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The International Journal of the Addictions, 14(6), 797-808, 1979
Drug Use in College Students: A Test of Sociodemographic and Reference Group Models of Explanation Lakshmi Murty Department of Sociology Rutgen University New Brunswick, New Jersey 08903
Abstract
This study examined the importance of reference group variables in the understanding of drug use in college students. Other studies have investigated the role of peer orientation, and this study further elaborates on the issue by specifically looking into parents and peers as reference groups for the students. This study supports the importance of reference group variables in understanding the students’ use of marijuana and/or hashish. In addition, it shows that the sociodemographic variables cannot predict drug use behavior as well as the reference group variables can. This study attempts to investigate the importance of reference group variables compared to the sociodemographic ones in understanding and 797 Copyright @ 1979 by Marcel Dekker, Inc. All Rights Reserved. Neither this work nor any part may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, microfilming, and recording, or by any information storage and retrieval system, without permission in writing from the publisher.
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798
MURTY
predicting the drug use of college students. Most of the literature on drug use abounds with the sociodemographic correlates of drug users and nonusers. Socioeconomic status is a key variable that has consistently correlated with drug use. Most of the studies indicate that it is the students from middle- and upper-middle-classes that most heavily use marijuana. However, for Kohn and Mercer (1971) this relationship did not reach the conventional level of significance. Simmons and Trout (1967)observe that drug users are often scholarship holders, social science majors, Jewish, and from middle-class intact urban or suburban homes. Similarly, Blum (1969) observes that students with drug experience are generally wealthier and older upper-classmen, irreligious, in opposition to their parents, politically left-wing and active, usually in arts and humanities or social sciences, undergoing ideological shifts, and generally more pessimistic about the future. Ahmed (1968) finds unconventionality in religious orientations in his sample of drug users. Suchman (1968) and Billings and Ferraro (1974) similarly note that drug users tend to be either atheists or have exotic or unusual religious preferences such as Zen Buddhism. Generally these studies have been descriptive and correlative. Very few studies have used theoretical propositions and tested them in the context of drug use. One such study is by Winslow (1974). Here an attempt is made to test two different and theoretically meaningful hypotheses, one stemming from diffusion and the other stemming from subcultures. The present study tests the general hypothesis that students will be influenced by their reference orientations in the use or nonuse of marijuana or hashish. In criticizing previous studies on drug use, Spevack and Pihl (1976, p. 757) single out one as the most important drawback “ . . . the interpretation of results of some questionnaires is confounded by the fact that many demographic differences (sex, age, social class) have been found to mark DUs and NUS and these differences, rather than the differential use of drugs, may explain many of the other behavioral and attitudinal differences noted between groups.” This study attempts to not only point to the importance of reference group variables in the understanding of drug use phenomenon, but also tries to compare their regression equations to those of the various demographic factors known to influence drug use behavior, in an effort to empirically document the relative role played by each of these sets of variables. As the vast amount of literature on drug use indicates, it is almost always a close peer that socializes one into the expectation of a pleasurable experience through the use of drugs. Along with this expectation goes the
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DRUG USE IN COLLEGE STUDENTS
799
notion of “growing up” and ascertaining independence from parents and a concomitant search for identity with peers. Becker (1953), Blum (1969), Tec (1970), Winslow (1974), Spevack and Pihl (1976), and many others have documented the critical role played by the peers in one’s use of drugs. In addition, Tec’s study of suburban teenagers documents the importance of parents as role models and the quality of life at home. This bespeaks the interactional and situational nature of the use of drugs and the salience of the concept of reference groups. Yet, this concept is not employed in the studies of drug use. This study uses the research on peer and parent influences on drug use patterns as a take-off point and brings the concept of reference groups directly into the design. The questions of importance to this study are: (1) the influence of parents as a reference group on the student’s use of pot/hash; (2) the quality of interaction between students and the reference group of parents and the influence this has on the use of pot/hash by students; (3) the influence of (a) best friends, and (b) other friends and acquaintances as reference groups on the use or nonuse of pot/hash by the students; and (4) the quality of interaction between students and their reference group of best friends or other friends and the influence this has on the use of pot/hash by the respondents. Following Shibutani (1955), a reference group is defined here as a . . . group whose perspective constitutes the frame of reference for the actor.” This theoretical definition has had tautological problems when it has been operationally defined for research purposes. To avoid such problems, the present study arrived at a novel operational definition of reference groups by combining it with the concept of dissonance. If indeed an individual’s attitudes and conduct are shaped by the groups to whom one orients one’s self, then it is logical to assume that when the individual finds out that in fact his/her norms and values are at odds with, or different from, the groups to whom he/she is attributing these norms, this new revelation should create a sense of cognitive dissonance. Whereas, if these persons were not his/her referent others, such revelations should not matter to the individual. With this rationale, a question was constructed to tap whether parents, best friends, or other friends were their reference group. This question was asked for each of the three semesters the student spent at the university. The aim was to see if there were any shifts in reference orientation (most likely is the shift from parents to peers) during these three semesters. The dependent variable drug use is measured by the following question: At the beginning of your first semester freshman year (second semester freshman yearlfirst semester sophomore year), where did you “
MURTY
800
stand on pot or hash? (a) Was against it and did not smoke, (b) Was curious but did not smoke, (c) Favored using it and experimented with it a few times, (d) Smoked occasionally, (e) Smoked regularly.
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RESEARCH DESIGN This study is based on second semester sophomores at the University of Connecticut. During the first week of 1974 spring semester, questionnaires were given out to students enrolled in randomly selected courses at the University of Connecticut main campus. Only those classes were included in the pool for sample selection that had a majority of second semester sophomores. This procedure of selecting students with one standard classification and not all was found necessary so as to guard the results from being confounded by comparing different cohorts of students, their differential ability to recall previous experiences regarding drug use influences, etc. The final sample size is 71 1 second semester sophomores. This is approximately a third of the student population with that classification enrolled at the university during the spring of 1974. Since stepwise multiple regression analysis provides a “near-optimum” solution to the problem of predicting the dependent variable from a series of independent variables, this method was found to be appropriate and efficient for the purposes of examining the relative importance of reference group and sociodemographic explanations of drug use.
DATA ANALYSIS Table 1 identifies the regression equation for the sociodemographic variables with the first semester drug use patterns. Of the total variance explained by all the sociodemographic variables (16.6%), a significant portion is explained (12.4%) by the religiosity information alone. The variables of religious preference and father’s occupation are the next most important predictors of student drug use in that order. Sex, age, grade point average, major field of study, ethnicity, parental social class identification, parents’ income, and father’s education have contributed less than one-half of 1% to the variance each, in addition to the first three variables. This is an interesting finding to note, particularly because parental economic status, parental social class identification, major field of study, and grade point average have generally been shown to have significant association with drug use variables. These results throw some doubt on, if not fiecessarily disprove, the
801
DRUG USE IN COLLEGE STUDENTS
Table 1 Multiple Regression Analysis of Sociodernographic Variables with Student Drug Jse in the First Semester
Sociodemographic variables
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~~~
Multiple r
Variance explained (rZ)
change
.35224 .37284 .39107 .39438 .39763 .39994 .40191 .40372 .40479 .40651 .40729
,12407 .13901 .15294 .15553 .15811 .15995 .16153 .16299 .16386 .I6525 .16588
.01494 .01393 .00260 .00257 @I184 .00159 .00146 .00086 .00139 .00063
r2
~
1, Religiosity 2. Religion 3. Father’s occupation 4. Sex 5. Age 6. Grade point average 7, Major field of study 8. Ethnicity 9. Parental SES identification 10. Parental economic status 11. Father’s education
.
importance attached to the demographic variables in the drug use literature available thus far. One of the problems is that most of these studies have not gone beyond correlation analysis to see what the observed correlation is actually worth in terms of its relative effectiveness in predicting the dependent variable. The only other study that utilized the method of multiple regression analysis (Cave, 1972) has also found that sociodemographic variables explain very little of variation in drug use patterns. This gives us confidence in the overall explanatory power of sociodemographic variables found in my research. Stepwise multiple regression equations for the second and third semester drug use patterns (Tables 2 and 3, respectively) are quite similar to the first with some minor shifts in the order of importance of the variables included in the equation. In the second semester, father’s occupation has dropped in its explanatory power of drug use patterns considerably but father’s education has taken its place. Mother’s occupation and education are not important in any of the three semesters. One of the reasons for this lack of importance is possibly that there is not much variation in this variable. Most of the students have stated that their mothers are housewives. A real test of the role of mother’s occupation would probably come from a sample that has variation in her occupational status. Father’s occupation and education have dropped to a very
MURTY
802
Table 2
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Multiple Regression Analysis of Sociodemographic Variables with Student Drug Use in the Second Semester
Sociodemographic variables
Multiple r
Religiosity Religion Father’s education Sex 5. Grade point average 6. Parental SES identification 7. Parental economic status 8. Major field of study 9. Age 10. Father’s occupation 11. Ethnicity 12. Mother’s occupation 13. Mother’s education
.33749 ,35638 .36773 .37846 .38508 .39005 -39489 .39902 .a278 .40451 .40498 .40533
1. 2. 3. 4.
.a560
Variance explained (r2)
rz change
.I1390 .12701 .13523 .I4323 .14829 .15214 .15593 .15922 .16223 .16363 .I6401 .16430 .16451
.01311 .00822 .00801 .00506 .00385 .00379 .00329 .00301 .00140 .00038 .00029 .00021
insignificant status in the third semester. On the other hand, major field of study and parental economic status have gained additional explanatory power relative to the first two semesters. However, these are only minor Table 3 Multiple Regression Analysis of Sociodemographic Variables with Student Drug Use in the Third Semester Variance explained
Sociodemographic variables
Multiple r
(r2)
rz change
Religiosity Religion Major field of study Parental economic status 5. Sex 6. Parental SES identification 7. Age 8. Grade point average 9. Ethnicity 10. Father’s education 11. Mother’s education 12. Father’s occupation
.35167 .35956 .36560 .37057 .37594 .38061 .38466 .38706 .38829 ,38899 .39031 .39034
.12367 .12928 .13367 .13732 .14133 .14486 .14797 .14982 .15077 .15131 .15234 .15237
.00561 .0m38 .00366 .oO401 .00353 .00310 .00185 .00095 .m54 .00103 . m 2
1. 2. 3. 4.
803
DRUG USE IN COLLEGE STUDENTS
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Table 4 Multiple Regression Analysis of Reference Group Variables with Student Drug Use in the First Semester
Reference group variables
Multiple r
Variance explained (r2)
1. Best friends’ drug use stand 2. Parents as a reference group 3. Other friends’ drug use stand 4. Parental drug use stand 5. Interaction with parents 6. Other friends as a reference group 7. Best friends as a reference group 8. Interaction with best friends 9. Interaction with other friends
.58328 .60550 .62080 .63028 .63477 .63896 .64030 .64034 .64035
.34021 .36663 .38539 .39725 .40293 .40827 .40998 .41003 .41005
rz change
,
.02642 .01876 .01186 .MI568 ,00533 .00171
.oooo5 .oooo2
variations and the pattern of relationships of sociodemographic variables to drug use stand have generally remained the same. Tables 4, 5, and 6 portray the variance explained by the reference group variables over the same three-semester period. The overall explanatory power of reference group variables for the first semester drug use is 41.0%, which is considerably higher than that recorded for the sociodemographic variables (16.6%). The overwhelming difference clearly supports the major thesis of this article-drug use patterns are influenced by (or, the variation in drug use patterns is more accurately predicted by) Table 5 Multiple Regression Analysis of Reference Group Variables with Student Drug Use in the Second Semester
r
Variance explained (r2>
rz change
.63606 .65165 .65970 .66306 .66626 .66764 .66828 .66849 .66853
.40458 .42464 .43521 .43965 .44391 .44574 .44660 .44688 .44694
.02006 .01057 .00444 .00426 .00184 -00086 .00027 oooO6
Multiple Reference group variables ~~
~
1. 2. 3. 4. 5. 6. 7. 8. 9.
~
~~
Best friends’ drug use stand Parents as a reference group Other friends’ drug use stand Parental drug use stand Interaction with parents Best friends as a reference group Other friends as a reference group Interaction with best friends Interaction with other friends
.
MURTY
804
Table 6 Multiple Regression Analysis of Reference Group Variables with Student Drug Use in the Third Semester
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Reference group variables 1. 2. 3. 4. 5. 6. 7. 8.
Best friends’ drug use stand Parents as a reference group Other friends’ drug use stand Parental drug use stand Best friends as a reference group Interaction with parents Interaction with best friends Other friends as a reference group
r
Variance explained (rz)
.62451 .64224 .64962 .65408 .65902 .66243 .66296 .66321
.39001 .41247 .42201 .42182 .43431 .43882 .43952 .43985
Multiple
r2 change .02246 .00954 .00581 .00649 .00451
.00071 .00033
the reference groups that individuals orient themselves to and not as much the sociodemographic backgrounds from which they come. The second and third semester profiles also support this contention. In fact, the second semester profile shows that there is an increase in the explanatory power of reference group variables in second semester (44.7% compared to 41.0% in the first). This observation suggests the possibility that there is an increase in the importance of best friends and other friends as the student gets more “seasoned” on the campus and gets away from parental influence. The most important variable in all the three semesters is the drug use stand of the best friends. Interestingly enough, whether or not best friends were chosen as a reference group does not seem to make a significant difference, whereas the choice of parents as a reference group is more important than parental stand on drug use. That is, best friends’ ability to influence is possibly facilitated by their physical proximity on a residential college campus such as the University of Connecticut and thereby reduce the need to choose them as a reference group so as to accept their influence. And since parents are not as easily accessible to students of such a campus (compared to a commuting-student oriented campus, for example), their being chosen as a reference group seems to facilitate the parents’ ability to influence their children regarding drug use behavior. The least important variables are the intensity of interaction with the reference groups of other friends and best friends. The discussion thus far has focused on the analysis of reference group and sociodemographic variables separately. The next step is to combine
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DRUG USE IN COLLEGE STUDENTS
805
the two sets of variables into one single regression equation and examine their relative power. But it should be borne in mind that stepwise multiple regression allows the variables in the first step to explain all the variance they can before the next step is introduced. This means that the order in which the variables are entered into the equation itself would explain some of the difference in the variance in drug use behavior. In an effort to take this statistical artifact into account, the regression equation was computed twice for each of the semesters-once with sociodemographic variables in the first step and reference group variables in the second step, and the second time in the reverse order. Table 7 presents the abridged version of the equations for each of the three semesters. In the first semester, even when the sociodemographic variables were entered first to allow them to explain a11 the variance they can without regard to reference group variables, the reference group variables explained considerably more amount of variance (27.3 vs 16.6%) in the drug use variable. When reference group variables were allowed to explain all they can first, 44% of the variance came to their share whereas only 2.3% additional variance was attributed to sociodemographic variables. This table can be interpreted in another way-controlling for the sociodemographic influences, reference group variables can explain 27.3% of the variance in drug use, whereas controlling for the reference group influences, only 2.3%of the variance is explained by the sociodemographic Table 7 Stepwise Multiple Regression Analysis of Sociodemographic and Reference Group Variables for All Three Semesters
Semester First
Second
Third
Order of steps 1st step-Sociodemographic variables 2nd step-Reference group variables 1st step-Reference group variables 2nd stepSociodemographic variables 1st step-sociodemographic variables 2nd step-Reference group variables 1 st step-Reference group variables 2nd step-Sociodemographic variables 1st step-Sociodemographic variables 2nd step-Reference group variables 1st step-Reference group variables 2nd stepSociodemographic variables
Variance explained (r2)
.16588 .43771 .41005 .43837 .16451 .46803 .44694 .46803 .15237 .46302 .43985 .46318
r2
change .27183 .02832 -30352 .02109 .31065 .02333
MURTY
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806
variables. The same trend is observed in the second and third semesters as well. The reference group variables explained double the amount of variance even after the sociodemographic variables were brought into the equation first and were allowed to explain all the variance they could. Before we become confident of the observed findings, a test of multicollinearity needs to be performed. Hamburg (1970, pp. 514-515) suggests that regression coefficients for highly intercorrelated independent variables tend to be unreliable and that in such instances one of the two variables should be discarded. Using the rule of thumb that any correlations beyond the r of .5 are “highly correlated,” I correlated all the independent variables with one another. None of them came beyond the .5 limit. Therefore, I rejected the possibility of multicollinearity and accepted that the variance explained by the independent variables is truly due to their association with the dependent variable and not due to high intercorrelations between the independent variables in the equation.
CONCLUSIONS The fundamental assumption of this article has been supported by the data analysis-reference group variables are considerably more important in the understanding and predicting of student drug use behavior than their sociodemographic backgrounds. This held true for all three semesters. Of the sociodemographic variables investigated in this research, religiosity and religious background of the respondent accounted for most of the variance. Of the reference group variables, best friends’ drug use stand, the choice of parents as a reference group, other friends’ drug use stand, and parental drug use stand (in the descending order) consistently explained significant portions of the variance in the reference group model. Interaction with best friends and other friends did not explain much of the variance in student drug use for any of the semesters. The distinction between membership and nonmembership reference groups helps us understand the lack of significance between the student drug use and the reference group of best friends or of other friends. Since parents are, at the adolescent/early adulthood stage of the life-cycle, not membership groups, their influence on student drug use is possible only when they are chosen as the reference group. However, since best friends and other friends are membership groups, the socialization process is facilitated for these groups by their physical proximity to their members. Through the presentation of role models and the reinforcement of desired
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DRUG USE IN COLLEGE STUDENTS
807
behaviors, peer groups can influence student drug use even when they are not chosen as reference groups. As Siegel and Siegel (1975) point out, however, when membership groups are also reference groups, their influence is greatest on the individual. This study documented the importance of reference groups in a very general sense. Much further research is needed in understanding the specific dynamics of influence between the reference group and the individuals and the role cognitive dissonance plays in the individual’s conforming or deviating from the drug use norms of the reference group. Though this research has been done specifically on the use of marijuana and/or hashish, the importance of reference group variables found here can be extended to the use of other drugs as well. And, when the reference group factors are important in the initiation into, and continued commitment to, the use of drugs, they can also be used in drug prevention programs. Providing the patients with alternative role models within the treatment programs gives the best opportunity to combine reference group and membership group criteria and motivating change in drug use behavior. ACKNOWLEDGMENT
This research was partly funded by the University of Connecticut Research Foundation. REFERENCES AHMED, S.N. Patterns in juvenile drug use. Diss. Abstr. 28A: 4703, 1968. BECKER, H.S. On becoming a marijuana user. Am. J . Sociol. 59: 235-243, 1953. BILLINGS, D.K., and FERRARO, D.P. Marijuana use by college students: Three-year trends, 1970-1972. Int. J . Addict. 9(2): 321-327, 1974. BLUM, R.H. Students and Drugs. San Francisco: Jossey-Bass, 1969. CAVE, H.L. Self-reported adolescent drug use: A path analysis. Diss. Abstr. 33A: 5295, 1972. HAMBURG, M. Statistical Analysis.for Decision-Making. New York: Harcourt, Brace and World, 1970. KOHN, P.M., and MERCER, G.W. Drug use, drug use attitudes, and the authoritarianrebellion dimension. J . Health SOC.Behav. 12: 125-131, 1971. SHIBUTANI, T. Reference groups as perspectives. Am. J . Sociol. 6 0 562-569, 1955. SIEGEL, A.E., and SIEGEL, A. Reference groups, membership groups and attitude change. J. Abnorm. SOC.Psycho!. 55: 360-364, 1957. SIMMONS, G., and TROUT, G. Hippies in college: From teeny boppers to drug freaks. Trans-Action, 5: 27-32, 1967.
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SPEVACK, M., and PIHL, R.O. Nonmedical drug use by college students: A three-year survey study. Int. J . Addict. ll(5): 755-792, 1976. SUCHMAN, E. The hang-loose ethic and the spirit of drug use. J . Health SOC.Eehav. 9: 146-155, 1968. TEC, N. Family and differential involvement with marijuana: A study of suburban teenagers. J . Marriage Family 32: 656-664, 1970. WINSLOW, J.B. Drug use and social integration. Int. J. Addicf. 9(4): 531-540, 1974.
The International Journal of the Addictions, 14(6), 797-808, 1979
Drug Use in College Students: A Test of Sociodemographic and Reference Group Models of Explanation Lakshmi Murty Department of Sociology Rutgen University New Brunswick, New Jersey 08903
Abstract
This study examined the importance of reference group variables in the understanding of drug use in college students. Other studies have investigated the role of peer orientation, and this study further elaborates on the issue by specifically looking into parents and peers as reference groups for the students. This study supports the importance of reference group variables in understanding the students’ use of marijuana and/or hashish. In addition, it shows that the sociodemographic variables cannot predict drug use behavior as well as the reference group variables can. This study attempts to investigate the importance of reference group variables compared to the sociodemographic ones in understanding and 797 Copyright @ 1979 by Marcel Dekker, Inc. All Rights Reserved. Neither this work nor any part may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, microfilming, and recording, or by any information storage and retrieval system, without permission in writing from the publisher.
Subst Use Misuse Downloaded from informahealthcare.com by Leids University on 11/21/14 For personal use only.
798
MURTY
predicting the drug use of college students. Most of the literature on drug use abounds with the sociodemographic correlates of drug users and nonusers. Socioeconomic status is a key variable that has consistently correlated with drug use. Most of the studies indicate that it is the students from middle- and upper-middle-classes that most heavily use marijuana. However, for Kohn and Mercer (1971) this relationship did not reach the conventional level of significance. Simmons and Trout (1967)observe that drug users are often scholarship holders, social science majors, Jewish, and from middle-class intact urban or suburban homes. Similarly, Blum (1969) observes that students with drug experience are generally wealthier and older upper-classmen, irreligious, in opposition to their parents, politically left-wing and active, usually in arts and humanities or social sciences, undergoing ideological shifts, and generally more pessimistic about the future. Ahmed (1968) finds unconventionality in religious orientations in his sample of drug users. Suchman (1968) and Billings and Ferraro (1974) similarly note that drug users tend to be either atheists or have exotic or unusual religious preferences such as Zen Buddhism. Generally these studies have been descriptive and correlative. Very few studies have used theoretical propositions and tested them in the context of drug use. One such study is by Winslow (1974). Here an attempt is made to test two different and theoretically meaningful hypotheses, one stemming from diffusion and the other stemming from subcultures. The present study tests the general hypothesis that students will be influenced by their reference orientations in the use or nonuse of marijuana or hashish. In criticizing previous studies on drug use, Spevack and Pihl (1976, p. 757) single out one as the most important drawback “ . . . the interpretation of results of some questionnaires is confounded by the fact that many demographic differences (sex, age, social class) have been found to mark DUs and NUS and these differences, rather than the differential use of drugs, may explain many of the other behavioral and attitudinal differences noted between groups.” This study attempts to not only point to the importance of reference group variables in the understanding of drug use phenomenon, but also tries to compare their regression equations to those of the various demographic factors known to influence drug use behavior, in an effort to empirically document the relative role played by each of these sets of variables. As the vast amount of literature on drug use indicates, it is almost always a close peer that socializes one into the expectation of a pleasurable experience through the use of drugs. Along with this expectation goes the
Subst Use Misuse Downloaded from informahealthcare.com by Leids University on 11/21/14 For personal use only.
DRUG USE IN COLLEGE STUDENTS
799
notion of “growing up” and ascertaining independence from parents and a concomitant search for identity with peers. Becker (1953), Blum (1969), Tec (1970), Winslow (1974), Spevack and Pihl (1976), and many others have documented the critical role played by the peers in one’s use of drugs. In addition, Tec’s study of suburban teenagers documents the importance of parents as role models and the quality of life at home. This bespeaks the interactional and situational nature of the use of drugs and the salience of the concept of reference groups. Yet, this concept is not employed in the studies of drug use. This study uses the research on peer and parent influences on drug use patterns as a take-off point and brings the concept of reference groups directly into the design. The questions of importance to this study are: (1) the influence of parents as a reference group on the student’s use of pot/hash; (2) the quality of interaction between students and the reference group of parents and the influence this has on the use of pot/hash by students; (3) the influence of (a) best friends, and (b) other friends and acquaintances as reference groups on the use or nonuse of pot/hash by the students; and (4) the quality of interaction between students and their reference group of best friends or other friends and the influence this has on the use of pot/hash by the respondents. Following Shibutani (1955), a reference group is defined here as a . . . group whose perspective constitutes the frame of reference for the actor.” This theoretical definition has had tautological problems when it has been operationally defined for research purposes. To avoid such problems, the present study arrived at a novel operational definition of reference groups by combining it with the concept of dissonance. If indeed an individual’s attitudes and conduct are shaped by the groups to whom one orients one’s self, then it is logical to assume that when the individual finds out that in fact his/her norms and values are at odds with, or different from, the groups to whom he/she is attributing these norms, this new revelation should create a sense of cognitive dissonance. Whereas, if these persons were not his/her referent others, such revelations should not matter to the individual. With this rationale, a question was constructed to tap whether parents, best friends, or other friends were their reference group. This question was asked for each of the three semesters the student spent at the university. The aim was to see if there were any shifts in reference orientation (most likely is the shift from parents to peers) during these three semesters. The dependent variable drug use is measured by the following question: At the beginning of your first semester freshman year (second semester freshman yearlfirst semester sophomore year), where did you “
MURTY
800
stand on pot or hash? (a) Was against it and did not smoke, (b) Was curious but did not smoke, (c) Favored using it and experimented with it a few times, (d) Smoked occasionally, (e) Smoked regularly.
Subst Use Misuse Downloaded from informahealthcare.com by Leids University on 11/21/14 For personal use only.
RESEARCH DESIGN This study is based on second semester sophomores at the University of Connecticut. During the first week of 1974 spring semester, questionnaires were given out to students enrolled in randomly selected courses at the University of Connecticut main campus. Only those classes were included in the pool for sample selection that had a majority of second semester sophomores. This procedure of selecting students with one standard classification and not all was found necessary so as to guard the results from being confounded by comparing different cohorts of students, their differential ability to recall previous experiences regarding drug use influences, etc. The final sample size is 71 1 second semester sophomores. This is approximately a third of the student population with that classification enrolled at the university during the spring of 1974. Since stepwise multiple regression analysis provides a “near-optimum” solution to the problem of predicting the dependent variable from a series of independent variables, this method was found to be appropriate and efficient for the purposes of examining the relative importance of reference group and sociodemographic explanations of drug use.
DATA ANALYSIS Table 1 identifies the regression equation for the sociodemographic variables with the first semester drug use patterns. Of the total variance explained by all the sociodemographic variables (16.6%), a significant portion is explained (12.4%) by the religiosity information alone. The variables of religious preference and father’s occupation are the next most important predictors of student drug use in that order. Sex, age, grade point average, major field of study, ethnicity, parental social class identification, parents’ income, and father’s education have contributed less than one-half of 1% to the variance each, in addition to the first three variables. This is an interesting finding to note, particularly because parental economic status, parental social class identification, major field of study, and grade point average have generally been shown to have significant association with drug use variables. These results throw some doubt on, if not fiecessarily disprove, the
801
DRUG USE IN COLLEGE STUDENTS
Table 1 Multiple Regression Analysis of Sociodernographic Variables with Student Drug Jse in the First Semester
Sociodemographic variables
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~~~
Multiple r
Variance explained (rZ)
change
.35224 .37284 .39107 .39438 .39763 .39994 .40191 .40372 .40479 .40651 .40729
,12407 .13901 .15294 .15553 .15811 .15995 .16153 .16299 .16386 .I6525 .16588
.01494 .01393 .00260 .00257 @I184 .00159 .00146 .00086 .00139 .00063
r2
~
1, Religiosity 2. Religion 3. Father’s occupation 4. Sex 5. Age 6. Grade point average 7, Major field of study 8. Ethnicity 9. Parental SES identification 10. Parental economic status 11. Father’s education
.
importance attached to the demographic variables in the drug use literature available thus far. One of the problems is that most of these studies have not gone beyond correlation analysis to see what the observed correlation is actually worth in terms of its relative effectiveness in predicting the dependent variable. The only other study that utilized the method of multiple regression analysis (Cave, 1972) has also found that sociodemographic variables explain very little of variation in drug use patterns. This gives us confidence in the overall explanatory power of sociodemographic variables found in my research. Stepwise multiple regression equations for the second and third semester drug use patterns (Tables 2 and 3, respectively) are quite similar to the first with some minor shifts in the order of importance of the variables included in the equation. In the second semester, father’s occupation has dropped in its explanatory power of drug use patterns considerably but father’s education has taken its place. Mother’s occupation and education are not important in any of the three semesters. One of the reasons for this lack of importance is possibly that there is not much variation in this variable. Most of the students have stated that their mothers are housewives. A real test of the role of mother’s occupation would probably come from a sample that has variation in her occupational status. Father’s occupation and education have dropped to a very
MURTY
802
Table 2
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Multiple Regression Analysis of Sociodemographic Variables with Student Drug Use in the Second Semester
Sociodemographic variables
Multiple r
Religiosity Religion Father’s education Sex 5. Grade point average 6. Parental SES identification 7. Parental economic status 8. Major field of study 9. Age 10. Father’s occupation 11. Ethnicity 12. Mother’s occupation 13. Mother’s education
.33749 ,35638 .36773 .37846 .38508 .39005 -39489 .39902 .a278 .40451 .40498 .40533
1. 2. 3. 4.
.a560
Variance explained (r2)
rz change
.I1390 .12701 .13523 .I4323 .14829 .15214 .15593 .15922 .16223 .16363 .I6401 .16430 .16451
.01311 .00822 .00801 .00506 .00385 .00379 .00329 .00301 .00140 .00038 .00029 .00021
insignificant status in the third semester. On the other hand, major field of study and parental economic status have gained additional explanatory power relative to the first two semesters. However, these are only minor Table 3 Multiple Regression Analysis of Sociodemographic Variables with Student Drug Use in the Third Semester Variance explained
Sociodemographic variables
Multiple r
(r2)
rz change
Religiosity Religion Major field of study Parental economic status 5. Sex 6. Parental SES identification 7. Age 8. Grade point average 9. Ethnicity 10. Father’s education 11. Mother’s education 12. Father’s occupation
.35167 .35956 .36560 .37057 .37594 .38061 .38466 .38706 .38829 ,38899 .39031 .39034
.12367 .12928 .13367 .13732 .14133 .14486 .14797 .14982 .15077 .15131 .15234 .15237
.00561 .0m38 .00366 .oO401 .00353 .00310 .00185 .00095 .m54 .00103 . m 2
1. 2. 3. 4.
803
DRUG USE IN COLLEGE STUDENTS
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Table 4 Multiple Regression Analysis of Reference Group Variables with Student Drug Use in the First Semester
Reference group variables
Multiple r
Variance explained (r2)
1. Best friends’ drug use stand 2. Parents as a reference group 3. Other friends’ drug use stand 4. Parental drug use stand 5. Interaction with parents 6. Other friends as a reference group 7. Best friends as a reference group 8. Interaction with best friends 9. Interaction with other friends
.58328 .60550 .62080 .63028 .63477 .63896 .64030 .64034 .64035
.34021 .36663 .38539 .39725 .40293 .40827 .40998 .41003 .41005
rz change
,
.02642 .01876 .01186 .MI568 ,00533 .00171
.oooo5 .oooo2
variations and the pattern of relationships of sociodemographic variables to drug use stand have generally remained the same. Tables 4, 5, and 6 portray the variance explained by the reference group variables over the same three-semester period. The overall explanatory power of reference group variables for the first semester drug use is 41.0%, which is considerably higher than that recorded for the sociodemographic variables (16.6%). The overwhelming difference clearly supports the major thesis of this article-drug use patterns are influenced by (or, the variation in drug use patterns is more accurately predicted by) Table 5 Multiple Regression Analysis of Reference Group Variables with Student Drug Use in the Second Semester
r
Variance explained (r2>
rz change
.63606 .65165 .65970 .66306 .66626 .66764 .66828 .66849 .66853
.40458 .42464 .43521 .43965 .44391 .44574 .44660 .44688 .44694
.02006 .01057 .00444 .00426 .00184 -00086 .00027 oooO6
Multiple Reference group variables ~~
~
1. 2. 3. 4. 5. 6. 7. 8. 9.
~
~~
Best friends’ drug use stand Parents as a reference group Other friends’ drug use stand Parental drug use stand Interaction with parents Best friends as a reference group Other friends as a reference group Interaction with best friends Interaction with other friends
.
MURTY
804
Table 6 Multiple Regression Analysis of Reference Group Variables with Student Drug Use in the Third Semester
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Reference group variables 1. 2. 3. 4. 5. 6. 7. 8.
Best friends’ drug use stand Parents as a reference group Other friends’ drug use stand Parental drug use stand Best friends as a reference group Interaction with parents Interaction with best friends Other friends as a reference group
r
Variance explained (rz)
.62451 .64224 .64962 .65408 .65902 .66243 .66296 .66321
.39001 .41247 .42201 .42182 .43431 .43882 .43952 .43985
Multiple
r2 change .02246 .00954 .00581 .00649 .00451
.00071 .00033
the reference groups that individuals orient themselves to and not as much the sociodemographic backgrounds from which they come. The second and third semester profiles also support this contention. In fact, the second semester profile shows that there is an increase in the explanatory power of reference group variables in second semester (44.7% compared to 41.0% in the first). This observation suggests the possibility that there is an increase in the importance of best friends and other friends as the student gets more “seasoned” on the campus and gets away from parental influence. The most important variable in all the three semesters is the drug use stand of the best friends. Interestingly enough, whether or not best friends were chosen as a reference group does not seem to make a significant difference, whereas the choice of parents as a reference group is more important than parental stand on drug use. That is, best friends’ ability to influence is possibly facilitated by their physical proximity on a residential college campus such as the University of Connecticut and thereby reduce the need to choose them as a reference group so as to accept their influence. And since parents are not as easily accessible to students of such a campus (compared to a commuting-student oriented campus, for example), their being chosen as a reference group seems to facilitate the parents’ ability to influence their children regarding drug use behavior. The least important variables are the intensity of interaction with the reference groups of other friends and best friends. The discussion thus far has focused on the analysis of reference group and sociodemographic variables separately. The next step is to combine
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DRUG USE IN COLLEGE STUDENTS
805
the two sets of variables into one single regression equation and examine their relative power. But it should be borne in mind that stepwise multiple regression allows the variables in the first step to explain all the variance they can before the next step is introduced. This means that the order in which the variables are entered into the equation itself would explain some of the difference in the variance in drug use behavior. In an effort to take this statistical artifact into account, the regression equation was computed twice for each of the semesters-once with sociodemographic variables in the first step and reference group variables in the second step, and the second time in the reverse order. Table 7 presents the abridged version of the equations for each of the three semesters. In the first semester, even when the sociodemographic variables were entered first to allow them to explain a11 the variance they can without regard to reference group variables, the reference group variables explained considerably more amount of variance (27.3 vs 16.6%) in the drug use variable. When reference group variables were allowed to explain all they can first, 44% of the variance came to their share whereas only 2.3% additional variance was attributed to sociodemographic variables. This table can be interpreted in another way-controlling for the sociodemographic influences, reference group variables can explain 27.3% of the variance in drug use, whereas controlling for the reference group influences, only 2.3%of the variance is explained by the sociodemographic Table 7 Stepwise Multiple Regression Analysis of Sociodemographic and Reference Group Variables for All Three Semesters
Semester First
Second
Third
Order of steps 1st step-Sociodemographic variables 2nd step-Reference group variables 1st step-Reference group variables 2nd stepSociodemographic variables 1st step-sociodemographic variables 2nd step-Reference group variables 1 st step-Reference group variables 2nd step-Sociodemographic variables 1st step-Sociodemographic variables 2nd step-Reference group variables 1st step-Reference group variables 2nd stepSociodemographic variables
Variance explained (r2)
.16588 .43771 .41005 .43837 .16451 .46803 .44694 .46803 .15237 .46302 .43985 .46318
r2
change .27183 .02832 -30352 .02109 .31065 .02333
MURTY
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806
variables. The same trend is observed in the second and third semesters as well. The reference group variables explained double the amount of variance even after the sociodemographic variables were brought into the equation first and were allowed to explain all the variance they could. Before we become confident of the observed findings, a test of multicollinearity needs to be performed. Hamburg (1970, pp. 514-515) suggests that regression coefficients for highly intercorrelated independent variables tend to be unreliable and that in such instances one of the two variables should be discarded. Using the rule of thumb that any correlations beyond the r of .5 are “highly correlated,” I correlated all the independent variables with one another. None of them came beyond the .5 limit. Therefore, I rejected the possibility of multicollinearity and accepted that the variance explained by the independent variables is truly due to their association with the dependent variable and not due to high intercorrelations between the independent variables in the equation.
CONCLUSIONS The fundamental assumption of this article has been supported by the data analysis-reference group variables are considerably more important in the understanding and predicting of student drug use behavior than their sociodemographic backgrounds. This held true for all three semesters. Of the sociodemographic variables investigated in this research, religiosity and religious background of the respondent accounted for most of the variance. Of the reference group variables, best friends’ drug use stand, the choice of parents as a reference group, other friends’ drug use stand, and parental drug use stand (in the descending order) consistently explained significant portions of the variance in the reference group model. Interaction with best friends and other friends did not explain much of the variance in student drug use for any of the semesters. The distinction between membership and nonmembership reference groups helps us understand the lack of significance between the student drug use and the reference group of best friends or of other friends. Since parents are, at the adolescent/early adulthood stage of the life-cycle, not membership groups, their influence on student drug use is possible only when they are chosen as the reference group. However, since best friends and other friends are membership groups, the socialization process is facilitated for these groups by their physical proximity to their members. Through the presentation of role models and the reinforcement of desired
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DRUG USE IN COLLEGE STUDENTS
807
behaviors, peer groups can influence student drug use even when they are not chosen as reference groups. As Siegel and Siegel (1975) point out, however, when membership groups are also reference groups, their influence is greatest on the individual. This study documented the importance of reference groups in a very general sense. Much further research is needed in understanding the specific dynamics of influence between the reference group and the individuals and the role cognitive dissonance plays in the individual’s conforming or deviating from the drug use norms of the reference group. Though this research has been done specifically on the use of marijuana and/or hashish, the importance of reference group variables found here can be extended to the use of other drugs as well. And, when the reference group factors are important in the initiation into, and continued commitment to, the use of drugs, they can also be used in drug prevention programs. Providing the patients with alternative role models within the treatment programs gives the best opportunity to combine reference group and membership group criteria and motivating change in drug use behavior. ACKNOWLEDGMENT
This research was partly funded by the University of Connecticut Research Foundation. REFERENCES AHMED, S.N. Patterns in juvenile drug use. Diss. Abstr. 28A: 4703, 1968. BECKER, H.S. On becoming a marijuana user. Am. J . Sociol. 59: 235-243, 1953. BILLINGS, D.K., and FERRARO, D.P. Marijuana use by college students: Three-year trends, 1970-1972. Int. J . Addict. 9(2): 321-327, 1974. BLUM, R.H. Students and Drugs. San Francisco: Jossey-Bass, 1969. CAVE, H.L. Self-reported adolescent drug use: A path analysis. Diss. Abstr. 33A: 5295, 1972. HAMBURG, M. Statistical Analysis.for Decision-Making. New York: Harcourt, Brace and World, 1970. KOHN, P.M., and MERCER, G.W. Drug use, drug use attitudes, and the authoritarianrebellion dimension. J . Health SOC.Behav. 12: 125-131, 1971. SHIBUTANI, T. Reference groups as perspectives. Am. J . Sociol. 6 0 562-569, 1955. SIEGEL, A.E., and SIEGEL, A. Reference groups, membership groups and attitude change. J. Abnorm. SOC.Psycho!. 55: 360-364, 1957. SIMMONS, G., and TROUT, G. Hippies in college: From teeny boppers to drug freaks. Trans-Action, 5: 27-32, 1967.
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MURTY
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SPEVACK, M., and PIHL, R.O. Nonmedical drug use by college students: A three-year survey study. Int. J . Addict. ll(5): 755-792, 1976. SUCHMAN, E. The hang-loose ethic and the spirit of drug use. J . Health SOC.Eehav. 9: 146-155, 1968. TEC, N. Family and differential involvement with marijuana: A study of suburban teenagers. J . Marriage Family 32: 656-664, 1970. WINSLOW, J.B. Drug use and social integration. Int. J. Addicf. 9(4): 531-540, 1974.
