Drug use related problems among nonmedical users of prescription stimulants: A web-based survey of college students from a Midwestern university

Drug and Alcohol Dependence 91 (2007) 69–76

Drug use related problems among nonmedical users of prescription stimulants: A web-based survey of college students from a Midwestern university Sean Esteban McCabe a,∗ , Christian J. Teter b,c a

University of Michigan Substance Abuse Research Center, 2025 Traverwood Dr., Suite C, Ann Arbor, MI 48105-2194, USA b Northeastern University School of Pharmacy, 203 Mugar Life Sciences Building, Boston, MA 02115-5000, USA c McLean Hospital, Alcohol and Drug Abuse Treatment Program, 115 Mill St., Belmont, MA 02478, USA Received 19 June 2006; received in revised form 4 May 2007; accepted 14 May 2007

Abstract This college-based study compared nonmedical users of prescription stimulants to other types of drug users regarding drug use related problems. A Web survey was self-administered in 2005 by a probability sample of 3639 full-time undergraduate students (68% response rate) at a large public Midwestern 4-year university in the United States. The survey consisted of measures to assess substance use and misuse, including a modified version of the Drug Abuse Screening Test (DAST-10). Nonmedical users of prescription stimulants were more likely than other drug users to report polydrug use. Nonmedical users of prescription stimulants had over four times greater odds than other drug users to experience three or more DAST-10 items in the past 12 months (AOR = 4.61, 95% CI = 3.28–6.48). Among nonmedical users of prescription stimulants, those who used prescription stimulants via intranasal and other non-oral routes of administration had greater odds than oral only users to experience three or more DAST-10 items in the past 12 months. The findings of the present study suggest that the majority of nonmedical users of prescription stimulants are polydrug users and should be screened for potential drug abuse or dependence, especially those who report non-oral routes of administration. © 2007 Elsevier Ireland Ltd. All rights reserved. Keywords: Prescription stimulants; Prescription drug abuse; Drug dependence; Screening; Route of administration; College students

1. Introduction Although it is well accepted that prescription stimulants are highly effective treatment for attention deficit/hyperactivity disorder (ADHD) in children, adolescents, and adults (Greenhill et al., 2002; Spencer, 2004), there is a growing body of research documenting the nonmedical use, abuse and dependence on prescription stimulants among adolescents and young adults in North America (e.g., Barrett et al., 2005; Johnston et al., 2005a,b; Kroutil et al., 2006; Marsh et al., 2000; Substance Abuse and Mental Health Services Administration (SAMHSA), 2005a,b. The past year nonmedical use, abuse or dependence on prescription stimulants used to treat ADHD is most prevalent among young adults 18–24 years of age (e.g., Johnston et al., 2005b; Kroutil et al., 2006; McCabe et al., 2005; SAMHSA, 2005a). Among young adults, there is evidence to suggest

∗

Corresponding author. Tel.: +1 734 998 6500; fax: +1 734 998 6508. E-mail address: [email protected] (S.E. McCabe).

0376-8716/$ – see front matter © 2007 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.drugalcdep.2007.05.010

that the past-year nonmedical use of prescription stimulants (e.g., methylphenidate) may be more prevalent among college students as compared to their peers not attending college (Herman-Stahl et al., 2007; Johnston et al., 2005b). For purposes of this study, nonmedical use of prescription stimulants (NMUPS) refers to the use of a prescription stimulant by an individual without a physician’s prescription for the medication. To date, epidemiological research has established several important findings associated with the NMUPS among college students (e.g., Barrett et al., 2005; Hall et al., 2005; McCabe et al., 2006a; Teter et al., 2003, 2005; Upadhyaya et al., 2005; White et al., 2006). First, a recent college-based investigation found that the number of nonmedical users of prescription stimulants was greater than the number of medical users of prescription stimulants for ADHD among full-time undergraduate students attending a large public Midwestern university (McCabe et al., 2006a). Second, the leading motivations associated with NMUPS among college students are to (1) improve concentration/attention, (2) increase alertness, (3) help study and (4) use for recreational purposes (e.g., to get high) (Barrett

70

S.E. McCabe, C.J. Teter / Drug and Alcohol Dependence 91 (2007) 69–76

et al., 2005; Hall et al., 2005; Teter et al., 2005, 2006; White et al., 2006). Third, NMUPS is highly correlated with other drug use behaviors among adolescents and young adults (Barrett et al., 2005; Teter et al., 2003; McCabe et al., 2004, 2005, 2006b; SAMHSA, 2006), regardless of the motive associated with nonmedical use (Teter et al., 2005). Collegiate nonmedical prescription stimulant users are more likely to report use of alcohol, cigarettes, marijuana, cocaine, and other drugs than their non-stimulant using peers (McCabe et al., 2005, 2006b; Teter et al., 2003, 2005). For example, over 80% of nonmedical users of prescription stimulants reported marijuana use in the past year as compared to approximately 30% of non-stimulant users (McCabe et al., 2005; Teter et al., 2005). Finally, approximately 40–50% of collegiate nonmedical users of prescription stimulants report using these drugs via the intranasal route of administration (Barrett et al., 2005; Teter et al., 2006; White et al., 2006). Based on the high rates of non-oral administration that have been documented among college students, NMUPS should be taken very seriously as a potential public health problem. It has been well-established that alterations in the pharmacokinetics of a drug can significantly impact its abuse liability. More precisely, routes of administration that deliver drug to the brain faster are associated with greater reinforcing properties (Volkow and Swanson, 2003). Thus, students who engage in NMUPS via non-oral routes of administration may be placing themselves at higher risk for developing substance use disorders. However, the long-term consequences associated with human exposure to psychostimulants are not well understood and seem to depend on multiple variables, in addition to route of administration, such as age of exposure and dose administered (Fone and Nutt, 2005). Although previous epidemiological studies have increased our understanding of the prevalence, motives and routes of administration associated with NMUPS, several important issues remain unexamined on the topic of prescription stimulant abuse and dependence. First, more research is needed to determine the extent of drug use related problems among nonmedical users of prescription stimulants. Among the few brief screening instruments to detect probable drug abuse or dependence for drugs other than alcohol, the Drug Abuse Screening Test (DAST-10) offers promise because it has been used in clinical and non-clinical settings to detect drug use related problems for drugs other than alcohol (Cocco and Carey, 1998; Skinner, 1982). While the DAST-10 items are not stimulant-specific and the clinical significance of a web-based version of the DAST-10 remains unknown, the DAST-10 is a well-validated instrument that has the ability to identify individuals who need more intensive assessment for substance abuse problems (Cocco and Carey, 1998). Second, there is scant information available regarding routes of administration associated with NMUPS (Compton and Volkow, 2006). Such information will help inform the development of prevention strategies to reduce the abuse and diversion of prescription stimulants. The main objectives of the present study were to (1) compare drug use related problems between nonmedical users of prescription stimulants and other types of drug users in an attempt to identify the characteristics specifically associated with NMUPS versus other types of drug use;

and (2) examine drug use related problems among nonmedical users of prescription stimulants as a function of route of administration. 2. Methods 2.1. Study design This investigation was part of a larger study of college students conducted in January and February of 2005. After receiving Institutional Review Board approval, a random sample of 5389 full-time undergraduate students was drawn from the total undergraduate population of 20,138 full-time students (10,339 women and 9799 men) at a large Midwestern university. The entire sample was mailed a pre-notification letter with $2 enclosed describing the study and inviting students to self-administer a Web survey by using a URL address and unique password. Informed consent was obtained online from each participant. Non-respondents were sent up to four reminder e-mails. The Web survey was maintained on an Internet site running under the secure socket layer protocol to ensure privacy and security. By participating in the survey, students became eligible for a sweepstakes that included cash and other prizes. The final response rate was 68%.

2.2. Sample The sample consisted of 3639 undergraduate students. The demographic characteristics of the sample closely resembled the overall student population of the university. As illustrated in Table 1, the sample consisted of 53.6% women and 46.4% men. The racial/ethnic distribution of the sample was 67.4% White, 12.1% Asian, 6.0% African American, 4.5% Hispanic and 10.2% from other ethnic categories. The sample was made up of 28.5% freshmen, 23.4% sophomores, 23.1% juniors and 25.0% seniors. The mean age of students in the sample was 19.9 years old (S.D. = 2.0). Table 1 illustrates demographic characteristics for the overall sample, broken down by past year drug use status: nonmedical use of prescription stimulants (n = 212) or drug use other than nonmedical use of prescription stimulants (n = 1164) including marijuana, cocaine, LSD, psychedelics other than LSD, heroin, crystal methamphetamine, inhalants, ecstasy, and nonmedical use of pain medication, sleeping medication and sedative/anxiety medication.

2.3. Measures Nonmedical use of prescription stimulants was assessed with the following question: “On how many occasions in (a) your lifetime or (b) the past 12 months have you used the following types of drugs, not prescribed to you?” Stimulant medication (e.g., Ritalin, Dexedrine, Adderall, Concerta, methylphenidate). Consistent with previous research, the response scale ranged from (1) No occasions to (7) 40 or more occasions (Johnston et al., 2005a,b). According to our definition, nonmedical users of prescription stimulants were also allowed to report the use of other drugs (not including alcohol) in the past year, as will be discussed in further detail. Past year other drug use—including marijuana, cocaine, LSD, psychedelics other than LSD, heroin, crystal methamphetamine, inhalants, ecstasy, and nonmedical use of pain medication, sleeping medication and sedative/anxiety medication—was measured with the following question for each substance: “On how many occasions in the past 12 months have you used the following types of drugs?” The response scale for each substance was (1) no occasions to (7) 40 or more occasions. For purposes of analyses, the use of any of the 11 substances in the past year was summed to create an index of past year drug use. Routes of administration were assessed by asking respondents who reported nonmedical use of prescription stimulants to indicate the route(s) of administration they used for taking prescription stimulants not prescribed to them by a doctor. Respondents were asked to select all that apply from a list of five routes including (1) orally, (2) snorting, (3) smoking, (4) injecting, and (5) inhaling. For purposes of analyses, a three-level indicator variable was created for route of administration consisting of oral only, intranasal and oral, and other routes of administration.

S.E. McCabe, C.J. Teter / Drug and Alcohol Dependence 91 (2007) 69–76

71

Table 1 Sample characteristics for overall sample, past-year nonmedical users of prescription stimulants and other drug users Overall sample (n = 3639, %)

Past-year nonmedical users of prescription stimulants (n = 212, %)

Past-year other drug usersa (n = 1164, %)

Gender Female Male

53.6 46.4

48.1 51.9

54.4 45.6

Race/ethnicity African American Asian Hispanic White Other

6.0 12.1 4.2 67.4 10.2

1.9 6.1 5.7 80.2 6.1

5.1 7.2 5.4 73.3 8.9

Class year Freshmen Sophomore Junior Senior

28.5 23.4 23.1 25.0

23.1 26.4 21.2 29.2

29.9 23.8 20.7 25.6

Family income Less than $50,000 $50,000–$99,999 $100,000–$149,999 $150,000–$249,999 $250,000 or more Don’t know/rather not say

12.4 23.0 17.9 11.8 9.2 25.8

6.6 19.8 17.9 15.1 16.5 24.1

10.9 21.4 17.0 13.9 13.5 23.2

Living arrangement Residence hall Fraternity/sorority house House/apartment Otherb

46.5 4.4 43.7 5.4

31.1 8.5 57.5 2.8

42.5 6.1 46.5 4.9

Fraternity/sorority status Member Non-member

14.5 85.5

27.8 72.2

20.0 80.0

a Other drug use consisted of marijuana, cocaine, LSD, psychedelics other than LSD, heroin, crystal methamphetamine, inhalants, ecstasy, and nonmedical use of prescription pain medication, sleeping medication and sedative/anxiety medication. b Other living arrangement includes individuals living outside the university town and any other locations.

Drug use related problems were assessed with a modified version of the Drug Abuse Screening Test (DAST-10), a self-report instrument that can be used in clinical and non-clinical settings to screen for potential abuse and dependence on a wide variety of substances other than alcohol (Skinner, 1982). Respondents who used drugs other than alcohol in the past 12 months were asked whether they had experienced any of the DAST-10 items in the past 12 months. Respondents were informed that “drug” refers to use of prescription drugs not prescribed to you or in a manner not intended by the prescribing clinician, or use of other drugs such as marijuana, cocaine, LSD, ecstasy, etc. Cronbach’s alpha for the DAST10 was 0.69. Based on previous research, if a respondent indicated that they had experienced three or more DAST-10 items, this was considered a “positive” screening test result, denoting potential drug abuse or dependence (Cocco and Carey, 1998; French et al., 2001; Maisto et al., 2000; Skinner, 1982). Previous work indicated cutoff scores of either a 3 or 4 for the DAST-10 yielded levels of sensitivity and specificity of 0.74 and 0.86, respectively, using DSM-III-R drug use disorder diagnosis as the criterion (Cocco and Carey, 1998). Maisto et al. (2000) also evaluated the DAST-10 using DSM-IV drug use disorder diagnosis as the criterion and found levels of sensitivity and specificity of 0.70 and 0.80, respectively, when using a cutpoint of 3.

were tested using chi-square analyses for dichotomous and categorical outcomes. In addition, one-way analyses of variance (ANOVA) and post hoc pairwise comparisons using Tukey’s Honestly Significant Difference (HSD) tests were conducted for continuous outcomes. Multiple logistic regression analyses were conducted to examine the associations between NMUPS status (i.e., NMUPS versus past year use of other drugs) and drug use-related problems. In these analyses, NMUPS status was treated as an independent variable (1 = NMUPS, 0 = other drug use) and separate models were estimated for each of the DAST10 items. All analyses statistically controlled for student characteristics and other factors (e.g., gender, race, class year, family income, living arrangement, fraternity/sorority membership, age of onset for use of alcohol, tobacco and marijuana) that were significantly associated with NMUPS based on (a) previous research (e.g., Johnston et al., 2005a,b; McCabe et al., 2005, 2006a; Teter et al., 2003) and (b) bivariate associations in the present study. Adjusted odds ratios (AOR) and 95% confidence intervals (95% CI) were reported. All statistical analyses were performed using SPSS 13.0 statistical software.

2.4. Data analysis

3.1. Nonmedical use of prescription stimulants and other drug use

Prevalence rates of nonmedical use and routes of administration associated with NMUPS were derived by dividing the number of students reporting an outcome behavior by the total number of respondents to that question. Bivariate associations between student characteristics and drug outcome prevalence rates

3. Results

The lifetime prevalence of NMUPS was 8.5% and the pastyear prevalence of nonmedical use was 6.0%. Overall, the

72

S.E. McCabe, C.J. Teter / Drug and Alcohol Dependence 91 (2007) 69–76

past-year prevalence of NMUPS was higher than the past-year nonmedical use of psychedelics other than LSD (4.2%), cocaine (3.5%), sedative/anxiety medication (2.6%), sleeping medication (2.4%), ecstasy (1.7%), inhalants (1.5%), LSD (0.8%), crystal methamphetamine (0.3%) and heroin (0.1%) but lower than the past-year prevalence of nonmedical use of marijuana (35.5%) and pain medication (7.4%). Of the 301 undergraduate students who reported lifetime NMUPS, 40.2% used on 1 to 2 occasions, 21.9% used on 3 to 5 occasions, 13.3% used on 6 to 9 occasions, 24.6% used on 10 or more occasions. Of the 212 undergraduate students who reported past-year NMUPS, 39.2% used on 1 to 2 occasions, 31.6% used on 3 to 5 occasions, 11.3% used on 6 to 9 occasions, and 17.9% used on 10 or more occasions. To place this into a larger context of drug use, of the 1253 undergraduate students who reported past-year use of marijuana, 32.5% used on 1 to 2 occasions, 18.7% used on 3 to 5 occasions, 10.4% used on 6 to 9 occasions, and 38.5% used on 10 or more occasions. There were several student characteristics that were significantly associated with past-year NMUPS and other drug use. Bivariate analysis indicated that race/ethnicity, family income, living arrangement, and fraternity/sorority membership were all significantly associated with NMUPS. These same demographic variables were also significantly associated with other drug use. Neither gender nor class year were significantly associated with NMUPS or other drug use. Over 90% of students who reported past-year NMUPS also reported using other drugs (not including alcohol) in the past year. In contrast, approximately 20.8% of individuals who used drugs other than prescription stimulants (“other drug users”) used multiple drugs (not including alcohol) in the past year. Approximately 89.9% of students who reported past-year NMUPS also reported past-year marijuana use. The frequency of past-year marijuana use among past-year nonmedical users of prescription stimulants (n = 187) was as follows: 7.5% used on 1 to 2 occasions, 15.0% used on 3 to 5 occasions, 7.5% used on 6 to 9 occasions, and 70.0% used on 10 or more occasions. The frequency of NMUPS was associated with drug use related problems based on the DAST-10. Among past-year nonmedical users of prescription stimulants (n = 212), experiencing three or more DAST-10 items was reported by 42.2% of those who used on 1 to 2 occasions, 58.2% (3 to 5 occasions), 58.3% (6 to 9 occasions), and 76.3% of those who used on 10 or more occasions (χ2 = 12.9, df = 3, p < 0.01). A similar pattern was observed for the frequency of other drug use. For example, among pastyear users of marijuana, experiencing three or more DAST-10 items was reported by 9.9% of those who used on 1 to 2 occasions, 16.3% of those who used on 3 to 5 occasions, 21.7% of those who used on 6 to 9 occasions, and 46.4% of those who used on 10 or more occasions. There were significant bivariate and multivariate associations in every DAST-10 item between past-year nonmedical users of prescription stimulants and other types of drug users with the exception of the inability to stop using drugs (see Table 2). For example, past-year nonmedical users of prescription stimulants were more likely than other drug users to have reported simultaneous polydrug use (53.8% versus 16.9%, p < 0.001),

Fig. 1. Past-year drug use related problems among past-year nonmedical users of prescription stimulants and other drug users.

experienced blackouts as a result of drug use (21.7% versus 8.3%, p < 0.001), engaged in illegal activities to obtain drugs (27.4% versus 9.3%, p < 0.001), and experienced withdrawal symptoms when they stopped taking drugs (14.6% versus 2.5%, p < 0.001). As illustrated in Fig. 1 and Table 2, past-year nonmedical users of prescription stimulants reported experiencing three or more DAST-10 items in the past 12 months at higher rates than other drug users (55.2% versus 19.4%, p < 0.001). Multiple logistic regression analysis indicated that past-year nonmedical users of prescription stimulants were over four times more likely than other drug users to experience three or more DAST10 items after adjusting for gender, race/ethnicity, class year, family income, living arrangement and fraternity/sorority membership, age at onset for use of alcohol, tobacco and marijuana (AOR = 4.61, 95% CI = 3.28–6.48). ANOVA showed a main effect for NMUPS, F(1, 1372) = 170.92, p < 0.001, and post hoc tests indicated the mean DAST-10 score for past year nonmedical users of stimulants (M = 3.15, S.D. = 2.05) was significantly higher than the mean DAST-10 score of other past year drug users (M = 1.64, S.D. = 1.43). Furthermore, nonmedical users of prescription stimulants were more likely than other drug users to report using multiple drugs used in the past year (concurrent polydrug use). ANOVA showed a main effect for NMUPS, F(1, 1374) = 929.0, p < 0.001, and post hoc tests indicated the mean number of drugs among nonmedical users of prescription stimulants (M = 3.79, S.D. = 2.15) was significantly higher than other types of drug users (M = 1.32, S.D. = 0.75). 3.2. Route of administration and drug use related problems Among past-year nonmedical users of prescription stimulants (n = 212), approximately 58.5% reported an oral only route of administration of prescription stimulants, 34.9% reported intranasal and oral administration and 6.6% reported other routes of administration (e.g., injecting, smoking and inhaling). Bivariate analysis revealed approximately 36.3% who reported only oral administration experienced three or more DAST-10 items as compared to 81.1% of intranasal and oral users, and 85.7% of those who reported other routes of administration (χ2 = 43.24, df = 3, p < 0.001). Multivariate logistic

S.E. McCabe, C.J. Teter / Drug and Alcohol Dependence 91 (2007) 69–76

73

Table 2 Past-year drug use related problems among nonmedical users of prescription stimulants and other drug users DAST-10 itemsa

Have you used drugs other than those required for medical reasons? Have you used more than one drug at a time? Are you always able to stop using drugs when you want to?d Have you had blackouts or flashbacks as a result of drug use? Have you ever felt bad or guilty about your drug use? Have family members ever complained about your involvement with drugs? Have you stayed away from your family because of your use of drugs? Have you engaged in illegal activities in order to obtain drugs? Have you ever experienced withdrawal symptoms (felt sick) when you stopped taking drugs? Have you had medical problems as a result of your drug use (e.g., memory loss, hepatitis, convulsions, bleeding)? At least three DAST-10 items Mean DAST-10 score

Past-year nonmedical users of prescription stimulants (n = 212)

Past-year other drug users (n = 1164)b

Differences between NMUPS and other drug users

Unadjusted (%)

Unadjusted (%)

Adjusted OR (95% CI)c

92.5

69.7

6.71 (3.67–12.27)***

53.8

16.9

5.42 (3.82–7.69)***

14.2

14.4

0.85 (0.55–1.33)

21.7

8.3

2.34 (1.54–3.56)***

47.6

29.2

2.10 (1.53–2.88)***

20.3

6.0

3.02 (1.93–4.73)***

15.1

5.1

2.34 (1.43–3.83)**

27.4

9.3

2.82 (1.90–4.18)***

14.6

2.5

5.57 (3.13–9.92)***

7.5

2.2

2.83 (1.43–5.61)**

55.2 Mean = 3.15 (S.D. = 2.05)

19.4 Mean = 1.64 (S.D. = 1.43)

4.61 (3.28–6.48)***

**p < 0.01, ***p < 0.001. a DAST-10 = Drug Abuse Screening Test. b Other drug use refers to nonmedical use of marijuana, cocaine, LSD, other psychedelics, crystal methamphetamine, heroin, inhalants, ecstasy, sleeping medication, sedative/anxiety medication and/or pain medication. c Logistic regression analysis used “past-year other drug users” as the reference group and adjusted for gender, race, class year, family income, living arrangement, fraternity/sorority membership, age at onset of cigarette smoking, alcohol use, and marijuana use. d Prevalence indicates percentage of respondents who indicated a “no” response.

regression analyses adjusted for demographic variables (e.g., gender, class year, race/ethnicity, family income, living arrangement and fraternity/sorority membership, age at onset for use of alcohol, tobacco and marijuana) revealed nonmedical users of prescription stimulants who reported intranasal administration (AOR = 9.02, 95% CI = 3.53–23.08, p < 0.001) and other non-oral routes administration (AOR = 18.08, 95% CI = 3.08–106.17, p < 0.01) had at least nine times greater odds of experiencing three or more drug use related problems in the past year as compared to nonmedical users who reported oral administration only. 4. Discussion The results from the present study provide strong evidence that nonmedical users of prescription stimulants are more likely than other drug users to report polydrug use. Indeed, the majority of nonmedical users of prescription stimulants co-ingested multiple drugs at the same time (i.e., simultaneous polydrug use). The finding that nonmedical users of prescription stimulants report higher rates of polydrug use is consistent with other evidence that has found high rates of concurrent substance use among nonmedical users of prescription stimulants (Barrett et

al., 2005; McCabe et al., 2004, 2005; SAMHSA, 2006; Teter et al., 2003). Collegiate nonmedical users of prescription stimulants are also more likely to report drug use related problems than other drug users. Nonmedical users of prescription stimulants have over four times greater odds than other drug users of experiencing three or more DAST-10 items in the past 12 months. Furthermore, nonmedical users of prescription stimulants are more likely than other drug users to report nine out of ten DAST-10 items. Clearly, the higher rates of polydrug use among nonmedical users of prescription stimulants as compared to other drug users contributes to increased odds of drug use related problems. Additionally, because the DAST-10 items are not stimulant-specific, the increased odds of drug use related problems among nonmedical users of prescription stimulants cannot be attributed directly to NMUPS. Nevertheless, NMUPS appears to be a behavior that serves as a marker for potential drug abuse, especially NMUPS via non-oral routes of administration as discussed below. Among nonmedical users of prescription stimulants, intranasal and other non-oral users were over nine times more likely than oral users to report three or more DAST-10 items. Indeed, more than four in every five non-oral users of prescrip-

74

S.E. McCabe, C.J. Teter / Drug and Alcohol Dependence 91 (2007) 69–76

tion stimulants experienced three or more DAST-10 items in the past year. Using prescription medications via routes of administration that rapidly deliver drug to the brain may be particularly dangerous, because the rate of delivery of drug to the brain directly correlates with the abuse potential of that drug (e.g., Compton and Volkow, 2006; Kollins, 2003; Roset et al., 2001; Volkow and Swanson, 2003). Epidemiological studies have helped improve our understanding of the relative abuse liability of prescription drugs among college students. For example, the nonmedical use/medical use ratio for stimulant medication among college students is much higher (2.45) than other classes of prescription drugs including pain medication (0.38), sleeping medication (0.91) or sedative/anxiety medication (0.85), suggesting stimulant medication is the only prescription drug class with a higher proportion of nonmedical users than medical users (McCabe et al., 2006b). Additionally, among college students, nonmedical users of prescription stimulants are considerably more likely to report non-oral routes of administration (e.g., intranasal) than nonmedical users of prescription opioids (McCabe et al., 2007; Teter et al., 2006). These findings certainly could reflect the likeability of each drug class among college students. However, it is important to remember that other variables (e.g., age of exposure, dose administered) likely impact a drug’s abuse potential (Fone and Nutt, 2005). Furthermore, due to inter-individual differences in drug response, it is certainly possible that a given individual may be particularly at risk for developing substance abuse. For example, it has been suggested that individuals with low expression of dopamine D2 receptors may be at higher risk for abusing stimulants (Volkow and Swanson, 2003). Therefore, it is important that the abuse liability of stimulant medications never be under-estimated in a given individual. Future research efforts should combine epidemiological research with evaluations of the impact of various absorption rate profiles to use a multi-disciplinary approach to assess each medication’s abuse liability. The present study contained both strengths and limitations that should be taken into account while considering the implications of the findings. First, one of the strengths of the present study is the inclusion of a reliable brief screening instrument (DAST-10) that has been used in clinical and non-clinical settings. Whereas previous work often failed to distinguish nonmedical use from abuse and dependence, the DAST-10 improved our understanding regarding selected drug use related problems among nonmedical users of prescription stimulants. Second, the sample was large enough to statistically examine several important characteristics and conduct multivariate analysis, although future research will need to assess possible subgroup variation (Kleinbaum et al., 1982). Third, the present study took into account the route of administration for prescription stimulants which is often neglected in epidemiological studies examining NMUPS among adolescents and young adults. In terms of limitations, the DAST-10 has not been tested in a web-based version, and therefore future work is needed to determine the clinical significance of a web-based version, and to validate our findings using a more comprehensive diagnostic assessment. Similarly, the DAST-10 items were not stimulant-

specific so the higher rates of drug use related problems based on the DAST-10 among nonmedical users of prescription stimulants may be attributed to the use of other drugs and/or a pattern of polydrug use. However, because more than 90% of pastyear nonmedical users of prescription stimulants also reported using other drugs (not including alcohol) in the past year, brief screening instruments that cover a wide range of drugs appears appropriate. The present study did not include a diagnostic assessment of drug abuse or dependence so we were unable to assess the sensitivity or specificity of the DAST-10. Future research is needed to examine the sensitivity and specificity of the DAST-10 in college student populations. Second, the sample from the present study was drawn from one university and the findings may not generalize to other college samples because previous research has found that rates of NMUPS vary across different types of U.S. colleges and universities. For example, one national study found the past-year prevalence of NMUPS at individual four-year U.S. colleges and universities ranged from 0% to 25% (McCabe et al., 2005). Although the demographic characteristics of the sample in the present study resembled the demographic characteristics of four-year U.S. colleges and universities nationally (McCabe et al., 2005), future investigations should examine multiple colleges and universities as well as young adults not attending college to assess the generality of the present findings. Third, the number of respondents reporting “other routes” of administration of NMUPS (e.g., injecting, smoking and inhaling) was small (n = 19) relative to those reporting oral administration only (n = 182) and oral and intranasal administration (n = 100) which resulted in a wide 95% confidence interval for the “other routes” category when conducting multivariate analysis. Future investigations are needed to examine the association between route of administration and drug use related problems in larger and more diverse samples. Finally, nonresponse could have introduced bias in the present study because approximately three in every ten students who were invited did not participate in the study. Nonresponse bias was assessed by administering a short form of the questionnaire via telephone to a randomly selected sample of 750 students who did not respond to the original web survey, and 159 students responded. The demographic characteristics of the 159 students who responded to the telephone survey were compared with the 591 nonrespondents; there were no significant differences in terms of gender, race, age and class year between these two groups. We found no significant differences in the rates of past-year alcohol use, heavy episodic drinking, 30-day cigarette smoking and other problem behaviors between respondents to the follow-up phone survey and respondents who completed the original web survey. Despite these limitations, the present study provides strong evidence that the majority of nonmedical users of prescription stimulants are polydrug users. When these nonmedical users are compared to their peers who use other drugs, nonmedical users of prescription stimulants are more likely to report problems related to drug use. In spite of this, these higher rates of drug use problems cannot be attributed directly to NMUPS because the DAST-10 items are not stimulant-specific. Rather, NMUPS appears to be a behavior that serves as a marker for potential

S.E. McCabe, C.J. Teter / Drug and Alcohol Dependence 91 (2007) 69–76

drug abuse, especially among those who report non-oral routes of administration. Our findings indicate the need for appropriate screening and referral among college students. Screening instruments such as the DAST-10 could prove useful for detecting individuals in need of further clinical assessments. If screening is to be effective, however, cutoff scores for each screening instrument must be carefully considered so that students with potential substance use disorders are accurately, and not falsely, identified. Nevertheless, given that very few college students with substance abuse problems receive treatment services (McCabe et al., 2006a,b), a broad-based screening (with appropriate referral) could benefit college communities. Furthermore, prevention and intervention efforts should educate college students about the potential harmful effects of using prescription drugs without doctor supervision. And finally, it must be noted that efforts targeted towards reducing nonmedical prescription stimulant use must not interfere with the availability of these highly effective medications for those in need of treatment of neuropsychiatric disorders such as ADHD. Acknowledgments Funding for this study was provided by research grant DA018239 (PI: Sean Esteban McCabe) from the National Institute on Drug Abuse, National Institutes of Health; the NIDA had no further role in study design; in the collection, analysis and interpretation of data; in the writing of the report; or in the decision to submit the paper for publication. The authors would like to thank Dr. James A. Cranford for his assistance with the data analysis and E. Lauren Sogor for her assistance with collecting articles for the literature review. Disclosure: Drs. McCabe and Teter designed the study and wrote the protocol. Dr. McCabe undertook the statistical analysis, and wrote the first draft of the manuscript. Dr. Teter managed the literature searches and summaries of previous related work. All authors contributed to and have approved the final manuscript. Conflict of interest: None declared. References Barrett, S.P., Darredeau, C., Bordy, L.E., Pihl, R.O., 2005. Characteristics of methylphenidate misuse in a university student sample. Can. J. Psychiatry 50, 457–461. Cocco, K.M., Carey, K.B., 1998. Psychometric properties of the drug abuse screening test in psychiatric outpatients. Psychol. Assess. 10, 408–414. Compton, W.M., Volkow, N.D., 2006. Abuse of prescription drugs and the risk of addiction. Drug Alcohol Depend. (Suppl. 1), 4–7. Fone, K.C., Nutt, D.J., 2005. Stimulants: use and abuse in the treatment of attention deficit hyperactivity disorder. Curr. Opin. Pharmacol. 5, 87–93. French, M.T., Roebuck, M.C., McGeary, K.A., Chitwood, D.D., McCoy, C.B., 2001. Using the drug abuse screening test (DAST-10) to analyze health services utilization and cost for substance users in a community-based setting. Subst. Use Misuse 36, 927–946. Greenhill, L.L., Pliszka, S., Dulcan, M.K., Bernet, W., Arnold, V., Beitchman, J., Benson, R.S., Bukstein, O., Kinlan, J., McClellan, J., Rue, D., Shaw, J.A., Stock, S., 2002. Practice parameters for the use of stimulant medications in the treatment of children, adolescents, and adults. J. Am. Acad. Child Adolesc. Psychiatry 41 (Suppl. 2), 26S–49S.

75

Hall, K.M., Irwin, M.M., Bowman, K.A., Frankenberger, W., Jewett, D.C., 2005. Illicit use of prescribed stimulant medication among college students. J. Am. Coll. Health 53, 167–174. Herman-Stahl, M.A., Krebs, C.P., Kroutil, L.A., Heller, D.C., 2007. Risk and protective factors for methamphetamine use and nonmedical use of prescription stimulants among young adults aged 18 to 25. Addict. Behav. 32, 1003–1015. Johnston, L.D., O’Malley, P.M., Bachman, J.G., Schulenberg, J.E., 2005a. Monitoring the Future National Survey Results on Drug Use, 1975–2004. Secondary School Students, vol. I. National Institute on Drug Abuse (NIH Publication 05-5727), Bethesda, MD. Johnston, L.D., O’Malley, P.M., Bachman, J.G., Schulenberg, J.E., 2005b. Monitoring the Future National Survey Results on Drug Use, 1975–2004. College Students and Adults ages 19–45, vol. II. National Institute on Drug Abuse (NIH Publication 05-5728), Bethesda, MD. Kleinbaum, D.G., Kupper, L.L., Morgenstern, H., 1982. Epidemiological Research: Principles and Quantitative Methods. Lifetime Learning Publications, London. Kollins, S.H., 2003. Comparing the abuse potential of methylphenidate versus other stimulants: a review of available evidence and relevance to the ADHD patient. J. Clin. Psychiatry 64, 14–18. Kroutil, L.A., Van Brunt, D.L., Herman-Stahl, M.A., Heller, D.C., Bray, R.M., Penne, M.A., 2006. Nonmedical use of prescription stimulants in the United States. Drug Alcohol Depend. 84, 135–143. Maisto, S.A., Carey, M.P., Carey, K.B., Gordon, C.M., Gleason, J.R., 2000. Use of the AUDIT and the DAST-10 to identify alcohol and drug use disorders among adults with a severe and persistent mental illness. Psychol. Assess. 12, 186–192. Marsh, L.D., Key, J.D., Payne, T.P., 2000. Methylphenidate misuse in substance abusing adolescents. J. Child Adolesc. Subst. Abuse 9, 1–14. McCabe, S.E., Cranford, J.A., Boyd, C.J., Teter, C.J., 2007. Motives, diversion and routes of administration associated with nonmedical use of prescription opioids. Addict. Behav. 32, 562–575. McCabe, S.E., Knight, J.R., Teter, C.J., Wechsler, H., 2005. Non-medical use of prescription stimulants among U.S. college students: prevalence and correlates from a national survey. Addiction 100, 96–106. McCabe, S.E., Teter, C.J., Boyd, C.J., 2006a. Medical use, illicit use and diversion of prescription stimulant medication. J. Psychoactive Drugs 38, 43–56. McCabe, S.E., Teter, C.J., Boyd, C.J., 2006b. Medical use, illicit use and diversion of prescription drugs. J. Am. Coll. Health 54, 269–278. McCabe, S.E., Teter, C.J., Boyd, C.J., Guthrie, S.K., 2004. Prevalence and correlates of illicit methylphenidate use among 8th, 10th, and 12th grade students in the United States, 2001. J. Adolesc. Health 35, 501–504. Roset, P.N., Farre, M., de la Torre, R., Mas, M., Menoyo, E., Hernandez, C., 2001. Modulation of rate of onset and intensity of drug effects reduces abuse potential in healthy males. Drug Alcohol Depend. 64, 285–298. Skinner, H., 1982. The drug abuse screening test. Addict. Behav. 7, 363–371. Spencer, T.J., 2004. ADHD treatment across the life cycle. J. Clin. Psychiatry 65 (Suppl. 3), 22–26. Substance Abuse and Mental Health Services Administration, 2005a. The NSDUH Report: Stimulant Use, 2003. Available at: http://www.oas.samhsa. gov/2k5/stimulants/stimulants.pdf. Accessed November 13, 2005. Substance Abuse and Mental Health Services Administration, 2005b. The NSDUH Report: College Enrollment Status and Past Year Illicit Drug Use among Young Adults: 2002, 2003, and 2004. Available at: http://oas.samhsa. gov/2k5/College/college.pdf. Accessed October 25, 2005. Substance Abuse and Mental Health Services Administration, 2006. The DAWN Report: Emergency Department Visits Involving ADHD Stimulant Medications. Available at: https://dawninfo.samhsa.gov/files/ TNDR09ADHDmedsForHtml.pdf. Accessed January 25, 2007. Teter, C.J., McCabe, S.E., Boyd, C.J., Guthrie, S.K., 2003. Illicit methylphenidate use in an undergraduate student population. Pharmacotherapy 23, 609–617. Teter, C.J., McCabe, S.E., Cranford, J.A., Boyd, C.J., Guthrie, S.K., 2005. Prevalence and motivations for the illicit use of prescription stimulants in an undergraduate student sample. J. Am. Coll. Health 53, 253–262. Teter, C.J., McCabe, S.E., LaGrange, K., Cranford, J.A., Boyd, C.J., 2006. Illicit use of specific prescription stimulants among college students: preva-

76

S.E. McCabe, C.J. Teter / Drug and Alcohol Dependence 91 (2007) 69–76

lence, motives and routes of administration. Pharmacotherapy 26, 1501– 1510. Upadhyaya, H.P., Rose, K., Wang, W., Brady, K.T., 2005. Attentiondeficit/hyperactivity disorder, medication treatment, and substance use patterns among adolescents and young adults. J. Child Adolesc. Psychopharmacol. 15, 799–809.

Volkow, N.D., Swanson, J.M., 2003. Variables that affect the clinical use and abuse of methylphenidate in the treatment of ADHD. Am. J. Psychiatry 160, 1909–1918. White, B.P., Becker-Blease, K.A., Grace-Bishop, K., 2006. Stimulant medication use, misuse and abuse in an undergraduate and graduate student sample. J. Am. Coll. Health 54, 261–268.