Norms and sensitivity of the adolescent version of the drug use screening inventory

Addictive

Behavior\. Vol. 20, No. 2. pp. 149-17, 1995 Copyright G 1995 Elsevier Science Ltd Printed in the USA. All rights reserved 0306-4603195 $9.50 + .OO

Pergamon

0306-4603(94)ooo58-1

NORMS AND SENSITIVITY OF THE ADOLESCENT VERSION OF THE DRUG USE SCREENING INVENTORY LEVENT

KIRISCI,

ADA MEZZICH. University

and RALPH TARTER

of Pittsburgh

Abstract - The distribution and the statistical accuracy of scores on the Drug Use Screening Inventory (DUSI) and the discriminative power of the DUSI for identifying individuals who qualify for a DSM-III-R diagnosis of Psychoactive Substance Use Disorder (PSUD) were examined in 846 adolescents. The subjects with PSUD had higher mean scores, and the distribution of their scores approximated a normal distribution in each of the 10 domains measured by the DUSI. All of the DUSI domains yielded more precise trait estimates for the subjects who had more severe PSUD. Within the normal sample. using a score of 30 on the overall problem density index as the cutoff score, the DUSI correctly classified 95% of the normal sample and 81% of the PSUD cases.

It is generally accepted that alcohol and drug abuse is a polythetic disorder. That is. there is no single or necessary condition which encompasses all individuals. and the configuration of symptoms or disturbances varies among individuals in the population. Arguably, the heterogeneity of manifest disturbances is so large that the diagnostic entity of Psychoactive Substance Use Disorder (American Psychiatric Association, 1987) is too broad to have utility for understanding etiology and natural history or to recommend a specific treatment modality likely to be effective (Tarter. Moss et al., 1992). The Drug Use Screening Inventory was developed with the intention of quantifying severity of disturbance of alcohol and drug abuse in conjunction with nine other commonly experienced facets of disturbance (Tarter. 1990). Because a common measurement scale is utilized for the 10 domains, it is possible to profile severity of disturbances within a multidimensional framework. Toward this end. the DUSI characterizes each person’s unique configuration of problems consequent to drug or alcohol involvement. Similar to other dimensionally oriented instruments. such as the Addiction Severity Index (McClellan et al., 1980). the DUSI provides quantification of the consequences of alcohol and drug involvement which are integral to diagnostic formulation within the DSM-III-R or DSM-IV taxonomic systems. Homologous versions of the DUSI have been developed for adults and adolescents. With respect to the latter version, validity and reliability, estimates reveal that the DUSI has sound psychometric properties (Tarter et al.. in press: Tarter, Laird et al.. 1992). In addition, scores on the DUSI among alcohol- and drug-abusing adolescents have been shown to be related to magnitude of temperament deviations (Tarter et al.. 1990) and coping capacities (Mezzich et al.. in press): these latter psychological processes have been implicated to be etiologically salient in the early-age-onset variant of substance abuse. This article has two aims: (1) to describe the distribution and the statistical accuSupported by grants from the National Institute on Alcohol Abuse and Alcoholism (AA 08746) and the National Institute on Drug Abuse (DA 05605. DA 059.52). Requests for reprints should be sent to Levent Kirisci. PhD. Pittsburgh Adolescent Alcohol Research Center, Department of Psychiatry. University of Pittsburgh. Pittsburgh. PA 15213. 149

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racy of scores on the DUSI among adolescents who encompass the spectrum of drug nonusers, users, and abusers; and (2) to examine the discriminative power of the DUSI for identifying individuals who qualify for a DSM-III-R diagnosis of Psychoactive Substance Use Disorder (American Psychiatric Association, 1987). METHODS

Subjects Three groups of adolescents ranging in age between 12 and 18 participated in the study. The sample consisted of 259 subjects who qualified for a DSM-III-R diagnosis of Psychoactive Substance Use Disorder (PSUD) (American Psychiatric Association, 1987), 278 normal subjects who had varying degrees of involvement with alcohol and drugs but did not meet criteria for a PSUD diagnosis, and 309 subjects who met criteria for a psychiatric disorder but did not qualify for a substance abuse disorder. To capture a broad spectrum of severity of involvement with alcohol and drugs, spanning no use to threshold diagnosis, subjects were recruited from diverse sources, including inpatient and outpatient treatment facilities. juvenile court, and the general population using advertisement, the reverse telephone book. and the snowball procedure. Employing these diverse recruitment methods and drawing from multiple sources afforded the opportunity to derive a sample which is sufficiently large and heterogenous that it is representative of the population. Table I summarizes the demographic and personal characteristics of the three groups. Table 2 summarizes the distribution of diagnoses in the PSUD group. As can be seen, cases of pure alcohol abuse and pure drug abuse are rare. This finding is congruent with numerous investigations demonstrating a high prevalence of psychopathology in the early-age-onset variant of substance abuse. Also. in keeping with contemporary secular trends, the most prevalent pattern consists of conjoint alcohol and drug abuse in association with other axis I or axis II psychiatric disorders. The psychiatric group was heterogeneous with respect to diagnostic distribution. The prevalence of specific diagnoses, listed in Table 3. is commensurate with other clinical samples of adolescents. To qualify as a normal control, the subject could not qualify for a current or lifetime diagnosis. Table 1. Demographic

Age Grade SES Ethnicity Euro-American Afro-American Other

and personal characteristics

of the normal, PSUD, and psychiatric groups

Normal (n = 278)

PSUD (n = 259)

M

(SD)

M

(SD)

M

(SD)

14.34 8.13 2.25

(1.7) (3.0) (1.5)

IS.95 9.34 3.21

(1.2) (1.5) (1.2)

14.84 8.53 2.81

(1.7) (1.8) (1.3)

Psychiatric (n = 309)

N

(Q)

N

(R)

N

(57)

245 30 3

(88. I) (10.8) (1.1)

207 49 3

(79.9) (18.9) (1.2)

211 90 8

(68.3) (29.1) (2.6)

100%

100%

100%

Sex

M F

125 153

(45.0) (55.0)

I oov

117 142

(45.2) (54.8)

loo%

152 I.57

(49.2) (50.8)

100%

Adolescent

drug use inventory

Table 2. Distribution of alcohol abuse, drug abuse, and psychiatric diagnoses in PSUD group Presence of comorbid psychiatric disorder (5%)

Absence of comorbid psychiatric disorder (‘SF)

28.2 8.5 59.1

Alcohol abuse only Drug abuse only Alcohol and drug abuse

2.3 0.4 I.4

Instrrmentution The Drug Use Screening Inventory (DUSI), a multidimensional self-report instrument, quantifies severity of involvement with drugs and alcohol and commonly associated health, psychiatric, and psychosocial problems (Tarter, 1990). The questionnaire consists of 149 items that are answered either yes or no. The problem density (severity) score for each domain is obtained by dividing the number of yes endorsements by the number of items. The resulting value, multiplied by 100, yields the problem density score that has a range from 0 to 100% in each of 10 domains. In this fashion, a profile of problem severity is obtained across a common scale. The domains are (1) substance use; (2) behavior pattern: (3) health status: (4) psychiatric disorder; (5) social competence; (6) family system; (7) school adjustment; (8) work adjustment; (9) peer relationships; and (10) leisure and recreation. Procedure At the outset, informed consent was obtained from the subjects and either a parent or legal guardian. Next, each subject was administered a diagnostic interview by a trained master’s level clinician using the children’s version of the Schedule for Affective Disorders and Schizophrenia (K-SADS)(Orvaschel et al., 1982) or, for the subjects over 16 years of age, an expanded version of the Structured Clinical Interview for DSM-III-R (Spitzer, Williams, & Gibbon, 1987). Diagnoses were assigned to each case following a clinical conference that consisted of the clinician assessor and a child psychiatrist or child clinical psychologist. The DUSI was administered by a research associate who was blind to the subject’s diagnosis and alcohol/drug use history. Although the DUSI can be administered using either computer interactive or paper and pencil formats, only the latter procedure was used in this study.

Table 3. Prevalence of DSM-III-R diagnoses in the psychiatric group” Diagnosis Anxiety disorder Conduct disorder Depression Oppositional defiant Attention deficit disorder Eating disorder Other mood disorder “Percentage total exceeds of multiple diagnoses.

5% 45.6% 36.9% 25.6% 19.7% 14.6% 2.6% 1.9% 100% because

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et al.

Data analysis

In the first part of the analyses, the statistical accuracy of measurements obtained from the DUSI was established. To determine the statistical accuracy of measurements, each item was assumed to be characterized by its discrimination and threshold values (Kirisci, Tarter, & Hsu, in press). The values were calculated using the Multilog (Thissen, 1991) computer program. They were used to obtain the standard error of measurement and information for each domain. According to item response theory, the standard error of measurement can be used as an indicator of accuracy. The term information, defined as the reciprocal of the square root of the standard error of measurement, was computed for each trait level in each domain. This value describes the precision of trait estimate for each individual in each domain. The smaller the standard error or higher the level of information at a given trail level, the more precise is the measurement. After establishing the statistical accuracy of the DUSI problem severity scores for each domain, percentile ranks were next computed for the normal subjects (N = 278). Cutoff scores were then computed to examine the DUSI’s efficacy at classification of an individual as either having or not having a Psychoactive Substance Use Disorder. RESULTS

Table 4 presents the DUSI scores for the normal, PSUD, and psychiatric groups. As expected, the PSUD group had higher mean scores and the distribution of their scores approximated a normal distribution in each domain. Among the normals, a skewed distribution of scores was found in the positive direction across all domains; this finding is commensurate with their normal status. Statistical accuracy of the problem density score in each DUSI domain is summarized in Table 5. A trait scale was constructed to reflect a continuum between -2.0 and +2.0. The starting point of -2.0 denoted the least severe cases (i.e., normal subjects), whereas the end value of +2 denoted the most severe substance-abusing cases (namely, a PSUD diagnosis). Hence, this trait scale encompassed subjects across the complete spectrum of substance involvement. As can be seen, all of the DUSI domains yield more precise trait estimates for the subjects who have more severe PSUD. Cases with lower severity of PSUD have relatively less precise measurement of trait estimates. The overall problem density index reflected the data obtained for each domain. The marginal reliability based on item response theory, obtained by averaging the reliability across trait levels, ranged between 0.53 and 0.83 for the 10 domains. The distribution of scores, expressed as percentile ranks, is presented for the normal group in Table 6. This distribution of scores was used to determine the discriminative power of the DUSI for advancing a PSUD diagnosis. The overall problem density index was used for clarification because it encompasses the multiple domains subsumed within the PSUD diagnosis. Hence, this summary index reflects the multidimensional nature of PSUD beyond that reflected by the Substance Use scale score alone. Within the normal sample, using 30 on the overall problem density score as the cutoff score, the DUSI correctly classified 95.0% of the normal sample as not qualifying for PSUD. Five percent of normals were misclassified as having PSUD (false positive). The PSUD cases had an 81.0% correct classification rate. Subjects having

2

Substance use Behavior pattern Health status Psychiatric disorder Social competence Family system School adjustment Work adjustment Peer relationships Leisure/recreation Overall problem density index

DUSI Domain

24.6 22.6 21.5 17.8 22.8 20.0 4.8 23.2 23.1 19.1

5.5

M

Table 4. Distributional

13.4 19.4 16.9 18.1 17.3 20.3 17.6 10.8 21.4 18.03 12.9

SD 3.95 0.70 0.98 0.90 1.74 0.85 1.08 4.40 0.80 0.86 1.10

Skew

Normal

characteristics

19.76 0.02 1.16 0.37 4.13 0.20 0.83 27.48 -0.19 0.53 2.37

Kurt 54.4 47.5 36.02 41.6 31.1 43.8 51.9 24.2 57.8 46.6 44.6

M

29.5 21.5 19.5 21.6 21.3 20.6 23.6 21.2 21.1 22.8 16.1

SD -0.16 0.01 0.38 0.19 0.78 0.04 --0.13 0.83 m-O.67 0.04 0.05

Skew

PSUD

-1.13 -0.63 -0.26 -0.50 0.20 -0.29 -0.79 0.27 -0.11 -0.66 -0.39

Kurt

of the normal (n = 278). PSUD (n = 259), and psychiatric

8.0 30.0 25.7 27.0 20.9 29.4 26.7 6.9 30.1 26.9 24.0

M

16.2 19.8 18.5 18.7 19.5 21.1 19.5 12.2 22.1 19.3 13.3

SD

3.12 0.39 0.78 0.61 I .43 0.51 0.64 3.29 0.37 0.69 0.64

Skew

Psychiatric

(n = 309) subjects

Il.71 -0.37 0.46 -0.24 2.24 -0.34 -0.25 14.72 -0.85 0.29 0.89

Kurt

E

C.98) C.93) C.80) (.56) C.32) 1.20) C.18) C.24) C.38)

I.0 1.2 1.6

3.2 9.5 24.5 30. I 17.7 7.1 0.74

-2.0 -1.0 -1.5

-0.5 0.0 +0.5 + I .o +I.5 +2.0 Reliability

5.5 8.3 9.8 8.6 6. I 4.2 0.81

I.6 2.2 3.4

Inf.

f.79) C.68) 1.55) (.43) f.35) C.32) C.34) C.40) C.49)

(SE)

Behavior pattern

2.2 2.7 3.4 3.9 4.4 4.6 0.60

1.3 1.4 I.7

Inf. 1.6 2.1 3.2

(.8X) C.83) C.76) C.68) C.60) C.54) C.50) C.48) C.47) 4.9 7.1 X.8 9.3 x.1 6.3 0.80

Inf. 1.79) 1.68) 1.56) (.45) (.3X) C.34) 1.33) C.35) 1.40)

(SE)

2.5 3.5 5.2 7.2 X.6 7.0 0.67

1.3 I.8 I.5

(.8X) (.X2) 1.74) 1.64) (.53) C.44) 1.37) C.34) (.3X)

(SE)

Social camp.

4.0 5.5 6.6 6.8 6.2 5.1 0.76

I..( 2.0 2.8

Inf. 1.80) C.71) (.60) (JO) C.43) C.39) C.38) t.401 C.44)

(SE)

Family system

1.6 2.3 3.6 5.8 9.3 13.2 14.5 II.5 7.3 0.83

Inf. t.78) C.66) f.53) C.41) C.33) f.28) C.26) C.30) C.37)

(SE) C.98) (.Y6) C.91) C.82) C.67) C.49) C.34) C.28) (.2X)

1.0 I.1 I.2 I.5 2.2 4.2 8.5 13.1 12.5 0.53

Work adjust.

1.4 1.9 3.1 6.5 13.7 17.3 9.x 4.2 2.4 0.X1

Inf.

(.X3) C.73) (57) C.39) t.27) C.24) C.32) C.49) (.64)

(SE)

Peer relation.

of each domain

Inf.

reliability

(SE)

School adjust.

scores on trait scale and marginal

Inf.

density

Psychiatric disorder

of problem

(SE)

Health status

5. Precision

SE = Standard error of measurement: Inf. = information defined as I/\/.=.

(SEJ

Inf.

Trait Scale

Substance use

Table

1.4 I.7 2.1 2.9 4.2 5.9 6.9 6.2 4.5 0.71

Inf.

(.X4) 1.77) 1.69) (.5X) (.4Y) C.41) (.3X) C.40) t.471

(SE)

Leisure & Recreation

13.7 17.4 24.5 39.0 66.0 98.9 lM.6 X6. I 61.0 0.73

(.X6) f.78) (.67) C.50 f.44) C.37) (34) 1.37) (.43)

Overall problem density index

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drug use inventory

155

Table 6. Percentile rank for scores on the DUSI in each domain among normal subjects (N = 278) Percentile

Substance use score Behavior pattern score Health status score Psychiatric disorder score Social competence score Family system score School adjustment score Work adjustment score Peer relationships score Leisure/recreation score Overall problem density index

IO

20

30

40

50

60

70

80

90

0 0 0 0 0 0 0 0 0 0 3

0 5 10 0 0 0 5 0 0 8 5

0 s IO S 7 0 s 0 0 8 7

0 10 IO 6 7 7 5 0 7 8 IO

0 I5 20 IO 14 7 IO 0 7 I7 I2

0 20 20 I5 14 I4 I5 0 14 17 I4

0 25 26 20 21 21 IS 0 21 25 I8

0 35 30 25 21 28 20 0 29 33 22

13 41 40 35 29 36 30 IO 43 42 26

a psychiatric disorder were classified correctly (i.e., non-substance-abuse disorder, with 69% accuracy). As can be seen, the discriminative efficacy of the DUSI was superior in Euro-American compared to Afro-American subjects. No gender differences were evident in Euro-Americans; however, among Afro-Americans the DUSI performed better on normal Afro-American females than males. No gender differences were present among Agro-American PSUD cases, whereas in the psychiatric group, the DUSI had better discriminative power for males compared to females. These results are summarized in Table 7. DISCUSSION

The Drug Use Screening Inventory (DUSI) is a comparatively new screening tool: however, it has been shown in different samples to have good psychometric properties (Tarter, Laird et al., 1992, Tarter et al., in press). In prior research, the average internal reliability across the 10 domains was found to be .74 for males and .78 for females. Test-retest reliability averaged .95 for males and .88 for females. The correlation between the DUSI overall problem density scores and number of substance

Table 7. Classification accuracy of the DUSI Percent correct classification All normals (n = 278) Euro-American male (n = 116) Euro-American female (n = 129) Afro-American male (n = 8) Afro-American female (n = 22) All PSUD (n = 259) Euro-American male (n = 92) Euro-American female (n = 115) Afro-American male (n = 23) Afro-American female (n = 26) All psychiatric (n = 309) Euro-American male (n = 101) Euro-American female (n = 110) Afro-American male (n = 48) Afro-American female (n = 42)

95% 97% 97% 80% 92% 81% 86% 84% 68% 68% 69% 77% 68% 63% 53%

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L. KIRISCI et al

use and overall psychiatric symptoms reported on the K-SADS interview was .61 and 30, respectively. The present study extends these findings by demonstrating that the scores on the DUSI domains have good distributional characteristics. Depending on gender and ethnicity, it is able to classify correctly between 80% and 97% of individuals who are normal and 68% and 86% of adolescents who qualify for a DSM-III-R diagnosis of Psychoactive Substance Use Disorder. Using the overall problem density score, classification of psychiatric cases was less successful, with a 69.0% accuracy across all subgroups. This lower discriminative capacity is due to the fact that several domains of the DUSI measure disturbances which are commonly present in both drug-abusing and psychiatrically disturbed persons. The consequences of drug/alcohol involvement overlap with other psychiatric disorders. For example, impairment in coping capacity does not distinguish adolescents with PSUD from adolescents with other psychiatric disorders (Mezzich et al., in press). In addition, one of the DUSI domains specifically measures psychiatric disorder and, as can be seen in Table 2, over 95% of the PSUD subjects had concomitant psychopathology. In view of these findings, it would appear that the DUSI overall problem density index is not useful for discriminating substance abusers from non-substance-abusing psychiatric cases. Rather, in diagnosed cases of psychiatric disorder, it may be more advisable to employ the Substance Use scale for determining whether there is PSUD as well as for measuring subthreshold levels of drug use involvement and its consequences. It can be seen in Table 4 that the normal and psychiatric cases are more similar to each other than to the PSUD group on the Substance Use scale. Using a problem density score of 27 on the Substance Use domain score correctly classified 92% of the psychiatric patients. Thus, for individuals with psychiatric disorder, the Substance Use scale suffices for screening purposes. The psychometric properties, combined with the multidomain structure of the DUSI, would appear to justify its clinical applicability, at least in the Euro-American population. In this regard, the DUSI can be useful in four applications. First, from the results reported herein, the DUSI is concluded to be an efficient method for screening youth who may need treatment. Toward this end, the DUSI can be administered in group settings and scored either manually or using an optical mark reader system. Second, because the 10 domains are scored for severity according to a common scale, the areas of problem severity can be ranked from highest to lowest. This type of information can be useful for client-treatment matching. Third, by quantifying severity in multiple domains of functioning, the DUSI affords the opportunity to chart treatment progress efficiently. Inasmuch as it takes only about 15 to 20 minutes to complete the questionnaire, it can be administered at regular intervals to monitor the person’s progress toward attaining treatment objectives. Finally, the DUSI may be useful for tracking clients during follow-up aftercare. Specifically, it may be cost-effective to perform a periodic check-up following treatment to document the maintenance of treatment gains and to implement intervention prior to incipient relapse. At this juncture, in lieu of systematic empirical research, these applications should not be viewed as unqualified endorsement; however, emerging findings points to the heuristic value of the DUSI as a research tool as well as for multiple areas of clinical application. Although the psychometric properties of the DUSI appear to warrant its general application, it is important to note that the information solicited from the subject is highly sensitive and could be damaging to the person. Thus, validity remains a major

Adolescent

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157

concern. In response to this concern, a revised version has been developed which includes a Lie scale (DUSI-R) and is currently undergoing psychometric validation. Thus, although not completely eliminating the possibility of invalid reporting, clear instances of deception should be identifiable. However, the point needs to be underscored that the DUSI, like all screening instruments, is useful to the extent that false negative cases are minimized. Corroborative information from breath and urine screening as well as informant reporting should thus not be precluded. REFERENCES American Psychiatric Association. (1987). Diagnostic and siatistical manual ofmental disorders (3rd ed., rev.). Washington, DC: Author. Kirisci, L., Tarter, R. E., & Hsu, Tse-chi. (in press). Fitting a two-parameter logistic item response model to clarify the psychometric properties of the Drug Use Screening Inventory for adolescent alcohol and drug abuse. Alcoholism: Clinical and Experimental Re.yeorc,h. Mezzich, A., Tarter. R., Kirisci, L., Hsieh, Y-C., & Grim, M. (in press). Coping capacity in female adolescent substance abusers. Addictive Behaviors. McClellan, A. T., Luborsky, L., Woody. G., & O’Brien. C. (1980). An improved diagnostic evaluation instrument for substance abuse. The Journal of Nervorts and Menral Disease. 168, 26-33. Orvaschel, H., Puig-Antich, J., Chambers, W., Fabrizzi, M., &Johnson. R. (1982). Retrospective asses+ ment of prepubertal major depression with the Kiddie-SADS-E. Jorrrnul of the American Awdemy of Child Psychiatry,

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