedule (CAS; Hodges et al., 1982). This instrument consists of two parts. The first part contains 235 items covering 12 content areas, while the second part contains 53 items based on examiner observations (see also Verhulst, Althaus & Berden, 1987; Verhulst et al., 1989c). We also obtained a global I.Q. by using the WISC-R short-form (Silverstein, 1972). Stage 2: Parent interview. To assess the parents, we used a modified version of the Graham and Rutter (1968) parent questionnaire. The questionnaire contains questions on the following areas: family composition, child's general health, behavioral/emotional problems of the child, psychological and physical problems of parents, and characteristics of parent-child relationship and marital relationship. Parents were asked for recent (past 6 months), concrete descriptions of the child's behavior. Interviews were carried out by six previously trained interviewers. Interviews with the child and parents were carried out in separate rooms at the same time. Stage 2: Teacher and self-report. Versions of the CBCL to obtain teacher (Teacher Report Form: TRF; Achenbach & Edelbrock, 1986) and self-reports (Youth Self-Report: YSR; Achenbach & Edelbrock, 1987) were completed by the teachers of 116 children and by 119 children themselves. This information was used in addition to the information from the parent and child interviews to obtain a summary diagnosis as explained below. Stage 2: Summary diagnosis. The child and parent interview, the TRF and YSR scores, and the I.Q. scores were independently reviewed by three child psychiatrists who gave a severity rating and formulated a DSM-III-R diagnosis. These were the same raters who had reviewed similar information in an earlier study, in which interrater reliability for severity ratings and for DSM-III summary diagnoses had been found to be satisfactory (Verhulst et al., 1985b). Severity ratings were scored as follows: 0 = no disorder; 1 = ambiguous or trivial disorder; 2 = slight disorder; 3 = moderate disorder; 4 = severe disorder. The ratings were based on the present functioning of the child in terms of behavior, emotions, and relationships; duration and severity of abnormalities in functioning; and impact of these abnormalities on the child's development and functioning in the family, school, and with peers. Deviant behavior resulting from mental retardation (I.Q. < 85) was not considered a psychiatric disorder. To formulate a severity rating and DSM diagnosis, we chose the rating and diagnosis agreed on by the majority of raters.

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3.

325

Results

Stage 1: Comparison of Adopted and Nonadopted Children Total problem score. CBCL total problem scores were computed by summing the 0-1-2 scores on all problem items. Comparisons of the frequency distributions of the total problem scores revealed that the scores for the adoption sample, especially for boys, included more outliers with extremely high scores. Table 1 shows the mean total problem scores in both samples for both sexes and age groups 10 to 11 and 12 to 15. We divided the samples into the age groups 10 to 11 and 12 to 15 because these corresponded with age groups employed by Achenbach and Edelbrock (1983) for the derivation of empirical syndromes that were also used in the present study. Table 1:

Mean Total Problem Scores for the Adopted and Nonadopted Samples by Sex and Age Groups 10-11 and 12-15 Boys

Age

Girls

Group

Mean

SD

(n)

Mean

SD

(D)

10-11

Adopted Nonadopted

24.1 23.3

21.5 18.2

(278) (154)

17.8 20.1

16.2 15.9

(318) (165)

12-15

Adopted Nonadopted

26.0 20.1

22.7 16.7

(758) (301)

19.7 17.9

18.9 15.7

(794) (311)

As can be seen from Table 1, adopted boys scored higher than nonadopted boys (especially the 12- to 15-year-olds). For girls the picture was different. Whereas the 12- to 15-year-old adopted girls obtained higher problem scores than nonadopted girls, the reverse was true for the 10- to 11-year-old girls. To test these differences in mean problem scores, we computed ANCOVAs in which children were divided according to three independent variables: two groups (adoption status), two sexes (boys versus girls), and six age levels (10-15). To control for possible SES effects, SES was partialled out as covariate (6-step scale with 1 = lowest occupational status). Adopted children obtained significandy (p < .001) higher problem scores than nonadopted children, although the difference in mean scores accounted for less

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than 1% of the variance. There was a significant (p < .01) two-way Adoption Status x Sex interaction ( < 1 % of variance) reflecting especially elevated scores for adopted over nonadopted boys, although the scores for adopted girls in the entire sample were also higher than scores for nonadopted girls. We also found a significant (p < .001) Adoption Status x Age interaction (