J. DRUG EDUCATION, Vol. 21 (4) 303-312, 1991
PERSONAL AND SOCIAL MOTIVATIONS AS PREDICTORS OF SUBSTANCE USE AMONG COLLEGE STUDENTS
TONY L. HADEN, PH.D. Southwest Texas State University, San Marcos, Texas ELIZABETH W. EDMUNDSON, PH.D. University of Texas, Center for Health Promotion, Research and Development, Austin
ABSTRACT
The Drug Use Survey was administered via a direct mail to a simple random sample of 2200 students enrolled at a large southwestern U.S. university. A purpose of the study was to determine the predictability of self-reported drug use utilizing motivations (personal and social) commonly reported by substance users. Two subscales were developed, one for each category of motivations. Reliability for each subscale as estimated by coefficient alpha was 80 and .86, respectively. A series of step-wise multiple regression analyses were computed in which individual drug use indices served as criterion variables, while the predictor variables were the personal motivations subscale (PMS) and the social motivation subscale (SMS) for each model. The results indicated that the PMS was the stronger predictor in every model with the exception of the model that predicted the alcohol use index. The SMS was the best predictor for alcohol use.
Among college students who use psychoactive drugs, the primary substance of choice is alcohol, with marijuana a distant second and other recreational drugs an even more distant third [l-31. While the national media focuses on the use of crack cocaine and the negative health and behavioral effects associated with it, college campuses continue to experience the traditional use of alcohol by the vast majority of students [2-31. Since the 1960s, marijuana has remained a secondary, but significant, substance of choice with approximately half as many students using 303 8 1991, Baywood Publishing Co., Inc.
doi: 10.2190/WC1D-7XHR-ATQJ-81NP http://baywood.com
304 / HADEN AND EDMUNDSON
the drug on a regular basis as use alcohol. The remaining substances used recreationally by college students are done so on a limited basis relative to alcohol. The multifaceted nature of drug taking behavior is reflected in part by the commonly reported yet diverse motivations associated with various patterns of drug use [4-111. Motivations such as curiosity, a desire to alter consciousness, exploration of the self, facilitation of social interaction, stimulation of artistic creativity, enhancement of sensory experience and pleasure appear to be more associated with recreational patterns of use. Motivations that seem to be connected to problematic relationships with drugs include boredom, rebellion against societal expectations, peer pressure, and relief from emotional or physical pain. More specifically, theoretical discussions of the notion that individuals use different drugs for different reasons are popular in textbooks and conference papers, yet little evidence of systematic, data-based research on this issue has been published. The educational model of substance abuse prevention relies heavily upon the dissemination of information concerning the adverse consequences of substance misuse in order to counteract the motivations for drug use [4, 12, 131. One weakness of this approach is that the potential negative consequences of drug use are more often related to very heavy and long-term use rather than the pattern of use most commonly found among college students. Additionally, motivations for drug use are not the reciprocal of the motivations for abstinence [14]. By directly addressing the motivations for use, educational interventions would not have to rely upon the limited persuasiveness of potential adverse consequences messages. The efficacy of education as a mitigator of substance abuse is predicated on individuals internalizing the information on both the belief and attitudinal levels [151. The tenuous relationship between education and behavior is accentuated in college students due to their resiliency and the absence of chronic adverse effects of drug use, both attributable to their youth [16]. In addition, the pleasurable outcomes which often result from substance use frequently reinforces students’ motivations for using drugs. Thus, quite understandably, the positive consequences of substance use often outweigh the negative consequences among this population. If education is to be effective in preventing substance abuse, it is imperative that the motivations for substance use be empirically determined and objectively reported. Assumptions concerning the motivations for substance use based upon anecdotal, experiential, and intuitive evidence are seductive, but undermine the credibility of abuse prevention programs. Therefore, the intent of this study was to determine the predictability of substance use among college students utilizing self-reported personal and social motivations. Information concerning the relationship between substance use and its motivations has direct abuse prevention implications. Specifically, the ability of programs to intervene at the primary prevention level depends upon an understanding of the underlying motivational factors that correspond to the use of specific psychoactive substances.
MOTIVATIONS AS PREDICTORS OF SUBSTANCE USE / 305
METHODOLOGY A major institutional research survey on student drug use was conducted at a large, public southwestern university. The survey was mailed to a simple random sample of 2200 students with one follow-up letter. Respondents returned the survey via a stamped addressed envelope that was included in the packet. A cover letter explained the purpose of the survey and ensured the students that participation was completely voluntary and anonymous. The net response totalled 1013 or a 46.04 percent response rate. A comparison of the sample’s demographic statistics indicated the sample mirrored the student population’s demographic parameters. Table 1 contains the demographic characteristics the sample.
Instrument The survey instrument consisted of 174 items that purported to measure: 1) personal substance use behavior (frequency, intensity, duration); 2) perceived substance use behavior of other students; 3) frequency of behaviors associated with substance use; 4) motivations for substance use; 5) consequences of substance use; 6) attitudes toward substance use relative to school and health; 7) demographics; and 8) miscellaneous items. The substances of interest to the study included alcohol, marijuana, cocaine, amphetamines, barbiturates, tranquilizers, psychedelics, and designer drugs (e.g., MDA, MDMA). The Motivations for Substance Use section of the survey contained a response category whereby the respondent could indicate that he/she was not a current user of any substance. Thus, all analyses involving the motivation items included only those respondents that reported to be current drug users.
Analyses The Motivations for Substance use section of the survey consisted of eleven Likert-type items covering a variety of specific reasons associated with alcohol and other drug use. Respondents were asked to indicate the importance of each reason as a motivator for their use of alcohol and other drugs. The response categories for each item had three levels which ranged from not important, moderately important, to very important. For the purposes of this study the motivation items were grouped into two subscales, personal motivations (eight items) and social motivations (three items) (see Table 2). The Personal Substance Use Behavior section of the survey consisted of three facets of drug use: 1)frequency of use; 2) intensity of effects of use; and 3) duration of effects of use. Due to differences in the pharmacology of the substances of interest, comparison among the substances on only one facet or of each facet individually could be very misleading. Therefore, an index comprised of the three facets of drug use was computed for each of the substances.
306 / HADEN AND EDMUNDSON
Table 1. Biographic Background Characteristics of Study Sample (n = 1013) Variable
Frequency
Percent
489 523
48.3 51.6
223 31a 177 91 204
22.0 31.4 17.5 9.0 20.1
Class Freshman Sophomore Junior Senior Graduate
147 1 a3 21 1 235 236
14.5 18.1 20.8 23.2 23.3
Race Asian/Oriental Black White/Caucasian Hispanic Other
68 33 a09 97 6
6.7 3.3 79.9 9.6 .5
25 129 280 275 305
2.5 12.7 27.6 27.1 30.1
175 7 16 a1 4
17.3 0.7 1.6 80.4
Gender Male Female Age
19 years or younger 20-21 22-23 24-25 26 years or older
Grade-Point Average
0.00-1.99 2.00-2.49 2.50-2.99 3.00-3.49 3.50-4.00 Marital Status MarriedKohabitating Separated Divorced Never Married
MOTIVATIONS AS PREDICTORS OF SUBSTANCE USE / 307
Table 2. Motivations for Substance Use Sub-scales The reasons I use alcohol and/or other drugs are:
Personal Motivation Sub-scale
Social Motivation Sub-scale
pl p2 p3 p4 p5 p6
sl
p7
to experiment to relax to get away from my problems to escape boredom to get to sleep because of bad moods to feel better about myself
s2
s3
to have a good time with friends to fit in with the group I like to celebrate
The Statistical Package for the Social Sciences (SPSS) was utilized to compute eight step-wise multiple regression analyses, with the motivation subscales serving as the predictor variables in each of the models. One of the eight substance use indexes served as the criterion variable in each model. A potential problem inherent in using both of the motivation subscales as predictor variables was the possibility of an intercorrelation between them that could result in their absolute impact being masked. Although the subscales had no items in common, some of the items have enough characteristics in common so as to make the question of multicollinearity salient. Although the correlation between the subscales was not high enough to support a claim of unidimensionality (r = .67),it was high enough to warrant further analysis into the construct (factorial) validity of the subscales. Therefore, a principal components analysis of the motivation items was conducted followed by varimax rotation of the components with eigenvalues greater than one. RESULTS
The internal consistency reliability estimate using Cronbach’s coefficient alpha for the entire instrument was found to be .96. Cronbach’s coefficient alpha provided estimates of reliability, .SO and .S6, for the personal and social motivations subscales, respectively. The descriptive statistics for the Motivation of Substance Use subscales indicated that the social motivation items were slightly stronger than the personal motivation items. On a scale of 0-3 with a score of 3 representing the strongest motivational level for an item, the social motivation items had a relative mean of 2.54 with a standard deviation of .57, compared to the personal motivation items that had a relative mean of 2.00 with a standard deviation of .69.
308 / HADEN AND EDMUNDSON
As with the motivation subscales, the substance use indexes evidenced acceptable reliability estimates, with coefficient alpha ranging between .75 and .96. Descriptive statistics for the substance use indexes and the intercorrelation matrix for the indexes are presented in Table 3. The results of the principal components analysis of the motivation item suggest that the eleven items constituted two factors (see Table 4). The eight personal motivation items had the highest factor loadings on factor one, and the three social motivation items had the highest factor loadings on factor two. Therefore, while it was never presumed that the subscales represented two separate unidimensional constructs, it does appear that they did represent two facets of motivation that were sufficiently discrete to warrant statistical comparison. A series of stepwise multiple regression models were analyzed in which the eight substance use indexes each served as the criterion variable (see Table 5). The predictor variables for every regression model were the Personal Motivation Subscale (PMS) and the Social Motivation Scale (SMS). The degree of predictability of the motivation subscales varied from substance to substance. In general, Table 3. Descriptive Statistics of Substance Use Indexes (Score range 0-15; N = 842) Substance Use Index
Mean
Std. Dvn.
Coef Alpha
Alcohol Marijuana Cocaine Amphetamine Barbiturate Tranquilizer Psychedelics Designer drugs
7.55 3.44 1.47 1.14 .48
2.02 3.58 2.90 2.58 1.68 1.83 3.27 3.39
.75 .93 .94
.68 1.49 1.68
.93
.91 .90 .96 .96
Pearson Correlation Coefficients Among Substance Use Indexes
Alcohol Marijuana Cocaine Amphetamine Barbiturate Tranquilizer Psychedelics Designer drugs
Alc.
Mar.
1.oo .47 .30 .25 .15 .16 .22
1.00 .59 .51 .30 .35
.33
.53 51
COC. Amp.
1.00 .72 .46 .45 .66 .60
1.00 .57
.50 .61 .55
Bar.
Tra.
Psy.
D.D.
1.00 .69 .44 .42
1.00 S3 .38
1.00 55
1 .OO
MOTIVATIONS AS PREDICTORS OF SUBSTANCE USE / 309
Table 4. Principal Components Analysis of the Motivationsfor Drug Use Items ~~
Variable
Factor 1
Factor 2
Pl
.3962 .4608 1932 5449 .7356 .7339 .6597 .7591 .7460 .2133
.2963 .3850 .7615 .7373 .2629 .2970 .1413 .1929 .1959 .7391
P2 sl s2 P3 P4 P5 P6
P7 s3
.
the PMS proved to be the stronger predictor of the two scales in that it was either the first or only variable that entered into seven of the eight regression equations. Every prediction model was statistically significant at thep c ,0001 level. The regression analysis for which the Alcohol Use Index was the criterion variable resulted in a two variable model in which the SMS was the strongest predictor. This regression model had a Multiple R value of .72 and an adjusted R-Squared value of .51. Alcohol use proved to be the most predictable of the substance use behaviors. The regression model for which the Marijuana Use Index was the criterion variable resulted in a two variable equation in which the PMS was the stronger predictor. As noted by Table 5 , this regression model yielded a Multiple R value of .41 and an adjusted R-Squared value of .17. Marijuana use was the second most predictable of the substance use behavior indexes. Other regression models in which both predictor variables entered into the equation and which the stronger predictor was the PMS included those for the Barbiturate and the Tranquilizer Use Indexes. However, neither model proved to have substantial predictiveness, with Multiple R values of .25 and .27 and Adjusted R-Square values of .06 and .07, respectively. The regression models for which the Cocaine, Amphetamine, Psychedelics and Designer Drug Use Indexes were each the criterion variable resulted in only the PMS entering into the equations at a significant level. However, those four equations yielded R-Square values that also indicated limited contributions to the predictability of the criterion variable. Thus, while alcohol use was very predictable using the SMS and marijuana use was moderately predictable using the PMS, the remaining six substances were very difficult to predict from either social or personal motivations. The
310 / HADEN AND EDMUNDSON
Table 5. Summary Statistics Associated with the Stepwise Multiple Regression Analysis Personal and Social Motivation Sub-scales by Substance Use Index (n = 863) ~
Step
Variable Entered
Model R2
Multiple R
F-Ratio
p-Value
Dependent Variable = Alcohol Index
1 2
Social motivations Personal motivations
0.3242 0.3470
0.5694 0.5890
452.47 250.31
0.0001
0.0001
Dependent Variable = Cocaine Index
1 2
Personal motivations Social motivations
0.0753 0.0914
0.2744 0.3024
19.13 11.77
0.0001 0.0001
Dependent Variable = Marijuana Index 1 2
Personal motivations Social motivations
0.091 1 0.0976
0.3019 0.3124
55.55 29.91
0.0001 0.0001
Dependent Variable = Tranquilizer Index 1
Personal motivations
0.0753
0.2745
12.71
0.0005
Dependent Variable = Designer Drugs Index
1
Personal motivations
0.0509
0.2255
10.56
0.0014
Dependent Variable = Psychedelics Index 1
Personal motivations
0.0481
0.2193
9.50
0.0024
Dependent Variable = Barbiturate Index 1
Personal motivations
0.0946
0.3075
10.45
0.0017
Dependent Variable = Amphetamine Index
1
Personal motivations
0.0839
0.2896
18.95
0.0017
general low levels of usage among substances other than alcohol and marijuana was a likely factor in the inability of the motivation subscales to adequately predict usage. Although the regression models for alcohol and marijuana use resulted in two-predictor variable equations, in each model the variable that was entered second contributed little to the overall predictiveness of the model.
MOTIVATIONSAS PREDICTORS OF SUBSTANCE USE / 31 1
CONCLUSI 0NS
The results of the descriptive statistics for both motivation subscales indicate that, with the exception of alcohol, college students use drugs more for personal reasons than for social reasons. Thus, primary prevention programs should be directed toward the personal aspects of drug use. However, given the strength of the SMS as a predictor of alcohol use and the fact that alcohol is the overwhelming drug of choice among college students, it appears that prevention efforts should also be directed toward addressing the social motivations for drinking. The results found in this study also indicate a need for more research, given that students’ motivations for substance use varied across specific drugs and therefore may vary across other variables. Moreover, the complexity of substance use behavior warrants abuse prevention efforts that should be tailored to the context. In the case of motivation, there appears to be a difference in the type of reasons why students use alcohol compared to other drugs. Thus, there should be a corresponding difference in the way prevention programs address the use of alcohol versus other recreational drugs. Finally, it should be noted that research indicates that junior high school and high school students use all drugs for primarily social reasons [17]. The results of this study suggest that a fundamental shift in motivations of substance use occurs among students as they mature and enter college such that personal motivations increase in their influence on drug use behavior. The change in emphasis from social to personal motivations for drug use may be consistent with the stage of human development that characterizes most students’ college experience.
REFERENCES 1. P. R. Clifford, E. W. Edrnundson, W. R. Koch, and B. G. Dodd, Discerning the Epidemiology of Drug Use among a Sample of College Students, Journal of Drug Education, 19:3,pp. 209-223,1989. 2. National Institute on Drug Abuse, Drug Use among American High School Students, College Students, and Other Young Adulfs, (DIIHS Publication No. 81-1450),U.S. Government Printing Office, Washington, DC, 1986. 3. National Institute on Drug Abuse, National Trends in Drug Use and Related Factors among American High School Students and Young Adults, 1975-1986, (DHHS Publication No. (ADM) 87-1535), U.S. Government Printing Office, Washington, DC, 1987. 4. D. Duncan and R. Gold, Drugs and fhe Whole Person, Macmillan, New York, 1985. 5. R. Jessor and S. L. Jessor, Problem Behavior and Pyschosocial Development: A Longitudinal Study ofYoufh,Academic Press, New York, 1977. 6. S. Peele, Diseasing of America: Addiction Treatment Out of Control, Lexington Books, Lexington, Massachusetts, 1989. 7. J. Shedler and J. Block, Adolescent Drug Use and Psychological Health: A Longitudinal Inquiry,American Psychologist, 4.55, pp. 612-630,1990.
312 / HADEN AND EDMUNDSON
8. B. Segal, G. J. Huba, and J. L. Singer, Reasons for Drug and Alcohol Use by College Students, The International Journal of thedddictions, 15~4,pp. 489498,1980. 9. R. Siege], Intoxication: Life in Pursuit ofArtificia1 Paradise, E. P. Dutton, New York, 1989. 10. A. Weil and W. Rosen, Chocolate to Morphine: Understanding Mind-Active Drugs, Houghton Mifflin, Boston, 1983. 11. A. Weil, The Natural Mind: An Investigation ofDrugs and the Higher Consciousness, Houghton Mifflin, Boston, 1986. 12. M. Goodstadt and M. Sheppard, Three Approaches to Alcohol Education, Journal of Studies on Alcohol, 44, pp. 362-380,1983. 13. National Institute on Drug Abuse, Prevention Planning Workbook, ( D H H S Publication No. (ADM)81-1062), U.S. Government Printing Office, Washington, DC, 1981. 14. M. Goodstadt, Drug Education: The Prevention Issues, Journal of Drug Education, I9:3, pp. 197-208,1989. 15. M. Fishbein and I. Azjen, Belief; Attitude, Intention and Behavior: An Introduction to Theory and Research, Addison-Wesley, Reading, Massachusetts, 1975. 16. A. P. Sullivan, R. Guglielmo, and P. Opperman, Measuring and Interpreting SchoolBased Prevention Outcomes: The New York City Model, Journal ofDrug Education, 1612,pp. 181-190,1986. 17. 0.Ray and C. Ksir, Drugs, Society and Human Behavior, Mosby Co.,St. Louis, 1987.
Direct reprint requests to: Elizabeth W. Edmundson, Ph.D. Center for Health Promotion Research and Development EDA 3 University of Texas Austin, TX 78712
PERSONAL AND SOCIAL MOTIVATIONS AS PREDICTORS OF SUBSTANCE USE AMONG COLLEGE STUDENTS
TONY L. HADEN, PH.D. Southwest Texas State University, San Marcos, Texas ELIZABETH W. EDMUNDSON, PH.D. University of Texas, Center for Health Promotion, Research and Development, Austin
ABSTRACT
The Drug Use Survey was administered via a direct mail to a simple random sample of 2200 students enrolled at a large southwestern U.S. university. A purpose of the study was to determine the predictability of self-reported drug use utilizing motivations (personal and social) commonly reported by substance users. Two subscales were developed, one for each category of motivations. Reliability for each subscale as estimated by coefficient alpha was 80 and .86, respectively. A series of step-wise multiple regression analyses were computed in which individual drug use indices served as criterion variables, while the predictor variables were the personal motivations subscale (PMS) and the social motivation subscale (SMS) for each model. The results indicated that the PMS was the stronger predictor in every model with the exception of the model that predicted the alcohol use index. The SMS was the best predictor for alcohol use.
Among college students who use psychoactive drugs, the primary substance of choice is alcohol, with marijuana a distant second and other recreational drugs an even more distant third [l-31. While the national media focuses on the use of crack cocaine and the negative health and behavioral effects associated with it, college campuses continue to experience the traditional use of alcohol by the vast majority of students [2-31. Since the 1960s, marijuana has remained a secondary, but significant, substance of choice with approximately half as many students using 303 8 1991, Baywood Publishing Co., Inc.
doi: 10.2190/WC1D-7XHR-ATQJ-81NP http://baywood.com
304 / HADEN AND EDMUNDSON
the drug on a regular basis as use alcohol. The remaining substances used recreationally by college students are done so on a limited basis relative to alcohol. The multifaceted nature of drug taking behavior is reflected in part by the commonly reported yet diverse motivations associated with various patterns of drug use [4-111. Motivations such as curiosity, a desire to alter consciousness, exploration of the self, facilitation of social interaction, stimulation of artistic creativity, enhancement of sensory experience and pleasure appear to be more associated with recreational patterns of use. Motivations that seem to be connected to problematic relationships with drugs include boredom, rebellion against societal expectations, peer pressure, and relief from emotional or physical pain. More specifically, theoretical discussions of the notion that individuals use different drugs for different reasons are popular in textbooks and conference papers, yet little evidence of systematic, data-based research on this issue has been published. The educational model of substance abuse prevention relies heavily upon the dissemination of information concerning the adverse consequences of substance misuse in order to counteract the motivations for drug use [4, 12, 131. One weakness of this approach is that the potential negative consequences of drug use are more often related to very heavy and long-term use rather than the pattern of use most commonly found among college students. Additionally, motivations for drug use are not the reciprocal of the motivations for abstinence [14]. By directly addressing the motivations for use, educational interventions would not have to rely upon the limited persuasiveness of potential adverse consequences messages. The efficacy of education as a mitigator of substance abuse is predicated on individuals internalizing the information on both the belief and attitudinal levels [151. The tenuous relationship between education and behavior is accentuated in college students due to their resiliency and the absence of chronic adverse effects of drug use, both attributable to their youth [16]. In addition, the pleasurable outcomes which often result from substance use frequently reinforces students’ motivations for using drugs. Thus, quite understandably, the positive consequences of substance use often outweigh the negative consequences among this population. If education is to be effective in preventing substance abuse, it is imperative that the motivations for substance use be empirically determined and objectively reported. Assumptions concerning the motivations for substance use based upon anecdotal, experiential, and intuitive evidence are seductive, but undermine the credibility of abuse prevention programs. Therefore, the intent of this study was to determine the predictability of substance use among college students utilizing self-reported personal and social motivations. Information concerning the relationship between substance use and its motivations has direct abuse prevention implications. Specifically, the ability of programs to intervene at the primary prevention level depends upon an understanding of the underlying motivational factors that correspond to the use of specific psychoactive substances.
MOTIVATIONS AS PREDICTORS OF SUBSTANCE USE / 305
METHODOLOGY A major institutional research survey on student drug use was conducted at a large, public southwestern university. The survey was mailed to a simple random sample of 2200 students with one follow-up letter. Respondents returned the survey via a stamped addressed envelope that was included in the packet. A cover letter explained the purpose of the survey and ensured the students that participation was completely voluntary and anonymous. The net response totalled 1013 or a 46.04 percent response rate. A comparison of the sample’s demographic statistics indicated the sample mirrored the student population’s demographic parameters. Table 1 contains the demographic characteristics the sample.
Instrument The survey instrument consisted of 174 items that purported to measure: 1) personal substance use behavior (frequency, intensity, duration); 2) perceived substance use behavior of other students; 3) frequency of behaviors associated with substance use; 4) motivations for substance use; 5) consequences of substance use; 6) attitudes toward substance use relative to school and health; 7) demographics; and 8) miscellaneous items. The substances of interest to the study included alcohol, marijuana, cocaine, amphetamines, barbiturates, tranquilizers, psychedelics, and designer drugs (e.g., MDA, MDMA). The Motivations for Substance Use section of the survey contained a response category whereby the respondent could indicate that he/she was not a current user of any substance. Thus, all analyses involving the motivation items included only those respondents that reported to be current drug users.
Analyses The Motivations for Substance use section of the survey consisted of eleven Likert-type items covering a variety of specific reasons associated with alcohol and other drug use. Respondents were asked to indicate the importance of each reason as a motivator for their use of alcohol and other drugs. The response categories for each item had three levels which ranged from not important, moderately important, to very important. For the purposes of this study the motivation items were grouped into two subscales, personal motivations (eight items) and social motivations (three items) (see Table 2). The Personal Substance Use Behavior section of the survey consisted of three facets of drug use: 1)frequency of use; 2) intensity of effects of use; and 3) duration of effects of use. Due to differences in the pharmacology of the substances of interest, comparison among the substances on only one facet or of each facet individually could be very misleading. Therefore, an index comprised of the three facets of drug use was computed for each of the substances.
306 / HADEN AND EDMUNDSON
Table 1. Biographic Background Characteristics of Study Sample (n = 1013) Variable
Frequency
Percent
489 523
48.3 51.6
223 31a 177 91 204
22.0 31.4 17.5 9.0 20.1
Class Freshman Sophomore Junior Senior Graduate
147 1 a3 21 1 235 236
14.5 18.1 20.8 23.2 23.3
Race Asian/Oriental Black White/Caucasian Hispanic Other
68 33 a09 97 6
6.7 3.3 79.9 9.6 .5
25 129 280 275 305
2.5 12.7 27.6 27.1 30.1
175 7 16 a1 4
17.3 0.7 1.6 80.4
Gender Male Female Age
19 years or younger 20-21 22-23 24-25 26 years or older
Grade-Point Average
0.00-1.99 2.00-2.49 2.50-2.99 3.00-3.49 3.50-4.00 Marital Status MarriedKohabitating Separated Divorced Never Married
MOTIVATIONS AS PREDICTORS OF SUBSTANCE USE / 307
Table 2. Motivations for Substance Use Sub-scales The reasons I use alcohol and/or other drugs are:
Personal Motivation Sub-scale
Social Motivation Sub-scale
pl p2 p3 p4 p5 p6
sl
p7
to experiment to relax to get away from my problems to escape boredom to get to sleep because of bad moods to feel better about myself
s2
s3
to have a good time with friends to fit in with the group I like to celebrate
The Statistical Package for the Social Sciences (SPSS) was utilized to compute eight step-wise multiple regression analyses, with the motivation subscales serving as the predictor variables in each of the models. One of the eight substance use indexes served as the criterion variable in each model. A potential problem inherent in using both of the motivation subscales as predictor variables was the possibility of an intercorrelation between them that could result in their absolute impact being masked. Although the subscales had no items in common, some of the items have enough characteristics in common so as to make the question of multicollinearity salient. Although the correlation between the subscales was not high enough to support a claim of unidimensionality (r = .67),it was high enough to warrant further analysis into the construct (factorial) validity of the subscales. Therefore, a principal components analysis of the motivation items was conducted followed by varimax rotation of the components with eigenvalues greater than one. RESULTS
The internal consistency reliability estimate using Cronbach’s coefficient alpha for the entire instrument was found to be .96. Cronbach’s coefficient alpha provided estimates of reliability, .SO and .S6, for the personal and social motivations subscales, respectively. The descriptive statistics for the Motivation of Substance Use subscales indicated that the social motivation items were slightly stronger than the personal motivation items. On a scale of 0-3 with a score of 3 representing the strongest motivational level for an item, the social motivation items had a relative mean of 2.54 with a standard deviation of .57, compared to the personal motivation items that had a relative mean of 2.00 with a standard deviation of .69.
308 / HADEN AND EDMUNDSON
As with the motivation subscales, the substance use indexes evidenced acceptable reliability estimates, with coefficient alpha ranging between .75 and .96. Descriptive statistics for the substance use indexes and the intercorrelation matrix for the indexes are presented in Table 3. The results of the principal components analysis of the motivation item suggest that the eleven items constituted two factors (see Table 4). The eight personal motivation items had the highest factor loadings on factor one, and the three social motivation items had the highest factor loadings on factor two. Therefore, while it was never presumed that the subscales represented two separate unidimensional constructs, it does appear that they did represent two facets of motivation that were sufficiently discrete to warrant statistical comparison. A series of stepwise multiple regression models were analyzed in which the eight substance use indexes each served as the criterion variable (see Table 5). The predictor variables for every regression model were the Personal Motivation Subscale (PMS) and the Social Motivation Scale (SMS). The degree of predictability of the motivation subscales varied from substance to substance. In general, Table 3. Descriptive Statistics of Substance Use Indexes (Score range 0-15; N = 842) Substance Use Index
Mean
Std. Dvn.
Coef Alpha
Alcohol Marijuana Cocaine Amphetamine Barbiturate Tranquilizer Psychedelics Designer drugs
7.55 3.44 1.47 1.14 .48
2.02 3.58 2.90 2.58 1.68 1.83 3.27 3.39
.75 .93 .94
.68 1.49 1.68
.93
.91 .90 .96 .96
Pearson Correlation Coefficients Among Substance Use Indexes
Alcohol Marijuana Cocaine Amphetamine Barbiturate Tranquilizer Psychedelics Designer drugs
Alc.
Mar.
1.oo .47 .30 .25 .15 .16 .22
1.00 .59 .51 .30 .35
.33
.53 51
COC. Amp.
1.00 .72 .46 .45 .66 .60
1.00 .57
.50 .61 .55
Bar.
Tra.
Psy.
D.D.
1.00 .69 .44 .42
1.00 S3 .38
1.00 55
1 .OO
MOTIVATIONS AS PREDICTORS OF SUBSTANCE USE / 309
Table 4. Principal Components Analysis of the Motivationsfor Drug Use Items ~~
Variable
Factor 1
Factor 2
Pl
.3962 .4608 1932 5449 .7356 .7339 .6597 .7591 .7460 .2133
.2963 .3850 .7615 .7373 .2629 .2970 .1413 .1929 .1959 .7391
P2 sl s2 P3 P4 P5 P6
P7 s3
.
the PMS proved to be the stronger predictor of the two scales in that it was either the first or only variable that entered into seven of the eight regression equations. Every prediction model was statistically significant at thep c ,0001 level. The regression analysis for which the Alcohol Use Index was the criterion variable resulted in a two variable model in which the SMS was the strongest predictor. This regression model had a Multiple R value of .72 and an adjusted R-Squared value of .51. Alcohol use proved to be the most predictable of the substance use behaviors. The regression model for which the Marijuana Use Index was the criterion variable resulted in a two variable equation in which the PMS was the stronger predictor. As noted by Table 5 , this regression model yielded a Multiple R value of .41 and an adjusted R-Squared value of .17. Marijuana use was the second most predictable of the substance use behavior indexes. Other regression models in which both predictor variables entered into the equation and which the stronger predictor was the PMS included those for the Barbiturate and the Tranquilizer Use Indexes. However, neither model proved to have substantial predictiveness, with Multiple R values of .25 and .27 and Adjusted R-Square values of .06 and .07, respectively. The regression models for which the Cocaine, Amphetamine, Psychedelics and Designer Drug Use Indexes were each the criterion variable resulted in only the PMS entering into the equations at a significant level. However, those four equations yielded R-Square values that also indicated limited contributions to the predictability of the criterion variable. Thus, while alcohol use was very predictable using the SMS and marijuana use was moderately predictable using the PMS, the remaining six substances were very difficult to predict from either social or personal motivations. The
310 / HADEN AND EDMUNDSON
Table 5. Summary Statistics Associated with the Stepwise Multiple Regression Analysis Personal and Social Motivation Sub-scales by Substance Use Index (n = 863) ~
Step
Variable Entered
Model R2
Multiple R
F-Ratio
p-Value
Dependent Variable = Alcohol Index
1 2
Social motivations Personal motivations
0.3242 0.3470
0.5694 0.5890
452.47 250.31
0.0001
0.0001
Dependent Variable = Cocaine Index
1 2
Personal motivations Social motivations
0.0753 0.0914
0.2744 0.3024
19.13 11.77
0.0001 0.0001
Dependent Variable = Marijuana Index 1 2
Personal motivations Social motivations
0.091 1 0.0976
0.3019 0.3124
55.55 29.91
0.0001 0.0001
Dependent Variable = Tranquilizer Index 1
Personal motivations
0.0753
0.2745
12.71
0.0005
Dependent Variable = Designer Drugs Index
1
Personal motivations
0.0509
0.2255
10.56
0.0014
Dependent Variable = Psychedelics Index 1
Personal motivations
0.0481
0.2193
9.50
0.0024
Dependent Variable = Barbiturate Index 1
Personal motivations
0.0946
0.3075
10.45
0.0017
Dependent Variable = Amphetamine Index
1
Personal motivations
0.0839
0.2896
18.95
0.0017
general low levels of usage among substances other than alcohol and marijuana was a likely factor in the inability of the motivation subscales to adequately predict usage. Although the regression models for alcohol and marijuana use resulted in two-predictor variable equations, in each model the variable that was entered second contributed little to the overall predictiveness of the model.
MOTIVATIONSAS PREDICTORS OF SUBSTANCE USE / 31 1
CONCLUSI 0NS
The results of the descriptive statistics for both motivation subscales indicate that, with the exception of alcohol, college students use drugs more for personal reasons than for social reasons. Thus, primary prevention programs should be directed toward the personal aspects of drug use. However, given the strength of the SMS as a predictor of alcohol use and the fact that alcohol is the overwhelming drug of choice among college students, it appears that prevention efforts should also be directed toward addressing the social motivations for drinking. The results found in this study also indicate a need for more research, given that students’ motivations for substance use varied across specific drugs and therefore may vary across other variables. Moreover, the complexity of substance use behavior warrants abuse prevention efforts that should be tailored to the context. In the case of motivation, there appears to be a difference in the type of reasons why students use alcohol compared to other drugs. Thus, there should be a corresponding difference in the way prevention programs address the use of alcohol versus other recreational drugs. Finally, it should be noted that research indicates that junior high school and high school students use all drugs for primarily social reasons [17]. The results of this study suggest that a fundamental shift in motivations of substance use occurs among students as they mature and enter college such that personal motivations increase in their influence on drug use behavior. The change in emphasis from social to personal motivations for drug use may be consistent with the stage of human development that characterizes most students’ college experience.
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8. B. Segal, G. J. Huba, and J. L. Singer, Reasons for Drug and Alcohol Use by College Students, The International Journal of thedddictions, 15~4,pp. 489498,1980. 9. R. Siege], Intoxication: Life in Pursuit ofArtificia1 Paradise, E. P. Dutton, New York, 1989. 10. A. Weil and W. Rosen, Chocolate to Morphine: Understanding Mind-Active Drugs, Houghton Mifflin, Boston, 1983. 11. A. Weil, The Natural Mind: An Investigation ofDrugs and the Higher Consciousness, Houghton Mifflin, Boston, 1986. 12. M. Goodstadt and M. Sheppard, Three Approaches to Alcohol Education, Journal of Studies on Alcohol, 44, pp. 362-380,1983. 13. National Institute on Drug Abuse, Prevention Planning Workbook, ( D H H S Publication No. (ADM)81-1062), U.S. Government Printing Office, Washington, DC, 1981. 14. M. Goodstadt, Drug Education: The Prevention Issues, Journal of Drug Education, I9:3, pp. 197-208,1989. 15. M. Fishbein and I. Azjen, Belief; Attitude, Intention and Behavior: An Introduction to Theory and Research, Addison-Wesley, Reading, Massachusetts, 1975. 16. A. P. Sullivan, R. Guglielmo, and P. Opperman, Measuring and Interpreting SchoolBased Prevention Outcomes: The New York City Model, Journal ofDrug Education, 1612,pp. 181-190,1986. 17. 0.Ray and C. Ksir, Drugs, Society and Human Behavior, Mosby Co.,St. Louis, 1987.
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