longitudinal predictors of serious substance use and delinquency

LONGITUDINAL PREDICTORS OF SERIOUS SUBSTANCE USE AND DELINQUENCY*

HELENE RASKIN WHITE ROBERT J. PANDINA

Rutgers Center of Alcohol Studies

RANDY L. LAGRANGE University of North Carolina, Wilmington

The present study tests the validity of a common-cause model in explaining both serious substance use and serious delinquent behavior among youths. Longitudinal data on 441 male and 441 female adolescents are analyzed. Youths originally tested at Time I when they were 12, IS, or 18 years old were retested three years later when they were IS , 18, or 21 years old. The results provide modest support for a common-cause model. While a number of predictor variables drawn from control theory and differential association theory are related to both behaviors, those drawn from the literature on psychological correlates of adolescent deviance tend to be more strongly related to subsequent serious substance use than to serious delinquency. The findings suggest that there is a degree of etiological independence in serious adolescent substance use and serious forms of delinquency. The implications of these results for theory development and policy implementation are discussed.

The relationship between drugs and crime is the source of continuing spec- ulation and debate. Researchers probing the links between drugs and crime for the past half century have produced an abundance of contradictory findings. These disparities have paved an erratic course for social policy. Although American drug control and crime control strategies assume that an important connection exists between drug use and crime (Watters, Reinarman, and Fagan, 1985), the precise nature of the relationship between drugs and crimes remains elusive. About the only area of agreement is that substance use and crime are somehow linked (Gropper, 1984).

Watters et al.’s (1985) review of the research literature on serious substance use and serious forms of adolescent delinquency identifies three different perspectives of the drug-crime connection, each of which implies differing strategies for control policies. The “drugs-cause-crime” explanation assumes that

* An earlier version of this paper was presented at the 1984 annual meetings of the American Society of Criminology. The preparation of this manuscript was supported, in part, by grants from the National Institute on Alcohol Abuse and Alcoholism (AA-05823) and the National Institute on Drug Abuse (DA-03395). The authors express their gratitude to two anonymous reviewers for their valuable comments.

CRIMINOLOGY VOLUME 25 NUMBER 3 1987 715

716 WHITE, PANDINA, AND LAGRANGE

drug users need to generate illicit income to support their drug habit, and/or that the psychopharmacological effects of drugs increase the addict’s propen- sity toward crime, and especially violent crime. Recent and impressive evidence of the drugs-cause-crime explanation comes from Gropper (1984). He cites research indicating that raising or lowering the frequency of substance use among addicts raises or lowers their frequency of crime. Other studies demonstrate that criminal activity is significantly greater following addiction to drugs than before addiction (for example, DeFleur, Ball, and Snarr, 1969). Despite this empirical support, Watters et al. (1985) maintain that these findings are far from conclusive, are often based on cross-sectional data, and have not controlled for the effect of age. It is probable that for some youths under some conditions, the use of illegal drugs leads to criminal behavior; there is little convincing evidence that this happens for the majority of youths. None- theless, the general sentiment that drugs cause crime remains deeply ingrained in the public’s mind.

A second perspective holds that “crime causes drug use.” According to this explanation, involvement in delinquency provides the context, the reference group, and definitions of the situation that are conducive for subsequent involvement with drugs (Bachman, O’Malley, and Johnston, 1978; Elliott and Ageton, 1981). Again, the evidence supporting this view is not conclusive. While it is indeed probable that crime leads to drug usage under certain conditions for certain persons, this deviance progression from crime to drugs is not likely to reflect the dominant pattern.1

Watters et al. (1985) identify a third perspective that is generating increas- ing research and theoretical support. Rather than being causally connected, the empirical link between drug use and crime is assumed to be spurious and the result of both having similar etiological roots (Goode, 1972; Collins, 1981; Elliott and Huizinga, 1984). The “common-cause” models identify a number of social and psychological factors seemingly shared by adolescent substance users and delinquents and appear to demonstrate that similar causal processes exist for both forms of deviance.

A variant of this common-cause model assumes that drug use and delinquency among youths are merely coincidental, simultaneous behaviors (that is, noncausal and nonreciprocal) in a concurrent cluster of other adolescent problem behaviors (Jessor and Jessor, 1977; Kandel, 1978; White, Johnson, and Garrison, 1985). Drug usage and delinquency are thought to cluster together as a result of experimentation with a wide range of behaviors during

1. Causality is a quicksilverish concept in the social sciences. Researchers may wish to suggest causality, but limitations in their methods and data seldom allow them to d o so. Even in longitudinal data, evidence that variable A precedes variable B is not sufficient to conclude causality as the relationship actually may be spurious or reciprocal. For example, see Thornberry and Christenson (1984) for a discussion of the reciprocal relationship between unemployment and crime.

SERIOUS SUBSTANCE USE 717

the adolescent stage in the life cycle. This “coincident” model is more con- cerned with the meaning of a deviant act than with the cause(s) of that act. Jessor and Jessor (1977) suggest that qualitatively different behaviors (for example, smoking marijuana or vandalizing property) may serve the same underlying social-psychological function (for example, expressing independence from parental control, identification with peer group). Evidence supporting this view frequently is derived from adolescent samples where relatively nonserious forms of substance use (cigarette smoking, occasional alcohol use, or experimentation with marijuana) appear to occur simultaneously with relatively minor and infrequent forms of delinquent behavior. However, given a conducive social context and enduring patterns of support from peers, initiation into delinquency or drug use may eventually amplify into involvement in more serious forms of deviant behavior (Akers, Krohn, Lanza-Kaduce, and Radosevich, 1979). The implication is that coincident models may be better suited for explaining the drug-crime relationship at the lower end of the seriousness scale, while common-cause models may be more appropriate for explaining the relationship between serious substance use and serious crime. This second issue is the main question addressed in this paper. There are a few noteworthy applications of common-cause models to substance use and delinquency. Hawkins and Weis’s (1980) Social Development Model integrates social control and social learning theory stressing the importance of early antisocial behaviors, early experiences in the family, later experiences in the school, and interaction with peers. Their model has been moderately successful in predicting adolescent marijuana use and delinquency (Catalano, White, Hawkins, and Pandina, 1985). Elliott and Hui- zinga (1 984) tested a social-psychological model incorporating elements of traditional strain theory, social control (bonding) theory, and social learning theory; the social learning aspect suggests that bonding to deviant persons provides the social rewards (motivations) for deviant behavior. Elliott and Huizinga maintain that their results strongly support the common-cause hypothesis.*

The purpose of the present study is to test the etiological similarity of serious substance use and serious delinquency among adolescents. The “model” being tested is a mixture of control theory, differential association theory, and variables selected from the psychological literature on correlates of adolescent deviance. Although a substantial amount of research exists separately in the drug literature and the delinquency literature, there are few studies that focus directly on the overlap of drug use and delinquency, and even fewer that test

2 . Besides these more general theoretical models, single predictors for either or both deviant behaviors are abundant (for example, grade average, religiosity, and so on). For reviews, consult Kandel (1978) and Jensen and Rojek (1980).


for shared causal processes (Elliott and Huizinga, 1984; Watters et al., 1985). This paper attempts to further the understanding in this area.

THEORETICAL BACKGROUND

Hirschi’s (1969) control theory is the cornerstone of much delinquency the- orizing and research. Not only has control theory amassed substantial support in the delinquency literature (Wiatrowski, Griswold, and Roberts, 198 1; Matsueda, 1982; Agnew, 1985; LaGrange and White, 1985), recent applications suggest that control theory also has relevance to explaining adolescent substance use (Elliott and Huizinga, 1984; Marcos, Bahr, and Johnson, 1986; Massey and Krohn, 1986), although alternative explanations may be more predictive of substance use than control theory (White, Johnson, and Hor- witz, 1986). Central to Hirschi’s theory is the notion that youths who do not have strong bonds to society, such as weak attachments to parents, teachers, and peers, and limited commitment to educational pursuits, experience greater personal and social freedom to engage in delinquent behavior than youths who have strong bonds to society. Empirical applications of control theory differ in their measurement of central control concepts, in the opera- tionalization of delinquent behavior, and in overall research design. How- ever, with considerable regularity the evidence indicates that school variables are more predictive of delinquency than “under-the-roof” experiences (John- son, 1979), and that attachment to one’s friends is not predictive of delinquency without specifying whether the peers are delinquent or nondelinquent (Linden and Hackler, 1973).

In the original statement of control theory, Hirschi seriously underesti- mated the importance of delinquent peers, thus leaving an essential link in the delinquency process largely absent: that is, given the freedom from social controls, what provokes the desire to commit deviance? As a way to compen- sate for the specification error of a pure control theory, it is now common- place to integrate the central explanatory principles of control theory with Sutherland’s differential association theory (Sutherland and Cressey, 1978). This mixed theoretical approach has yielded substantial empirical support (Johnson, 1979; Matsueda, 1982; LaGrange and White, 1985; Massey and Krohn, 1986; Marcos et al., 1986).

Sutherland’s theory postulates that deviant behavior is learned through associations and definitions that either encourage (reinforce) or discourage (punish) such behavior. This suggests that youths who frequently associate with deviant friends also are likely to engage in similar deviant behavior because reinforcing definitions and behavior patterns are freely available. The deviance-inducing effect of deviant peers is well documented in adolescent delinquency (Johnson, 1979; Matsueda, 1982; LaGrange and White, 1985) and adolescent substance use (Jacquith, 198 1; Kaplan, Martin, and Robbins,


1984; Marcos et al., 1986; White et al., 1986). This study also utilizes the central components of control theory and differential association theory to test the etiological crossover for serious forms of substance use and delinquency. Multiple measures of the family, the school, and peers are employed. In addition, an assortment of intrapersonal measures (for example, self- esteem, distress, impulsivity, hostility, disinhibition) drawn from the relevant psychological literature (Bates, Labouvie, and White, 1986; Hindelang, 1972; Jessor and Jessor, 1977; Kaplan et al., 1984; Labouvie and McGee, 1986; White, Labouvie, and Bates, 1985) is included. (The measures are discussed more fully below.)

This study differs from much previous research in several ways. First, rather than relying on cross-sectional data, this study uses longitudinal data to predict subsequent serious substance use and serious delinquency (measured three years later). Second, while many studies examine relatively homogeneous populations (for example, high school or college students) without attention to important developmental differences across age groupings, here adolescents in three age groups (12 to 15; 15 to 18; and 18 to 21 years old) are examined. Third, this study focuses on more serious forms of substance use and delinquency than generally found in the literature.

METHODS

Data were collected as part of the Rutgers Health and Human Develop- ment Project, a prospective longitudinal study which examines the acquisi- tion and maintenance of alcohol- and drug-using behaviors. The initial sample was obtained through random telephone calls in the State of New Jersey and was stratified by age and gender. (See Horwitz and White, 1987, for details about the sampling methods and participation rates.) Following the telephone contact, a staff member interviewed volunteering subjects and their parents in their homes. Subsequently, subjects came to the project center for an entire day of testing. The subjects were tested initially during 1979 and 1980 when they were 12, 15, or 18 years old (Time 1, T1) and returned three years later (1982/1983) to be retested (Time 2, T2) using essentially the same battery of instruments. The retest yielded a high three- year retention rate of 94%. A comparison of subjects who were retested and those who dropped out indicates minimal differences in the extent of substance use and delinquent behavior at T1.1

3. For example, for 18-year-old males, 53% of the follow-up sample as compared to 44% of the dropouts smoked marijuana in the last year and 16% of the former as compared to 13% of the latter committed at least one grand theft in the last three years. Statis- tical tests on several of the substance use and delinquency variables revealed no significant differences between follow-up and attrition samples.


SAMPLE

The total sample for the present analysis consists of 882 New Jersey adolescents grouped into three age groups: 135 male and 144 female 21-year-olds; 153 male and 152 female 18-year-olds; and 153 male and 145 female 15-year- olds. These ages reflect age at T2.

The sample is predominantly white (90%), a somewhat higher proportion than the 83% whites in New Jersey (U.S. Bureau of the Census, 1981). Half of the subjects are Catholic, 30% are Protestant, 9% are Jewish, and the remaining 1 1 % have another or no religion, analogous to the religious break- down in New Jersey. The median income of the sample at T1 is between $20,000 and $29,000 and is comparable to that of the entire state at that time (US. Bureau of the Census, 1981). With regard to family composition at T1, 79.9% live with both natural parents, 10.1% with a single parent, and the rest in other arrangements. Comparisons of participants and eligible refusers on various demographic variables (collected during the initial anonymous telephone interview) revealed similarity in terms of race, religion, and drinking behavior of the head of household. However, there is an overrepresentation of higher parental education levels and higher family incomes among participants, but no serious restriction on the range of these measures. (For more extensive details of methodological and theoretical considerations of this study see Pandina, Labouvie, and White, 1984.)

DATA COLLECTION AND INSTRUMENTS

Self-report data are utilized in this study. Overall, self-reports are accepted as reliable and valid indicators of substance use and delinquent behaviors (Akers et al., 1979; Elliott and Huizinga, 1984; Hindelang, Hirschi, and Weis, 1981; Single, Kandel, and Johnson, 1975). In addition, self-reports provide a more direct and more complete measure of various forms of deviant behavior than do measures based upon official law enforcement and institutional records (Elliott and Huizinga, 1984; Dunford and Elliott, 1984). To maxi- mize reliability and validity of the self-report data, questionnaires were administered individually by a trained interviewer assigned to a participant for the length of the testing day. Participants were instructed not to put their names on any questionnaire and were repeatedly assured of the complete con- fidentiality of all data especially with regard to parents, teachers, and public authorities.

The level of delinquency reported by the respondents is similar to the amount of involvement found in other surveys of predominantly middle-class adolescents (Linden, 1978; Levine and Kozak, 1979). The data on the prevalence of alcohol and drug use in the sample are comparable to and replicate rates for adolescents living in the Northeast region of the country (Johnston,

SERIOUS SUBSTANCE USE 72 1

O’Malley, and Bachman, 1984).4 (Data on prevalence of substance use and delinquency for this sample are presented in detail in Pandina and White, 1984.)

MEASURES

Dependent Variables. The authors wanted to obtain a broader, more repre- sentative view of adolescent substance abuse than is commonly found in the literature. Since adolescent substance abuse lacks an appropriate and consistent operational definition (White, in press), serious use was characterized using several convergent measures. First, alcohol was separated from other drugs because of the uniqueness attributed to the alcohol-crime (violence) relationship (Collins, 1981; Pandina and White, 1984) and because the theories of the etiology of alcoholism (Roebuck and Kessler, 1972; White, 1982) differ somewhat from those of the eiology of drug abuse (Lettieri, Sayers, and Pearson, 1980).

Adolescent problem drinking is estimated from the frequency with which adolescents experience 51 negative consequences or symptoms as a result of alcohol use (such as trouble with school authorities, fights with friends, mem- ory losses). (The odd-even split-half reliability for this scale is .92.) Adoles- cents who score more than one standard deviation greater than the mean for their age/gender group are defined as problem drinkers (APRO). A quantity-frequency index is also computed of the total amount of alcohol con- sumed (beer, wine, and distilled spirits). Subjects whose alcohol score is more than one standard deviation greater than the mean score for their age/gender group are defined as heavy drinkers (HAL).

Similar scales are constructed for drugs. Problem users (DPRO) are those adolescents who score more than one standard deviation higher than the mean for their age/gender group on a combined list of 102 negative consequences and symptoms experienced when using or because of use of marijuana (odd-even split-half reliability = .91) and of other drugs (odd-even split-half reliability = .95). Heavy drug (HDR) users are those adolescents who score more than one standard deviation greater than the mean for their age/gender group on the Substance Use Involvement Index (SUI). The SUI was developed by Pandina, White, and Yorke (1981) and reflects overall substance use involvement relative to the other subjects in the sample.5

4. For example, Johnston et al. (1984) report that in 1979-1980, 56%-61% of the high school seniors in the Northeast had used marijuana and 14% had used cocaine. Com- parable figures in the present sample are 63% and 19%, respectively, for 18-year-old subjects tested in these same years. (The fact that these rates are slightly higher than rates reported by Johnston et al. is probably due to the fact that some of the 18-year-olds in this sample are already in college or working.)

The SUI is a scale that combines both quantitative (for example, number of sub- stances used. number of times used, frequency of use, recency of use, quantity of use) and

5 .


A different approach is used to measure serious delinquency. Heavy delinquents (HDEL) are defined as those adolescents who have committed any index offense three or more times in the past three years (Elliott and Hui- zinga, 1984). Labeled delinquents (LDEL) are adolescents who have been incarcerated or on probation or parole in the last three years-that is, adolescents who have had formal contact with the criminal justice system.6

Independent VariabZes.7 The independent variables are multiple indicators of four domains: the family, school, peers, and intrapsychic domains. These variables are measured at T1 and used to predict T2 (three years later) serious substance use and serious delinquency.

Five measures of family influences are used that relate to the structure as well as the nature of the parent-child relationship. Parents’ tolerance of (1 = approve, 2 = not care, and 3 = disapprove of) subject substance use and of subject delinquency is measured. Parental control is a four-item scale (for example, how often parents “tell you how to spend your free time”) from an adapted version of the Youth Perception Inventory (Streit, 1978) and parental nurturance is measured using 16 items (for example, how often parents “give you a lot of care and attention”) from this same inventory. These four indices are measured from the child’s perception of parental behavior and attitudes. In addition, a measure of family intactness is used that indicates whether the subject lives with both natural parents (= 1) or not (= 2).

~~

qualitative (type of substance) aspects of substance use in a unitary score that reflects a user’s substance involvement relative to a specific reference group. This index enables comparison without the necessity of sequential comparisons for different drug classes. Weights are assigned to each level of substance use on an empirical basis as a function of the relative levels of use reported by the sample (Pandina et al., 1981). For this particular study, the SUI combines weighted values for extent, frequency, recency, and quantity of use of marijuana, PCP, inhalants, psychedelics, cocaine, and heroin and nonmedical use of analgesics, stimulants, sedatives, and tranquilizers.

6. The delinquency measures used here rely on self-reports of behaviors over a three- year period. Use of this time interval as opposed to the last year avoids the chance of missing any event. On the other hand, the longer recall period may distort the data somewhat. (See Elliott and Huizinga, 1984, for a detailed discussion of this issue.) It should be noted that even seriously involved adolescents in the sample are not the prototype of the most serious delinquents nationally. This is a primarily white, middle-class sample. The subjects are mostly school-oriented and are volunteers in a research project. However, within this sample, about 20% of the males had committed at least one index offense within the past three years.

The arrest and incarceration data should be interpreted with caution. Arrest data do not accurately reflect level of delinquency (Elliott and Huizinga, 1984). Furthermore, probabilities of arrest and severity of punishment are variable and depend upon many factors including community context, race, socioeconomic status, and so on.

All indices used in the present analysis have been carefully constructed and display appropriate psychometric properties for analysis. Because a complete listing of all items used in index construction is not possible here given the large number of items used, interested readers are encouraged to contact the senior author for further information.

7.


There are four measures of school influences that relate to achievement and commitment. School commitment is measured by two items (for example, how often you “try to get the best grade”) from the Moos Classroom Envi- ronment Scale (Moos and Tricket, 1974). Grade average is measured by combining the subject’s overall grade average with grades received in math and English in the last three years (A = 1 to F = 5). The subject’s educational expectations are also estimated by asking them how far they expect to go in school. Finally, the total number of times absent from school in the last year is measured by combining legitimate absences with illegitimate cuts.

Three indicators of peer influences include measures of the maximum proportion (none to all) of friends who have tried alcohol, who have tried drugs (including marijuana), and who have engaged in delinquent behavior (minor and serious offenses). In addition, there is a measure of friends’ tolerance to (1 = approve, 2 = not care, and 3 = disapprove of) the subject using sub- stances and a measure of friends’ tolerance of their committing delinquent behaviors.

The final domain tapped reflects intrapsychic (or intrapersonal) functioning. Several areas of functioning are assessed on the basis of previous research suggesting the potential importance of each correlate. Also measured are the following: (1) self-esteem using ten items measuring the frequency of positive and negative self-evaluations (for example, how often you “feel that you are a good person”); (2) life distress combining a modified version of the Life Events scales (Dohrenwend and Dohrenwend, 1981) and a modification of Havighurst’s (1972) life issues sca1e;g (3) several scales from the Personality Research Form (Jackson, 1968) which indicate personality traits of need for achievement, harm avoidance, autonomy, and impulsivity; (4) four scales from the Johns Hopkins Symptom Checklist (SCL-90R) (Der- ogatis, 1977) which tap psychiatric symptomology: depression, anxiety, hostility, and paranoid ideation; and (5) the Disinhibition Scale of the Zuckerman (1979) Sensation Seeking Scale.

RESULTS EXTENTOFOVERLAP

The first issue addressed is the extent of overlap between serious substance

8. Subjects were to indicate whether the events had ever happened to them, and for those events that had happened, whether they were causing emotional upset at the present time. A list of life issues based on Havighurst’s (1972) notion of developmental tasks for adolescents, previous research on adolescent worries and problems, and Izard’s ( 1977) notion that negative emotions may be elicited by events, persons, objects, and cognitions also was included. Subjects were asked to indicate the degree of “bothersomeness” of all applicable problems (response scale: not at all, a little, somewhat, a lot). A person’s total distress score was obtained by adding up the number of upsetting events and the number of bothersome (somewhat, a lot) problems.


use and delinquency: what proportion of adolescents who are serious substance users are also serious delinquents? The percentage of all subjects who meet the global criteria as serious users or serious delinquents is presented in Table 1. Also indicated is the percentage who meet dual criteria-that is, who are both serious users and serious delinquents. These data indicate that between 23% and 43% of the males and between 16% and 38% of the females meet at least one criterion of serious substance use. These percent- ages increase with age for both genders. In general, the percentage of serious delinquents is lower than for serious substance users, especially among females. The percent of adolescents meeting both criteria is relatively low; overall 7% of the adolescents in the sample (or approximately one-third of the serious substance users and two-thirds of the serious delinquents) meet at least one criterion of serious delinquency and at least one criterion of serious substance use. (This percentage is higher than Elliott and Huizinga’s (1984) estimate of 1.5%, probably due to the differences in the way substance use was measured and possibly due to the differences in the age range of the subjects.) Hence, approximately two times as many males are either serious delinquents or serious substance users than are both, and for females this ratio is about seven to one. At each age level, more males than females meet the dual criteria.

Table 1. Percentage of Adolescents Who Are Classified as Serious Substance Users or Delinquents by Age and Gender

Serious Substance Users Serious

Total (HAL,APRO,HDR Delinquents Met Only Met Age/Gender N or DPRO) (HDEL or LDEL) One Criterion Both Criteria

15 M 153 20 1 1 16 7 15 F 145 15 3 14 2 18 M 153 26 18 21 11 18 F 152 27 3 25 3 21 M I35 36 20 29 13 21 F 144 334 4 31 4

Total 882 26 10 23 7

Six discreet criterion groups representing different typologies for serious users and serious delinquents are established as outlined under the Measures section: heavy alcohol users (HAL), heavy drug users (HDR), problem alcohol users (APRO), problem drug users (DPRO), heavy delinquents (HDEL), and labeled delinquents (LDEL). Table 2 presents the number of subjects


Table 2. Extent of Overlap Among Alcohol Use, Drug Use, and Delinquency for Males (In Percents)

Number of Other Groups

15-Year-Olds

0 1

2 3 4 5

Total N

18-Year-Olds

0 1

2 3 4 5

Total N

2 1 -Yedr-Olds

0 1 2 3 4 5

Total N

Total

0 1 2 3 4 5

Total N

Heavy Alcohol Users

33 25 25 17 0 0

12 -

29 23 12 18 18 0

12 -

33 38 14

10 0 5

21 -

32 30 16 14 6 2

50 -

Problem Alcohol Users

Heavy Drug Users

18 23 35 18 6 0

17 -

11

28 28 I 1 22 0

18 -

6 20 29 29 0 6

17 -

1 1

27 31 19 10 2

52 -

6 35 35 18 6 0

17 -

22 22 30 13 13 0

23 -

18 44 15 18 0 4

27 -

16 34 25 16 6 2

67 -

Problem Drug Users

Heavy Delinquents

0 31 38 23

8 0

13 -

0 12 50 19 19 0

16 -

17 22 33 22 0 6

18 -

6 21 40 21 9

2 47 -

40 30 20 0

10 0

10 -

33 20 13 20 13 0

15 -

27 36 27 0 0 9

1 1 -

33

28 19 8 8 3

36 -

Labeled Delinquents

14 29 29 14 14 0 7 -

23 18

18 18 23 0

17 -

35 18

23 18

0 6

17 -

27 20 22 17 12 2

41 -


Table 3. Extent of Joint Membership for Males (In Percents)

Membership In Other Groups

Heavy Alcohol Users (HAL)

Problem Alcohol Users (APRO)

Heavy Drug Users (HDR)

15-Year-Olds

HAL APRO HDR DPRO HDEL LDEL N

18-Year-Olds


2 1 -Year-Olds


Total - HAL APRO HDR DPRO HDEL LDEL N

-

42 33 17 8

25 12 -

-

47 29 29 24 41 17 -

-

48 33 14 19 10

21 -

-

46 32 20 18

24 50 -

29 -

53 47 24 18 17 -

44 -

50 56 22 33 18 -

59 -

41 48 24 35 17 -

44 -

48 50 23 29 52 -

24 53 -

71 12 24 17 -

22 39 -

52 22 39 23 -

26 26 -

48 15

33 27 -

24 37 -

55 16 33 67 -

Problem Drug Users (DPRO)

Heavy Delinquents (HDEL)

Labeled Delinquents (LDEL)

15

62 92 -

23 15

13 -

31 62 75 -

38 44 16 -

17 44 72 -

1 1 39 18 -

21 55 79 -

23 34 47 -

10

40 20 30 -

10

10 -

27 27 33 40 -

33 15 -

36 36 36 18 -

9 11 -

25 33 31 31 -

19 36 -

43 43 57 29 14 - -

7

41 35 53 41 29 - -

17

12 35 53 41

6 - - 17

29 37 54 39 17 - - 41


meeting criteria for each typology by age; also indicated are the percentage of subjects in each criterion group who meet criteria for one or more additional typology groups. (Since fewer than 3% of the females meet the criteria for heavy delinquency (n = 10) and/or labeled delinquency (n = lo), females are eliminated from this analysis, as well as the remainder of the analyses.)

The data presented in Table 2 indicate that 32% of heavy alcohol users do not fall into other criterion groups, 28% fall into only one additional group, and 16% fall into only two other groups. Inspection of the data indicates that subjects often meet criteria for membership in several typological groups. However, with few exceptions, only about one-third or fewer of the 15- and 21-year-olds fall into more than two additional criterion groups. The middle age group has the greatest number who fall into three or more categories.

The degree of overlap between qualitatively distinct criterion groups is dis- played in an alternate fashion. The percentage of subjects in each use and delinquency criterion group who also meet criteria for membership in other groups is presented in Table 3. Considering the two subgroups of serious alcohol users, about half of the two older age groups who fall in one subgroup also fall in the other. The extent of overlap is greater between the two serious drug user groups, especially within the youngest age group.

The extent of overlap between heavy and labeled delinquents is relatively small within the youngest and oldest age groups (approximately 10%) and only one-third or less within the middle age group. Thus, it appears that those adolescents committing index offenses are not necessarily the same individuals who receive formal punishment through the criminal justice system. These findings replicate those reported by Dunford and Elliott (1984).

Across deviance categories, the greatest degree of overlap appears to be between the problem alcohol and problem drug users. Approximately one- half of the adolescents exhibiting problems with one substance also display serious problems with the other. On the other hand, less than one-third of heavy users of one substance are also classified as heavy users of the other. Approximately one-fourth to one-half of the heavy and labeled delinquents also fall in each of the serious substance use categories with over one-half of the labeled delinquents also being heavy drug users. In sum, these data suggest that the target behaviors of serious use and delinquency are not necessarily isolated within one distinct group of adolescents who are serious alcohol and drug users and delinquents, but rather that a significant number of adolescents distribute themselves across a number of mixed delinquency use groupings.

PREDICTORS OF SERIOUS DRUG USE AND DELINQUENCY

Analyses of covariance (with unequal cell frequencies) are performed for


each of the 25 independent variables9 using each of the six seriousness groups. The purpose is to determine if individuals displaying “serious deviant behavior” differ from those not displaying such behavior. (Age is covaried in all analyses since the majority of the independent variables have been shown to be significantly related to age.) The results of post hoc least square means comparisons for significant group differences are presented in Table 4.

In general, the same covariates are significantly related to heavy alcohol use as to problem alcohol use. The only differences are that family intactness, parental nurturance, and harm avoidance differentiate heavy from nonheavy users but not problem from nonproblem users, while school commitment dif- ferentiates problem from nonproblem users but not heavy from nonheavy users. Although different adolescents fall into these two categories of serious alcohol use, the same variables tend to relate to membership in either. Simi- larly, variables related to heavy and problem drug use are almost identical except that parental nurturance and hostility are significantly related to heavy and not problem drug use and educational expectations are related to problem but not heavy drug use. All of the variables related to serious drug use are also related to serious alcohol use, although self-esteem, distress, and need for achievement relate significantly to serious alcohol use but not drug use.

The covariates of heavy and labeled delinquency differ qualitatively. These differences are not apparent in the two other deviant categories. The only covariates that relate to both types of delinquency are educational expectations, grade average, school commitment, and distress. Whereas friend delinquency and tolerance of delinquency relate to heavy delinquency, friend drug use and tolerance of substance use relate to labeled delinquency. Family intactness and parental nurturance relate significantly to labeled, but not heavy delinquency. Also, labeled delinquency relates to autonomy while heavy delinquency relates to harm avoidance.

The same peer and school variables relate to serious substance use as to one of the serious delinquent categories. In fact, all the friend variables studied here except friend alcohol use significantly relate to membership in both substance use and one of the delinquency criterion groups. Likewise, all variables within the school domain except for total number of times absent from school relate to all the seriousness groups. On the other hand, most of the

9. Scores on the Disinhibition scale of the Zuckerman Sensation Seeking Scale were not available for the 15-year-olds. The independent variables were measured at T1 when these subjects were 12. The Sensation Seeking Scale was not administered to 12-year-olds because Zuckerman (1979) indicates that 14 is the minimum age for which the scale should be used. School commitment was not measured for individuals no longer in high school or below. The Disinbition and School Commitment scales are excluded from the later discriminant function analyses in order to maintain sample sizes and to be consistent across all age groups.


intrapsychic variables employed here relate to substance use (especially alcohol use) and not to delinquency. Serious delinquents share only a few personality characteristics in common with serious substance users (that is, they tend to be more distressed, more autonomous, and have less need for harm avoidance than their nondeviant peers). Depression, anxiety, and paranoid ideation are the only intrapsychic variables not significantly related to membership in a deviant group. The absence of a strong relationship between the family domain and serious substance use or delinquency is especially noteworthy. Only parental nurturance and family intactness are related significantly to any of the seriousness groups. Even so, significant differences are minimal.

Examination of the post hoc least square means demonstrates that all differences are in the expected direction. For example, adolescents most seriously involved with alcohol or drugs as compared to their peers who are less involved: (1) perceive less parental love, (2) have lower educational expectations, lower grades, and less commitment to school, (3) have friends who use drugs, commit delinquent acts, and are more tolerant of substance use, (4) have lower self-esteem, higher distress, lower need for achievement, higher need for autonomy, and lower need for harm avoidance, and ( 5 ) are more impulsive, hostile, and disinhibited.

All putative “predictors” that were significantly related to any form of serious deviance in the analyses of variance (see footnote 9) are entered into a discriminant analysis in order to determine if these 15 variables together can discriminate adolescents who meet any of the criteria for serious substance use (that is, HAL or APRO or HDR or DPRO) (group = 2) from those who meet none of these criteria (group = 1). Analyses are conducted separately by age, and the results are summarized in Table 5. The same analyses are repeated to discriminate adolescents who meet the criteria for serious delinquency (HDEL or LDEL) (group = 2) from those who do not (group = 1). These results are summarized in Table 6.

The model is powerful in predicting group membership across age groups for serious substance use and serious delinquency. That is, 72% to 84% of the serious/nonserious substance users and 80% to 96% of the serioushonserious delinquents are classified correctly. While classifications are relatively accurate, it should be noted that a reasonably accurate prediction could be made by considering only baseline rates of group membership. Specifically, given that membership in a serious deviant group ranges from 20% to 35%, 65% to 80% of the cases could be classified correctly by assigning each case into the nonserious group. Knowledge of a subject’s status on predictor variables, however, does increase classification accuracy substantially in the case of 1 8-year-old serioushonserious substance users and delinquents (respectively, 11% and 15% increases above base rates).

It is valuable to examine the classification summaries in order to determine

Tabl

e 4.

Sign

ifica

nt E

ffec

ts o

f Fa

mily

, Sc

hool

, Fr

iend

, an

d In

trap

sych

ic V

aria

bles

on

Seri

ous

Alc

ohol

U

se, D

rug

Use

, and

Del

inqu

ency

for

Mal

es (

Post

Hoc

Lea

st S

quar

e M

eans

Pre

sent

ed)

Hea

vy

Alc

ohol

Use

rs

Fam

ily

INF

AM

PT

OL

S

PT

OL

D

PN

UR

P

CO

N'

Scho

ol

ED

EX

P

AX

G

RA

DE

' C

OM

MIT

'

Frie

nds

FR

AL

C'

FR

DR

U'

FR

DE

L'

FT

OL

D'

FTO

LS'

~

Non

heav

y

1.1 -

-

3.3 -

3.5 -

3.2 -

-

2.6

2.1 -

2.3

Hea

vy

__

1.3*

-

-

3.0*

* -

3.1*

* -

3.8*

* -

-

3.0'

2.6*

-

2.0*

*

Prob

lem

H

rd\q

H

edvy

A

lcoh

ol U

wr\

D

rug

Use

rs

Prob

lem

Dru

g U

sers

D

elin

quen

t\

Non

prob

lem

Pr

oble

m

Non

hedv

q -~

Hea

cq

Non

prob

lem

Pr

oble

m

Non

heav

y He

a\y

-

.-

-

-

-

3.5 -

3.2

3.7

-

2.6

2.1 -

2.3

-

-

-

-

-

3.2*

* -

3.8*

* 3.

3**

-

3.1*

*

2.8*

**

-

2.1*

*

-

-

-

3.3 -

-

-

3.2

3.7

-

2.6

2.1 -

2.3

-

-

-

3.1*

-

-

-

3.7*

* 3.

3***

-

3.2*

**

2.7*

**

-

1.9*

**

-

-

-

-

-

3.5 -

3.2

3.7

-

2.6

2.1 -

2.3

-

-

-

-

-

3.2*

-

3.8*

* 3.

2***

-

3.3*

**

2.7*

* -

1.9*

**

-

-

-

-

-

2.7*

**

-

3.8*

* 3.

3***

-

-

3.0*

**

2.2*

* -

Labe

led

Del

inqu

ents

Non

labe

led

Labe

led

1.1 -

-

3.3 -

3.5 -

3.2

3.7

-

2.6 -

-

2.3

1.3*

-

-

3.1*

-

3.1*

* -

4.0*

**

3.3*

*

-

3.2*

* -

-

1.9*

**

Tabl

e 4

(Con

tinue

d)

Hea

vy

Prob

lem

H

eavy

H

eavy

A

lcoh

ol U

sers

A

lcoh

ol U

sers

D

rug

Use

rs

Prob

lem

Dru

g U

sers

D

elin

quen

ts

Labe

led

Del

inqu

ents

~~ N

onhe

avy

Hea

vy

Non

prob

lem

Pr

oble

m

Non

heav

y H

eavy

N

onpr

oble

m

Prob

lem

N

onhe

avy

Hea

vy

Non

labe

led

Labe

led

Intr

apsy

chic

-

-

-

-

-

-

-

-

EST"

18

.2

16.5

' 18

.2

16.5

* D

ISTR

5.

3 1.

4***

5.

3 7.

2**

-

AC

H

1.0

6.1*

* 7.

0 6.

2.

AU

T"

4.8

5.4*

4.

8 5.

5.

4.7

5.9*

**

4.1

6.0*

**

-

-

4.8

5.8*

* H

AV

O"

5.8

4.9*

-

-

IMP"

5.

3 6.

l*

5.2

6.7*

**

5.3

6.2*

* 5.

3 6.

1*

DE

P A

NX

H

OST

" 0.

8 1.

2**

0.8

1.2*

* 0.

8 1.

0*

PA

RID

D

ISIN

4.

3 5.

4*

4.4

5.4*

* 4.

3 5.

4***

4.

3 5.

8***

-

-

-

5.4

7.4*

* 5.

4 6.

9*

-

-

-

-

-

-

-

-

-

-

5.9

4.3*

**

5.8

4.2*

**

5.8

4.4*

* -

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

~~~

"Sig

nific

ant (

p <

.05)

age

effe

ct

INFA

M =

Int

act

Fam

ily;

PTO

LS =

Par

enta

l To

lera

nce

of S

ubst

ance

Use

; PT

OL

D =

Par

enta

l To

lera

nce

of D

elin

quen

cy;

PNU

R =

Par

enta

l N

urtu

ranc

e; P

CO

N =

Par

enta

l C

ontr

ol; E

DE

XP

= E

duca

tiona

l Exp

ecta

tions

; AB

S =

Tot

al A

bsen

ces;

GR

AD

E =

Gra

de A

vera

ge;

CO

MM

IT =

C

omm

itmen

t to

Sch

ool;

FRA

LC

=

Frie

nd A

lcoh

ol U

se;

FRD

RU

= F

rien

d D

rug

Use

; FR

DE

L =

Fri

end

Del

inqu

ency

; FT

OL

D =

Fri

end

Tole

ranc

e of

Del

inqu

ency

; FTO

LS =

Fri

end

Tole

ranc

e of

Sub

stan

ce U

se; E

ST =

Sel

f-Es

teem

; DIS

TR =

Dis

tress

; A

CH

= N

eed

for

Ach

ieve

men

t; A

UT

= A

uton

omy;

HA

VO

= H

arm

Avo

idan

ce;

IMP

= Im

puls

ivity

; D

EP

= D

epre

ssio

n; A

NX

= A

nxie

ty;

HO

ST =

H

ostil

ity;

PAR

ID =

Pa

rano

id I

deat

ion;

DIS

IN =

Dis

inhi

bitio

n.

*p <

.05

**p

< .0

1 **

*p <

.ool

z c) m

C

v,

m

Tab

le 5

. D

iscr

imin

ant

Ana

lysi

s C

lass

ific

atio

n Su

mm

ary

for

Seri

ous

Subs

tanc

e U

se

Am

ong

Mal

es b

y A

ge

15-Y

ear-

Old

\

Into

18-Y

ear-

Old

s 2 1

-Yea

r-O

lds

Into

In

to

From

1

2 ~

~

I 91

3

97

3 2

19

4 83

17

T

otal

I1

0 7

Perc

ent

94

6 Pr

iors

0.

80

0.20

Tot

al

94

100 23

100

1 I7

10

08

__

Fr

om

I 2

Tot

al

- -

~

1 91

6

91

94

6 10

0 2

15

20

35

43

57

100

Tot

al

106

26

132

Perc

ent

80

20

100%

Pr

iors

0.

73

0.27

From

I

2

1 66

14

82

18

2

21

22

49

51

Tot

al

87

36

Perc

ent

71

29

Prio

rs

0.65

0.

35

~ ~

Tot

al

80

100

43

100

123

1 00%

~

Wilk

s' L

ambd

a =

0.

85

ns

0.69

* 0.

70*

Ave

rage

Can

onic

al R'

=

0.15

0.

31

0.30

* %

Tot

al C

lass

ified

%T

otal

Fal

se

%T

otal

Fal

se

Cor

rect

ly =

8 1

O/C

84%

72

%

Posi

tives

=

3%

5%

11%

Neg

ativ

es =

16

%

11%

17

%

*p <

.001

ns

= n

onsi

gnif

ican

t


N

2 LL € 1 -

c C u 5

2

11

00 .-

C

v)

s V n


the number of false positives and negatives which result from the application of the prediction equation used in the discriminant analyses. False positives are adolescents who are classified as being serious substance users or delinquents, but whose behavior does not warrant such a classification. Alterna- tively, false negatives are adolescents who should be classified into a serious target behavior group and are not.

While the false positive rate is high for only the 21-year-old serious substance use group (1 1% of the total group or 18% of group 1 subjects), the false negative rate is consistently high (9% to 12% of the total or 43% to 91 % of the group 2 members) for all analyses except 18-year-old serious/ nonserious delinquency groups. In sum, the classification results suggest, with the one exception noted above, that use of these 15 variables for prediction would result in missing almost half to almost all of the serious deviants. The data also suggest that an examination of these predictors at age 15 (in early high school) may be useful for predicting serious delinquency and, to a lesser extent, serious substance use three years later.

The discriminant analyses are significant (p < .001) for the two older age groups but not the youngest in the serious/nonserious substance use classification. An examination of predictors reveals that the major contributing variables in the discriminant function are, in order of relative strength, friends’ tolerance of substance use, impulsivity, grade average, friends’ delinquency, friends’ tolerance of delinquency, and need for autonomy for 18-year- olds and friends’ tolerance of substance use, need for achievement, and friends’ delinquency for 2 1 -year-olds. In the analyses of serious delinquency, significant (p < .05) results are obtained for the two younger age groups, but not the oldest group. The important variables in this classification are friends’ tolerance of delinquency, distress, friends’ delinquency, self-esteem, and need for harm avoidance for 15-year-olds and educational expectations, parental nurturance, and need for autonomy for 18-year-olds. Hence, the discriminant analyses demonstrate that the pattern of predictors which is most useful in discriminating between target behavior groups varies as a function of the type of target behavior (that is, serious delinquency versus serious substance use) being predicted as well as the age of the group members.

DISCUSSION Proponents of a common-cause model of the drug-delinquency nexus

among adolescents posit that a common set of etiological factors account for the association between both behaviors (Collins, 198 1; Elliott and Huizinga, 1984). The few studies that have tested common-cause models on both substance use and delinquency simultaneously (for example, Catalan0 et al.,


1985; Elliott and Huizinga, 1984) have obtained positive results. These studies have employed models utilizing central components of differential association theory and control theory to test the etiological commonality between substance use and delinquency. The present study examined the applicability of a common-cause model in explaining serious substance use and delinquency among adolescents. The model utilized central components of control theory and differential association theory and also included intrapersonal measures drawn from the psychological literature on substance use and delinquency.

In attempting to determine whether serious substance use and serious delinquency share common etiological roots, several strategies were employed. First, the extent to which the same subsamples of individuals dis- played both target behaviors was examined. While a majority of the serious delinquents are also serious substance users, only about one-third of the serious users are also classified as serious delinquents. This finding is consistent with Elliott and Huizinga’s (1984) results. They found that serious and frequent delinquent behaviors directly related to a full range of drug-use behaviors including problem use, whereas the type and frequency of drug use was only directly related to selected types of crime (for example, felony theft, sell- ing drugs, and public disorder crimes) and not to general deviance.

Second, an attempt was made to determine if a common set of putative etiological factors are related to both target behaviors. Partial support for a common-cause hypothesis was obtained. The same variables from the school and peer domains are related to both behaviors. These are the same variables often used in tests of control and differential association models. Yet the parental variables studied here, also typically used in tests of these same two theories, are only weakly related to the target behaviors. Conversely, many of the intrapsychic variables tested here differentiate significantly between serious and nonserious alcohol users and, to a lesser extent, between serious and nonserious drug users. Yet, very few relate to serious delinquency.

Finally, the ability of these etiological factors to differentially classify serious and nonserious substance users as well as serious and nonserious drug users was determined. The results indicate that there are differences in the strength of predictors in classifying serious versus nonserious substance use and delinquency. While friend behaviors and attitudes are consistent across groups (except the oldest serious delinquents), school and personality variables differ in their significance as predictors of each target behavior. In addition, differences across age groups are noteworthy. The fact that both behaviors share some predictors in common also lends support to a common- cause hypothesis. However, the complexity of the relationship is highlighted by the observed differences in the predictive models. A combination of differential association theory and control theory (Johnson, 1979; Matsueda, 1982; LaGrange and White, 1985; Massey and Krohn, 1986; Marcos et al., 1986)


may be useful in explaining deviance proneness among adolescents. How- ever, there may be an additional set of predictors that differentiate “deviants” who will become serious delinquents from those who will become substance abusers. Data presented here suggest that several intrapsychic variables (for example, impulsivity, need for achievement) act as moderating influences. Future research should attempt to more clearly distinguish delinquents from substance users and test an “independent” versus a common-cause hypothesis of the substance use/delinquency nexus.

The findings presented above have relevance for intervention approaches. They suggest that joint programming may present several drawbacks. The results indicate that serious alcohol use, drug use, and delinquency are not necessarily concentrated in a homogeneous grouping of adolescents, but rather that each group represents a somewhat unique set of individuals whose dynamic processes are qualitatively distinct. Since peer groups generate considerable influence on behaviors (Akers et al., 1979; Jacquith, 1981; Mat- sueda, 1982), combined prevention approaches, by bringing together diverse groups of adolescents, may perpetuate further socialization into alternative forms of deviance. Also, the data suggest that serious delinquents and serious substance users do not necessarily express similar personality needs and “dis- turbances.” Intervention strategies may therefore require more individual- ized treatments than can be offered in joint programs. Social policies aimed at reducing serious substance use and delinquency should reflect both independent and common features of these target behaviors.

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delinquency. Contemporary Drug Problems Fall: 35 1-373.


White, Helene Raskin In Press The relationship between heavy drug and alcohol use and problem use

among adolescents. In Stanley Einstein (ed.), Drug and Alcohol Use: Issues and Factors. New York: Plenum. Sociological theories of the etiology of alcoholism. In Edith L. Gomberg, Helene R. White, and John A. Carpenter (eds.), Alcohol, Science and Society Revisited. Ann Arbor: University of Michigan Press and Center of Alcohol Studies.

The drug-crime nexus among adolescents and their peers. Deviant Behavior

1982

White, Helene Raskin, Valerie Johnson, and Carole Garrison 1985a

6: 183-204.

White, Helene Raskin, Erich W. Labouvie, and Marsha E. Bates 1985b The relationship between sensation seeking and delinquency: A longitudinal

analysis. Journal of Research in Crime and Delinquency 22: 197-211.

An application of three deviance theories to adolescent substance use. International Journal of the Addictions 21: 347-366.

Social control theory and delinquency. American Sociological Review 46:

White, Helene Raskin, Valerie Johnson, and Allan Horwitz 1986

Wiatrowski, Michael D., David B. Griswold, and Mary K. Roberts 198 1

525-541.

Zuckerman, Marvin 1979 Sensation Seeking: Beyond the Optimal Level of Arousal. Hillsdale, NJ:

Lawrence Erlbaum Associates.

Helene Raskin White is Assistant Professor of Sociology at the Center of Alcohol Stud- ies, Rutgers University. Her research focuses on the etiology of adolescent substance use and delinquency and the consequences of alcohol and marijuana use. Her publications are primarily in the field of alcohol and drug studies, although she has published several articles on delinquency.

Robert J . Pandina is Associate Professor of Psychology at the Center of Alcohol Studies, Rutgers University. His research emphasis is on identifying psychosocial and biopsycho- logical profiles and consequences associated with alcohol- and drug-taking behaviors. He is a frequent contributor to the alcohol and drug literature.

Randy L. LaGrange is Assistant Professor of Sociology and Criminal Justice at the Uni- versity of North Carolina at Wilmington. His research interests include fear of crime, com- parative criminology, and delinquency. He has published several articles in these areas.

longitudinal predictors of serious substance use and delinquency

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