Screening for problem drinking among college freshmen

JOURNAL OF ADOLESCENT HEALTH 1994;15:303-310

ORIGINAL

ARTICLE

MARK J. WERNER, M.D., LYNN S. WALKER, Ph.D., AND JOHN W. GREENE, M.D.

Puryose: This study identifiet? predictors of older adolescents at risk fci problem drinking. Metl~ods: College freshmen (n = 492) completed a questionnaire that addressed drinking patterns, risk factors for problem drinking, the CAGE questions, the Perceived-Benefit-of-Drinking Scale (PBDS), and the Children of Alcoholics Screening Test (CAST). They also responded to questions regarding alcohol-related problems including blackouts; alcohol-related injury, illness, violence, or legal problems; driving under the influence; and missing class. 50% of students were male with a mean age of 17.9 years (SD = 0.5). Results: Higher scores on the CAGE and PBDS, use of tobacco, best friend’s drinking pattern, and younger age at first drinking were associated with higher scores on a quantit;Jlfrequency drinking index and with reports of significantly more alcohol-related problems. Regression models using these variables explained 40% to 51% of the variance in drinking habits and alcoholrelated problems. Conclusion: A composite screening measure had significantly better sensitivity and specificity than either the CAGE or P’BDS alone in identifying older adolescents at high risk for problem drinking. KEY WORDS:

Problem drinking Health problems Screening College students

From the Division of Adolescent Medicine, Vmderbift University, Nashville, ?enrzessee. Address reprirrf requests to: Mark I. Werner, M.D., Division of Adolescenf Medicine, 436 Medical Center South, Vanderbilf University, Nashville, TN 37232. Presented it1 part beforefk Assvciatim for Medical Edwatiorr and Research on Substance Abuse, Washhgton, D.C., November 13,1992. Mamrscript accepfed September 3,1993.

Alcohol consumption by college students has remained remarkably consistent over the past 20 years U-6). A recent study of 14 Massachusetts colleges shows the proportion of frequent heavy drinkers remained unchanged between 1977 and 1989: 30% VS. 31% of men; 13% vs. 34% of women (7). The stability over time of frequent heavy drinking among college studects suggests that social and institutional policies have failed to reduce this problem. Frequent and heavy drinkers place themselves and others at increased risk for a variety of adverse consequences. Problems owing to drinking that arti frequently experienced by college students include: personal injury, accidents, missing class, blackouts, legal difficuities, poorer academic performance, acquaintance rape, sexually transmitted diseases, and unplanned pregnancy 11,3,8-10). A recent survey by the United States Department of Education of students at 96 colleges found that 34% of all students drove while intoxicated on at least one occasion in the past year, 33% got into an argument or fight, 30% missed class, and 23% performed poorly on a test because of drinking (11). In another study almost 30% of college students reported loss of hours of normal functioning while recovering from drinking during the preceding week (1). Screening for problem drinking among college students is complicated by the lack of a standardized and accepted definition of what constitutes problem drinking for adolescents and young adults. Heavy drinking in college may be interpreted as incipient problem drinking, or simply as a manifestation of usual adolescent development in an influential environment (12). Identification of problem drinking among adolescents is further complicated by the realization that heavy drinking is endemic in

0 Society for Adolescent Medicine, 1994 Published by Elsevier Sience Inc., 655 Avenue of the Americas, New York, NY 10010

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WERNER ET AL

this age group, that drinking is a multidimensional behavior, and that most indi.:iduals will temper their drinking during young adulthood and not develop alcoholism (6,12). There are likely to be many adolescents who suffer an adverse health or psychosocial outcome as a result of drinking but who do not meet traditional criteria for alcoholism. Screening for problem drinking is often motivated by an interest in reducing the prevalence of morbidity commonly associated with drinking in this age group. An approach which seeks to identify those students at greatest risk for common alcohol-related problems will define a target population for intervention and allocation of health care resources. As health care providers, we may need to place more emphasis on preventing associated morbidities rather than attempting to identify potential alcoholism among adolescents who drink heaviiy. The ability to develop valid screening instruments for the detection of problem drinking in a concern for college population is an important health professionals. Standard screening measures such as the CAGE and Perceived-Bcnefit-of-Drinking Scale (PBDS) appear to have limitations when used with older adolescents (13-15). The present study was undertaken to better characterize the college student populations identified by these two screening measures, and to identify additional factors that could enhance their usefulness as screening tests for problem drinking among college students.

Methods Sample and Procedure The sample consisted of 492 freshmen students, representing 29% of the 1700 students comprising the entering freshmen class at a private southern university. Participants were 248 female and 244 male students from 16 to 20 years of age (mean 17.9 years, SD = 0.5). Ninety percent of the subjects were white, 3% black, 2% Hispanic, and 4Y0 Asian. Study participants did not differ significantly from the remainder of the freshmen class regarding age, gender, and race. A confidential questionnaire was administered during freshmen orientation programs conducted in each dormitory and directed at alcohol and drug issues. All freshmen students of the university are required to live in campus dormitories. Students attended the orientation programs iii groups of 30-50. Groups were randomly selected for participation from each day and location of programming and included students from each coedu-

JOURNAL OF ADOLESCENT HEALTH Vol. 15, No. 4

cational dormitory. All students present at the selected orientation programs voluntarily participated in this study, which was approved by the Institutiona: Review Board, after an explanation of their rights as participants and the procedures for participation. Administration of questionnaires occurred within the first 3 weeks of the fall semester under the direct supervision of one of the authors (M.J.W.). All study materials and participant responses have remained in the possession and confidence of the same author.

Measures The dependent variables consisted of the scores on two measures of problem drinking modeled after other studies on adolescent alcohol use (13,14,16). The first was a quantity/frequency index computed from scale responses regarding typical quantity and frequency of drinking. By using a four-point response scale students were asked to indicate on how many occasions they drank alcohol in the past 30 days. Response options included: 1, none, one or two occasions; 2, three to five occasions; 3, six to eight occasions; and 4; nin.e or more occasions. Also by using a four-point scale students were asked, on average, how many drinks they had when they drank. A drink was defined as equal to one beer, one wine cooler or glass of wine, or one ounce of liquor in a mixed drink. Response options included: 1, none, 1 or 2 drinks; 2, 3-6 drinks; 3, 7-12 drinks; and 4, more than 12 drinks. A drinking index with values from 1 to 16 was created by multiplying the scale responses to these two questions regarding frequency and quantity of drinking. The second dependent variable was a composite score that reflected the various ways in which adolescents might experience problems related to alcohol use, labeled the alcohol-related problems index. The specific problems were chosen from other studies of college students and represent the spectrum of the most common outcomes Ill). These problems are directly related to drinking alcohol and may contribute to significant risk for early medical or psychosocial consequences. Students were asked to indicate whether the following had ever happened to them: “Have you ever become physically violent when you were under the influence of alcohol? Have you ever suffered an injury or medical illness because of drinking? Have you ever had legal difficulties as a result of drinking? Have you ever awakened the morning afte: some drinking and found that you could not remember part of the evening?

June 1994

Have you ever skipped or missed class after a night of drinking? In the past 12 months have you driven a motor vehicle under the influence of alcohol?” For each student, positive responses to these questions were summed to create an alcohol-related problems index correlated highly with each other: 0.68 for both genders and all students combined (p < .Ol). The remainder of the questionnaire included selfreport of frequency of alcohol and tobacco use; the CAGE questions (see explanation below); the Perceived-Benefit-of-Drinking Scale (PBDS); self-report of family and peer group drinking patterns; the Children of Alcoholics Screening Test (CAST) and demographic information. Students were asked to describe the drinking habits of their best friend as either: nondrinker, a light, moderate, or heavy social or problem drinker. Tobacco use was assessed with questions about both cigarette and chewing tobacco use. Students were considered current tobacco users if they reported any use of tobacco products in the past month. Students were asked to indicate the age at which they first drank alcohol and if they felt a member of their family was a problem drinker or alcoholic. The CAGE questions have proven useful in screening for alcoholism (17). The questions focus on cutting down on drinking, nlznoyunce at criticism by others about drinking, ,@ty feelings about drinking or something done while drinking, and the use of an eye-opener. The questions may be selfadministered. Although a positive response to the CAGE questions is not diagnostic of alcoholism, a score of 2 or greater is highly suspicious and warrants further evaluation (17). The PBDS is a brief clinical screening instrument useful in identifying adolescents who may be alcohol abusers. It consists of endorsing as true or false each of the following five statements: drinking helps me forget, drinking helps me be friendly, drinking helps me feel good about myself, drinking helps me relax, and drinking helps me be friends with others who drink. Reliability and validity of the PBDS are well established (18,191. It assesses the benefits an adolescent attributes to drinking, and is not dependent upon direct information about drinking patterns or negative consequences resulting from drinking. A full evaluation of potential drinking problems is strongly recommended for those scoring 3 or greater (18,191. The CAST is a valid, reliable, and easily administered measure of experiences with parental alcohol misuse. It consists of 30 questions with “yes” answers tabulated to yield a final score. A score of 6 or

SCREENINGFORPROBLEMDRINKING

Table 1.Correlation of Occurrence of Negative

305

Events

with Level of Drinking Mean drinking index Negative event

Variable absent

Variable present

3.2 4.6 4.6 4.6 4.9

8.0

3.7

Blackouts Violence Injury Missed class Legal difficulties Driving under the influence

greater suggests significant ental alcohol misuse (20).

Statistical

t value

I’

9.8 8.6 10.2 9.5

-13.98 -10.12 -7.17 -10.53 -7.50

~0.001
8.4

-12.56

~0.001

experiences

with par-

Analysis

Chi-square analyses were performed to test differences between male and female students regarding report of family members with problem drinking: CAST, CAGE, and PBDS scores; specific health problems; and both drinking and alcohol-related problems index scores. Spearman correlation coefficients were calculated between age of first drinking; best friend’s drinking pattern; report of family members with problem drinking; CAST, CAGE, and PBDS scores; and tobacco use and the two dependent indices. To support the validity of using reports of alcohol-related problems as an indicator of students at risk for problem drinking, Student’s f-tests were performed comparing mean drinking index scores when a particular problem was reported to the mean when a problem was not reported (Table 1). Hierarchical multiple regression analysis was used to identify those variables that, in combination with the CAGE and PBDS, explained the largest variance in drinking and alcohol-related problems index scores.

Results Descriptive

Data

The percentages of students affected by problems frequently associated with alcohol use are shown in Table 2. Whereas 43% of the students had not been affected by any of these problems, 36% had been affected by two or more. The most common problems experienced included blackouts (43%), sustaining an alcohol-related injury or illness (15%), becoming violent as a result of drinking (14%), and missing class as a result of drinking (13%). Ten

306

JOURNAL OF ADOLESCENT HEALTH Vol. 15, No.

WERNER ET AL

Table 2. Perceniage of Students Reporting Commonly Associated with Alcohol Use

Blackouts Driving under the influence Alcohol-related injury/illness Alcohol-related violenceR Missed class because of drinking 4Lcohol-related legal problems Alcohol-related problems index scores 0 1 2 3 4 25

Table 3. Characteristics of Students Scores on the CAGE, PBDS,or Both

Problems

All students 01 = 492)

Males Oz= 2.44)

Females 01 = 248)

43

49

39

34

41

27

15

i6

14

14

22

7

13

17

9

10

14

7

43 21 ‘I5 10 7 4

37 19 17 II 10 6

50 22 13 9 5 1

aDifference between males and females significant (based on x2), 1’ < 0.001.

percent of Ihe students had driven a car while under the influence of alcohol six or more times in the last year. Alcohol-related problems index scores were not significantly different between male and female students. Drinking frequency and quantity were significantly greater in males than in females (p’s < 0.001). The mean drinking index score was 6.7 (SD = 4.8) for males and 4.0 (SD = 3.4) for females (p < 0.001). The alcohol-related problems addressed in this study reflect the spectrum of possible consequences associated with drinking. Although they are quite different in their potential implications for youth, it is difficult to realistically weigh their potential impact upon a particular student. Forty-four percent of Ihe subjects, including 40% of males and 48% of females (p > 0.05), indicated that there was a family member with problem drinking or alcoholism. CAST scores equal to or above 6, indicating a significant likelihood of experiencing consequences from parental alcohol misuse, were obtained by 12% of the subjects; 9% of males and 14% of females (p < 0.03). CAGE scores 22, indicating high risk for alcoholism, were obtained by 19.5% of the subjects, including 26% of males and 13% of females (p < 0.003). Similarly, PBDS scores of 23, indicating high risk for problem drinking, were obtained by 26% (24% of males and 28% of females, p > 0.05). Twenty-two

All students (II = 492) Age (yrs) Gender (% male) Heavy drinking (%Y Frequent drinking f%jb Drinking index (mean) Cigarette use (%) Chewing tobacco use (%) Heavy-drinking friends (%) CAST score > 6 (%) Family problemdrinking (%) Alcohol problems index (mean) Blackouts (%) Violent while drinking (%) Injury while drinking (%) Legal difficulties (‘70) Missing class (%I Driving under influence (%)

4

With High-Risk

CAGE + only (n = 48)

PBDS + only (n = 79)

CAGE/ PBDS + (n = 48)

17.9 49 46 24 4.5 16

17.9 75 56 46 3.1 15

17.9 34 54 23 5.9 20

17.9 58 63 44 F.8 44

12

25

11

17

16 17.

25 10

18 14

32 13

44

62

58

49

1.3 43

2.4 67

1.4 54

2.9 83

14

38

14

35

15 10 13

29 23 23

14 9 17

44 27 33

34

56

35

71

aHeavy drinking defined as averaging more than nine drinks per occasion. bFrequent drinking defined as averaging mwe than seven drinking episodes per month.

percent first drank while under 13 years of age, and 53% while 14 years or younger. The CAGE and PBDS appear to identify somewhat different populations of at-risk students. Of the 175 students (35%) with high risk scores on either the CAGE (n = 96) or PBDS (n = 1271, only 48 (27%) were positive on both. Table 3 shows the characteristics of students with high-risk scores on the CAGE versus the PBDS or both. Relative to the PBDS, the CAGE appears to be more likely lo identify at-risk students within this sample who are male, drink more frequently, and have sustained more alcohol-related problems. In contrast, the PBDS appears to identify a larger number of students, particularly females, whose drinking frequency and occurrence of alcohol-related problems is somewhat less. Both the drinking and alcohol-related problems indices were correlated with CAGE scores, PBDS scores, age of first drinking, best friend’s drinking pattern, and tobacco use. They were not correlated with CAST scores or reports of family drinking

SCREENING FOR PROBLEM DRINKING

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Table 4. Correlation and Alcohol-Related

Coefficients (r) Between Drinking Problems Indices and Independent

Variablesa Drinking index All students

Males Females

Age of first 0.30 drinking 0.36 Friend’s drinking 0.35 pattern 0.34 Family drinking 0.01 problem@ 0.06 0.00 CAST scores! 0.02 0.45 CAGE scores 0.41 0.36 PBDS scores 0.44 0.48 Tobacco use 0.48 “AlI I’ values are significant indicated. bAll correlations

Males Females

0.44

0.34

0.34

0.37

0.23

0.34

0.38

0.24

0.07 0.04 0.32 0.53 0.45 at

p

0.05 0.07 0.47 0.44 0.46 5 0.001

0.00 0.06 0.51 0.38 0.49 except

0.09 0.08 0.39 0.50 0.41 where

nonsignificant.

problems (Table 4). These correlations were significant for both male and female students.

Prediction

of Problem

Table 5. Mierarchical Multiple Regression Analysis Predicting Scores on the Drinking and Alcohol-Related Problems Indices

Alcohol-related problems index All students

307

Beta Male students CAGE scores PBDS scores Tobacco use Friend’s

Drinking

Health problems

index

index

R2 change

p

RZ Beta change

p

-

0.450 0.175 0.379

0.20 0.03 0.14

< 0.0001 0.518 0.005 0.177 < 0.0001 0.380

0.27 0.03 0.13

< 0.0001 < 0.003 < 0.0001

drinking Age first

0.238

0.05

< 0.0001 0.221

0.05

< 0.0001

drinking Total Female students CAGE scores PBDS scores Tobacco ust Age first drinking Friend’s drinking Total

0.169

0.03 0.45”

< 0.001 0.178 ==I0.0001

0.03 0.51b

< 0.0001 i 0.0001

0.281 0.342 0.362

0.08 0.10 0.12

< 0.0001 0.452 < 0.0001 0.260 < 0.0001 0.244

0.20 0.06 0.05

< 0.0001 < 0.0001 c 0.0001

0.305

8.08

< 0.0001 0.241

0.05

<’ 0.0001

0.182

0.03 0.41c

< 0.0001 0.180 < 0.0001

0.04 0.40”

< 0.0001 < 0.0001

OF = 36.50; RZ = bF = 47.06; R2 = cF = 33.61; R2 = dF = 31.63; R* =

0.45; 0.51; 0.41; 0.40;

adjusted R* = 0.43; p < adjusted R2 = 0.49; p < adjusted R2 = 0.40; p < adjusted R2 = 0.39; I_’<

0.0001. 0.0001. 0.0001. 0.0001.

Drinking

A hierarchical multiple regression analysis was performed to identify those variables that accounted for significant variation in drinking and alcohol-related problems. CAGE scores were entered into the model first followed by PBDS scores since these represent standardized screening measures. Because the CAGE is more established, entering it into the hierarchical analysis first allowed for the evaluation of improved explanation of additional variance by other factors. The PBDS was entered second because of its conceptually different approach. Tobacco use, best friend’s drinking pattern, age of first drinking, CAST scores, and reports of family drinking problems were each entered in turn to see which explained the most additional variance. CAGE scores, PBDS scores, tobacco use, best friend’s drinking pattern, and age of first drinking were significant predictors of both drinking and alcohol-related problems index scores (Table 5). Together these variables explained 41% to 45% of the variance in drinking index scores and 40% to 51% of variance of the alcohol-related problems index (Table 5). Regression models were similar for male and female students with the exception that age of first drinking entered the model ahead of friend’s drinking pattern for female students (Table 5).

Based on these results, composite screening measures for female and male students were created and compared to CAGE and PBDS as predictors of problem drinking; particularly of those students already reporting alcohol-related problems (Table 6). In a manner similar to other studies on college student and adolescent problem drinking (13,14,16), problem drinkers were defined as individuals in the Table 6. Test Characteristics of Alcohol Questionnaires Screening for Problem Drinking

Male students CAGE PBDS

Composite

screen”

Female students CAGE PBDS Composite screena

in

Score

Sensitivity f%)

Specificity (%)

Positive predictive value (RI

22

42

61

78

23

32

56

67

2 2 23

95 83

91 79

65 67

22 r3 2 2 > 3

25 48 90 83

70 75 91 88

69 60 53 58

computed by adding one point for each “Composite scr’ CAGE items, PBDS items, age of first drinkpositive response ing < 15 years, . .,mg tobacco in the past month, and describing best friend as heavy drinker.

308

WERKER ET AL

top quartile in relation to their same sex peers on drinking index scores (i.e., top quartile based on quantity and frequency) or those who reported sustaining two or more alcohol-related problems. The composite screening measure was computed by summing one point for each positive response to CAGE items, PBDS items, using tobacco in the last month, drinking before age of 15, and describing one’s best friend as a heavy social or problem drinker. Test characteristics of this ccmposite screen were determined using both two and three positive responses as the cutoff score. Use of this combination of measures significantly increased sensitivity and specificity beyond that obtained with the CAGE or PBDS alone for problem drinking as here defined (Table 6).

The ability to develop

valid screening instruments for the detection of problem drinking in a college population is an important concern for health professionals. Approaches to screening for alcohol abuse have traditionally relied upon assessment of drinking frequency, quantity, and psychosocial consequences (21,22). The CAGE questionnaire, a screening instrument commonly used in health care settings (171, has been used with college students but may not be an adequate screening instrument for problem drinking among older adolescents when used alone (13,141. Heck (14) found that the CAGE together with the student’s likelihood of choosing nonalcoholic beverages at social events, history of driving under the influence of alcohol, and having started regular use of alcohol before college were very useful in screening for problem drinking. Considerable evidence suggests that individuals’ expectations regarding the potential outcomes associated with drinking alcohol are influential in the initiation and maintenance of drinking (23). These outcome expectancies have been associated with differing patterns of alcohol use by adolescents and with the transition to problem drinking (16,24,25). An alternative approach to screening for alcohol abuse utilizes the adolescent’s perceptions of why he or she drinks. The PBDS probes the adolescent’s view regarding the specific reinforcements received from drinking (18,19). The more benefits an adolescent attributes to drinking, the more likely he or she is to drink. PBDS scores are significantly higher for adolescents who . ng drunk more often, who claim to have had a problem with drinking,

JOURNAL OF ADOLESCENT HEALTH Vol. 15, No. 4

and who have reported trouble stemming from drinking. Although the PBDS has not been used extensively with college students, it has been shown to correlate with frequent binge drinking among college freshmen (261. In a study of pregnant innercity adolescents, the PBDS did not differentiate between those using and not using alcohol (15). Early alcohol use, alcohol use by family members, pe\?r influence, and pressure to be accepted by a ‘.‘roup influence alcohol consumption (27-29). Adocscents most often cite social factors as their reasons for using alcohol and other drugs (6). Members of fraternal organizations are more likely to drink and to incur alcohol-related problems (301. Robinson et al. (31) found that level of substance use, including alcohol, among adolescents was correlated with predicted substance use under social pressure, cigarette smoking, perceived friends’ drinking, and substance use to cope with stress. Our findings support previous studies suggesting that the CAGE and PBDS appear to have limitations when used with older adolescents (13-15). Results of this study suggest that an approach which expands upon a combination of the CAGE and PBDS to include tobacco use, age of first drinking, and peer drinking patterns can be useful in identifying older adolescents at high risk for problem drinking. These variable explained 40% to 51% of the variance in indices of quantity and frequency of drinking and the prevalence of specific alcohol-related problems for both male and female students. The CAGE may be most useful in identifying heavier drinking students who have sustained more deeply alcohol-related problems, particularly among males. The PBDS appears to be a valuable addition to the CAGE for identifying more moderate problem drinkers, particularly among female students. The modest overlap of the CAGE and PBDS is similar to that obtained one year earlier at the same university when 11% were in the high risk range on both the CAGE and the PBDS (26). The prominent role of tobacco use in identifying high risk students should be noted. This combination of 12 questions remains brief and can be easily administered in a primary health care setting in under 5 minutes. Pragmatically, screening efforts could start with the CAGE items and progress to include the PBDS items and subsequently address tobacco use, friend’s drinking, and age of first drinking. At any point where two positive responses have been obtained, then that student can be considered to be at high risk and the focus can turn to a more detailed assessment.

SCREENING FOR PROBLEM DRINKING

June 1994

College students are frequently affected by alcohol-related problems. This study focused upon health problems directly related to drinking alcohol and likely to be associated with significant risk for morbidity and mortality. The issues addressed take a broad view of health, and include items reflecting potential risk for medical, legal, or academic problems as a result of drinking. The occurrence of these selected alcohol-related problems were used to help define the target population, that at risk for problem drinking. Among these students, 57% had had one or more of the health problems surveyed, and 36% had been affected by twn or more. Blackouts, a symptom commonly used as an indication of alcohol abuse, were experienced by 43% of the students. Sustaining alcohol-related injuries or illness, becoming vinlent while drinking, missing class because of drinking, and driving a car while under the influence of alcohol were also common in this sample. Interestingly, missing class because of drinking, potentially the most benign, was actually associated with the highest mean drinking index scores. This suggests that many students who use alcohol do not actually miss class because of their drinking. Despite the greater frequency of heavy drinking among male students, there was no significant difference in alcohol-related problems index scores between males and females. Ii is important to remember that these were entering college freshmen, and as such their reported probiems occurred prior to entering college. Screening avd prevention efforts during their middle and late adolescence may have helped prevent some of these problems. Family history of problem drinking or alcoholism, including CAST scores, was not associated with students’ likelihood of drinking more heavily or having alcohol-related health problems. This may in part reflect that the study did not focus on the specific diagnosis or problem ol alcoholism. Based on CAST scores, the prevalence of a family history of alcoholism among our student population is similar to previous reports (32,331. Although no standard for problem drinking exists, there is general agreement that alcohol use becomes problematic when it becomes injurious to the individual or to others. Both frequency of intoxication and the occurrence of injurious consequences are predictive of short- and long-term negative effects of alcohol use (34). There are likely to be many adolescents who suffer an adverse health or psychosocial outcome as a result of drinking but who are not alcoholic. Screening approaches should attempt to identify students who are at risk for alcohol-

309

related problems, and not rely solely on traditional alcoholism screening tools. The prevention of alcohol-related injury or premature death in motor vehicle or other accidents, sexual and aggressive behavior, and academic failure are important goals for adolescents. As such, screening efforts are needed which seek to identify adolescents whose use of alcohol places them at increased risk for these morbidities. This study relied upon students’ retrospective self-report of health problems and did not attempt to temporally link drinking patterns with health problems. The predictive factors identified by this study will need to be prospectively evaluated for their longitudinal predictive value and applied to a more comprehensive problem drinking assessment. The sample in this study was overwhelmingly (90%) Caucasian from a selective southern university, limiting generalizability to other adolescent popula-. tions. Given the complexity of adolescent drinking behavior, it seems reasonable to use a multidimensional approach to screening. This study supports the value of these screening efforts and highlights the relationship of alcohol use to common adolescent morbidities. This study was supported in part by a grant from the National Institute on Alcohol Abuse and Alcoholism, and the National Institute of Drug Abuse, TO1 AAO7515.

References 1. Meihnan I’W, Stone JE, Gaylor MS, et al. Alcohol consumption by college undergraduates: current use and IO-year trends. J Stud Alcohol 3990;51:389-95. 2. Pope HG, Ionescu-Pioggia M, Aixley HG, et al. Drug use and life style among college undergraduates in 1989: a comparison with 1969 and 1978. Am J Psychiatry 1990;147:9YX-1001.

7 Engs RC, IHanson DJ. University students’ drinking L

patterns and problems: examining the effects of raising the purchase age. Public Hea1t.h Rep 1988;103:667-73.

4. Saltz .I, Elandt D. College student drinking 1985. Contemp Drug Prob 1986;13:117-59.

studies

1976-

5. O’Hare TM. Drinking in college: consumption patterns, problems, sex differences, and legal drinking age. J Stud Alcohol 199fl;51:536-41. 6. Johnston LD, O’Malley PM, Bachlnan JG. Drug Use Among Anierican High School Seniors, College Students, and Young Adults, 1975-1990. II. College Students and Young Adults. RockvilIe, Md: US Dept of Health and Human Services, 1991. 7. Wechsler H, Isaac N. Ilinge drinkers leges. JAMA 1992;267:2929-31.

at Massachusetts

cd-

a. Berkowitz AD, Perkins HW. Problem drinking among college students. J Am Coil Health 1986;35:21-8.

310

JOURNAL OF ADOLESCENT HEALTH Vol. 15, No. 4

WERNER ET AL

S, Globetti G, Stem J, et al. The quantity 22. Haworth-Hoeppner and frequency of drinking among undergraduates at a southem university. Int J Addict 1989;24:829-57.

9. Nicholi AM. Characteristics of college students who use psychoactive drugs for nonmedical reasons. J Am Co!1 Health 1985;33:189-92. 10. Gliksman L. Consequences of alcohol use: behavior changes and problems during the first year of university. Int J Addict !98S;u:1281-95. 11. Presley CA, Meilman PW. Alcohol and Drttgs on American College Campuses: A Report to College Presidents. Washington, DC Drug Prevention in Higher Edrtcation Program, Fund for the Improvement of Postsecondary Education, US Department of ’ ‘,lcation, July 1992.

24. Brown SA, Christiansen BA, Goldman MS. The alcohol expectancy questionnaire: an instrument for the assessment of adolescent and adult alcohol expectancies. J Stud Alcohol 1987;48:483-91.

12. Scheller G, Corn. .rg ES, Clay M. College students hol: an exploration of observations and opinions. ‘Drug Educ. 1979;24:30-41.

25. Brown SA, Goldman MS, Christiansen BA. Do alcohol expectancies mediate drinking patterns of adults? J Consult Clin Psycho1 1985;53:512-9.

and alcoJ Alcohol

13. Smith DS, Collins M, Kreisberg JP, et al. Screening for problem drinking in college freshmen. J Am Co11 Health 1987;36:89-94. 14. Heck EJ, Developing a screening questionnaire for problem drinking in college students. J Am Coil Health 1991;39:22731. 15. Kokotailo PK, Adger H, Duggan AK, et al. Cigarette, alcohol, and other drug use by school-age pregnant adolescents: prevalence, detection, and associated risk factors. Pediatrics 1992;90:328-34. 16. Christiansen BA, Smith CT, Roehling PV, et al. Using alcohol expectancies to predict adolescent drinking behavior after one year. J Consult Clin Psycho1 1989;57:93-9. 17. Ewing JE. Detecting alcoholism: JAMA 1984;252:1905-7.

The CAGE questionnaire.

MS, Brown SA, Christiansen BA. Expectancy 23. Goldman theory: thinking about drinking. In: Blane HT, Leonard KE, Eds. Psychological Theories of Drinking and Alcoholism. New York: Guilford Press, 19??, 181-226.

26. Werner MJ, Greene JW. Problem drinking freshmen. J Adolcsc Health 1992;13:487-92.

among

college

27. Newcomb MD, Maddahian E, Bentler PM. Risk factors for drug use among adolescents; Concurrent and longitudinal analyses. Am J Public Health 1986;76:525-31. 28. Hanson DJ. Trends in drinking and behaviors students. J Alcohol Drug Educ 1974;19:6-14. DI. Children 29. Macdonald 1986;140:7504.

of alcoholics.

among college

Am J Dis Child

30. Canterbury RJ, Gressard CF, Vieweg WVR, et al. Psychosocial inventory among first-year college students by patterns of alcohol use. Adv Alcohol Subst Abuse 1990;9:1-11. on 31. Robinson TN, Killen JD, Taylor B, et al. Perspectives adolescent substance use: a defined population study. JAMA 1987;258:2072-6.

18. Petchers MK, Singer MI. Perceived-Benefit-of-Drinking Scale: approach to screening for adolescent alcohol abuse. J Pediatr. 1987;110:997-81.

32. Schoenborn CA. Exposure to alcohohsm in the family: United States, 1988. Hyattsville, Md: National Center for Health Statistics, 1991; Advance Data No. 205.

19. Petchers MK, Singer MI, .r\ngelotta JW, et al. Revalidation and expansion of an adolescent substance abuse screening measure. J Dev Behav Pediatr. 1988;9:25-9.

33. Russell M, Henderson C, Blume SB. Children of Alcoholics: a Review of the Literature. New York: Children of Alcoholics Foundation, 1984.

20. Jones J. Preliminary Test Manual: The Children of Alcoholics Screening Test. Chicago, 111:Family Recovery Press, 1982.

34. Polich JM, Orvis BR. Alcohol Problems: Patterns and Prevalence in the U.S. Air Force. Washington, DC: U.S. Government Printing Office R-2308, 1979.

21. Temple M. Trends in collegiate drinking in California, 1984. J Stud .AlcohoI 1986;47:274-82.

1979-