Discerning the epidemiology of drug use among a sample of college students

Although estimates concerning the prevalence of various forms of substance abuse vary considerably, it is critical to note that even the more conservative estimates indicate a major public health problem. Furthermore, increased drug experimentation has been frequently associated with the college experience. Utilizing a slightly modified version of the National Institute on Drug Abuse (NIDA) Monitoring the Future Survey, the present study examined the epidemiology of self-reported drug taking behaviors (e.g., alcohol, marijuana, tranquilizers, stimulants, psychedelics, etc.) among a sample (n = 683) of students attending a major public university. Data analyses focused on the specific settings and social groupings in which drug use occurred as well as on the frequency and type(s) of drug taking behaviors. Based on the results yielded from a disjoint cluster analysis, four distinct groups of drug users were identified. These four groups then served as categories of the dependent variable in a discriminant function analysis. A general linear models procedure was employed to identify the more efficacious discriminating (i.e., independent) variables.     

Using process data to explain outcomes. An illustration from the Child and Adolescent Trial for Cardiovascular Health (CATCH)

The purpose of this article is to illustrate the use of process evaluation for understanding study outcomes. Data from the Child and Adolescent Trial for Cardiovascular Health (CATCH), a large school-based field trial, are used. Teacher characteristics, measures of classroom curriculum implementation, and competing influences are linked to changes in dietary knowledge, intentions, and self-efficacy of students in the intervention schools. Multiple regression analyses indicate that teacher characteristics did not predict program implementation. Teacher characteristics and program fidelity, or the number of modifications made to the classroom curriculum during implementation, had direct and independent effects on student outcomes.     

Personal and social motivations as predictors of substance use among college students.

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.