0
We're unable to sign you in at this time. Please try again in a few minutes.
Retry
We were able to sign you in, but your subscription(s) could not be found. Please try again in a few minutes.
Retry
There may be a problem with your account. Please contact the AMA Service Center to resolve this issue.
Contact the AMA Service Center:
Telephone: 1 (800) 262-2350 or 1 (312) 670-7827  *   Email: subscriptions@jamanetwork.com
Error Message ......
Original Investigation |

Marijuana-Using Drivers, Alcohol-Using Drivers, and Their Passengers Prevalence and Risk Factors Among Underage College Students FREE

Jennifer M. Whitehill, PhD1,2,4; Frederick P. Rivara, MD, MPH1,2,3; Megan A. Moreno, MD, MSEd, MPH2,3
[+] Author Affiliations
1Harborview Injury Prevention and Research Center, University of Washington, Seattle
2Department of Pediatrics, University of Washington School of Medicine, Seattle
3Center for Child Health Behavior and Development, Seattle Children’s Hospital, Seattle, Washington
4Department of Public Health, School of Public Health and Health Sciences, University of Massachusetts, Amherst
JAMA Pediatr. 2014;168(7):618-624. doi:10.1001/jamapediatrics.2013.5300.
Text Size: A A A
Published online

Importance  Driving after marijuana use increases the risk of a motor vehicle crash. Understanding this behavior among young drivers and how it may differ from alcohol-related driving behaviors could inform prevention efforts.

Objective  To describe the prevalence, sex differences, and risk factors associated with underage college students’ driving after using marijuana, driving after drinking alcohol, or riding with a driver using these substances.

Design, Setting, and Participants  Cross-sectional telephone survey of a random sample of 315 first-year college students (aged 18-20 years) from 2 large public universities, who were participating in an ongoing longitudinal study. At recruitment, 52.8% of eligible individuals consented to participate; retention was 93.2% one year later when data for this report were collected.

Main Outcomes and Measures  Self-reported past-28-day driving after marijuana use, riding with a marijuana-using driver, driving after alcohol use, and riding with an alcohol-using driver.

Results  In the prior month, 20.3% of students had used marijuana. Among marijuana-using students, 43.9% of male and 8.7% of female students drove after using marijuana (P < .001), and 51.2% of male and 34.8% of female students rode as a passenger with a marijuana-using driver (P = .21). Most students (65.1%) drank alcohol, and among this group 12.0% of male students and 2.7% of female students drove after drinking (P = .01), with 20.7% and 11.5% (P = .07), respectively, reporting riding with an alcohol-using driver. Controlling for demographics and substance use behaviors, driving after substance use was associated with at least a 2-fold increase in risk of being a passenger with another user; the reverse was also true. A 1% increase in the reported percentage of friends using marijuana was associated with a 2% increased risk of riding with a marijuana-using driver (95% CI, 1.01-1.03). Among students using any substances, past-28-day use of only marijuana was associated with a 6.24-fold increased risk of driving after substance use compared with using only alcohol (95% CI, 1.89-21.17).

Conclusions and Relevance  Driving and riding after marijuana use is common among underage, marijuana-using college students. This is concerning given recent legislation that may increase marijuana availability.

Concerns about drug-impaired driving are of increasing importance in the United States, where state laws that reduce or remove penalties for marijuana are becoming more common. Acute use of cannabis approximately doubles the risk of a motor vehicle crash,1,2 so maintaining road traffic safety despite a potential increase in marijuana use is a critical challenge.3,4 Marijuana possession has been decriminalized in 14 states, and 2 states have recently legalized marijuana possession and recreational use for those at least 21 years old.

The issue of marijuana-impaired driving is particularly salient for young drivers, for whom the combination of inexperience and substance use elevates crash risk.57 Youth younger than 21 are at the highest risk of involvement in a fatal motor vehicle crash.8 They are also the age group most likely to use marijuana.9 Nationally, cannabis was involved in 12% of fatal crashes among 16- to 20-year-olds.10

College students are a population at increased risk of substance-related risk behaviors, such as impaired driving.11 For the 66% of American youth that attend postsecondary education,12 college often represents a time of increased exposure to13 and experimentation with marijuana and other substances.14 Marijuana use increases after high school for youth who attend 4-year colleges compared with those who do not.15 Marijuana is second only to alcohol for substances most abused by this population.16 Compared with female students, male students are more likely to use substances,1719 drive after drinking, and be killed in an alcohol-related motor vehicle crash.2022 Findings of previous studies suggest that male students are twice as likely as female students to drive while high on marijuana and 20% more likely to ride with a marijuana-using driver.23

Because public health measures have reduced alcohol-related motor vehicle crashes and reported episodes of drinking and driving,20,21 understanding how marijuana-related driving behaviors are similar to or different from alcohol-related driving behaviors may help inform prevention efforts. The prevalence of driving or riding as a passenger after alcohol use has been established in other college studies,2426 but examination of how this compares with the prevalence of driving after marijuana use or riding with a marijuana-using driver has been limited to a single-institution study conducted before the surge in legislation that has increased availability of marijuana.22 Accordingly, the purpose of our study was (1) to describe prevalence and sex differences in underage college students’ driving after marijuana use and riding as a passenger with a marijuana-using driver, (2) to examine risk factors for marijuana-impaired driving or riding, and (3) to compare both prevalence and risk factors for marijuana-related driving behaviors with those for alcohol-related driving behaviors.

Setting and Recruitment

Data for this study were obtained from an ongoing longitudinal study of college students’ substance use at 2 large state universities in Wisconsin and Washington State. Incoming first-year students were randomly selected and recruited via postcards, e-mails, and telephone calls. To be eligible, participants had to be 18 or 19 years old by the beginning of the 2011-2012 academic year. Students were excluded if they had been on the university’s campus for early-enrollment programs. Oral consent was obtained by telephone for all students. All study procedures were approved by the institutional review boards at the University of Wisconsin–Madison and Seattle Children’s Research Institute, Seattle, Washington.

Data Collection

Participants completed a telephone interview with a trained research assistant at least once a year, beginning with a baseline interview during the summer before starting college. All interviews included questions about substance use frequency and quantity. The follow-up interview was conducted 1 year later between May 15 and September 20, 2012. In this interview, questions were added to assess driving after substance use. This report focuses on cross-sectional data collected during the summer 2012 interview.

Measures

Demographic information for students, including sex and race, was obtained during the baseline interview. Exact ages were not ascertained because all participants were in the same first-year student cohort and a narrow age range (18 or 19 years old) was part of the inclusion criteria.

Substance Use

Participants reported past-28-day substance use in response to the question, “Have you used (marijuana or alcohol) in the past 28 days?” Individuals who reported using a substance within the past 28 days were interviewed using the Timeline Followback method27 to ascertain the number of days each substance was used during this period. We used the responses to generate continuous variables for each participant, indicating the number of days the participant reported using marijuana only, alcohol only, or both.

Alcohol users were asked how many drinks they had on each day that they used alcohol, with 1 drink defined according to National Institute on Alcohol Abuse and Alcoholism (NIAAA) standards (12 oz of beer, 5 oz of wine, or 1.5 oz of hard liquor). Based on the responses, we generated counts of the number of days that female students had more than 4 drinks and male students had more than 5. We defined these days as heavy episodic (binge) drinking days and counted the number of binge and nonbinge drinking days. The Alcohol Use Disorders Identification Test (AUDIT)28 was administered to students to screen for problematic alcohol use in the past year. We followed commonly used clinical scoring guidelines: scores of 8 to 12 for female students or 8 to 14 for male students were considered indicative of hazardous drinking, and scores of 13 or more for female students or 15 or more for male students signified potential alcohol dependence.29

Students who reported substance use were asked how old they were when they first tried the substance. All students were asked to report the percentages of their friends who use marijuana and use alcohol.

Driving or Riding After Substance Use

Outcomes were assessed by asking, “In the past 28 days, how many times have you ridden as a passenger in a vehicle driven by someone who had been using marijuana?” Two similar questions asked about being a passenger with an alcohol-using driver. Past-28-day use of alcohol or marijuana prompted the interviewer to ask, “In the past 28 days, how many times have you driven after using that substance?” Reponses to both the riding and driving questions were ordinal (0, 1, 2-3, 4-5, or ≥6 times) but were coded as binary (0 or ≥1) in this analysis.

To assess exposure to the risk of driving after substance use, we asked participants if they (1) held a driver’s license and (2) kept a car at school. We also asked students about frequency of seat belt use (always, mostly, sometimes, rarely, or never) because seat belt wearing has a well-established relationship to motor vehicle-related risk taking.20,30 The distribution was heavily skewed toward always wearing a seat belt, so this variable was dichotomized to measure whether or not participants always wear their seat belts.

Statistical Analysis

We first examined differences by sex and university in means and proportions for all variables using t tests for continuous data and χ2 tests for categorical data. We examined the prevalence of driving after substance use and riding with a substance-using driver among all respondents and separately among those using substances in the past 28 days. We used χ2 tests to examine differences in prevalence between alcohol- and marijuana-related driving behaviors.

We conducted regression analyses for 4 outcomes: driving after marijuana use, riding with a driver who used marijuana, driving after alcohol use, and riding with a driver who used alcohol. To assess which factors were associated with the outcomes of interest, we used Poisson regression with robust standard errors to estimate relative risk (RR).31 We first examined bivariate associations, selecting predictors based on the literature about driving after drinking and substance use behavior, followed by multivariable regression. Factors that were nonsignificant in the initial multivariable model were not retained in the final model.

For the outcome of driving after marijuana use, we examined the following covariates: sex, seat belt use, university, age at first marijuana use, number of days using marijuana in the past 28 days, whether the respondent rode as a passenger with a marijuana-using driver, and whether the respondent drove after alcohol use. This same basic model was used to predict riding with a marijuana-using driver, with driving after marijuana use, and percentage of friends using marijuana entered as covariates. A similar approach was taken for alcohol-related outcomes, with an additional binary variable for positive AUDIT screen (≥8). We used a fifth regression model to compare how using marijuana, alcohol, or both substances in the past 28 days contributed to the risk of driving after any substance use. All analyses were conducted using Stata 12/SE software (Stata Corp).

Of 640 incoming college freshman approached, 338 (52.8% response rate) consented to be in the study, and 315 participants (93.2% retention rate) completed the follow-up interview at the end of their first year. All participants were between the ages of 18 and 20 years. The sample was 56.2% female and 75.6% white (Table 1); 59.4% of the participants were from the University of Wisconsin–Madison. Differences between the study population and those who refused were not significant for sex (P = .32) or university (P = .16), the 2 items we could assess among refusers. There were more participants from minority groups in the Washington sample (44.5%) than in the Wisconsin sample (10.9%) (P < .001) but no differences in sex (P = .63). The past-28-day prevalence of alcohol use was higher for Wisconsin (79.0%) than for Washington (65.4%) participants (P = .01), but there was no significant difference in the prevalence of marijuana use or use of both substances. There were no significant differences in driving or riding after substance use by university.

Table Graphic Jump LocationTable 1.  Demographic and Substance Use Characteristics of Underage College Students

A larger proportion of male than female students engaged in substance use (Table 1). The past-28-day prevalence of marijuana use was 29.7% for male and 13.0% for female students, and the past-28-day prevalence of alcohol use was 66.7% for male and 63.8% for female students. The prevalence of having used both marijuana and alcohol on the same day was 23.2% for male and 8.5% for female students.

Marijuana-Related Behavior
Driving After Marijuana Use

Among all students, the prevalence of driving after marijuana use was 6.3% (Table 2). Among current (past-28-day) marijuana users, 43.9% of male and 8.7% of female students drove after using marijuana. The risk of driving after marijuana use was highest for those who rode with a marijuana-using driver (RR, 5.72; 95% CI, 1.84-17.80) and for those who drove after drinking (RR, 2.45; 95% CI, 1.39-4.31), whereas an older age at first marijuana use was associated with a lower risk (RR, 0.78; 95% CI, 0.63-0.97) (Table 3). Each 1-year increase in the age at first marijuana use was associated with a 22% reduction in the risk of driving after marijuana use.

Table Graphic Jump LocationTable 2.  Past-28-Day Prevalence of Driving or Riding After Marijuana or Alcohol Use Among Underage College Students
Table Graphic Jump LocationTable 3.  Adjusted Relative Risk of Driving or Riding After Marijuana Use Among Underage College Studentsa
Riding With a Marijuana-Using Driver

Among all students the prevalence of riding with a driver who had used marijuana was 13.0%. The proportion of students who rode with a marijuana-using driver was higher for the subset of students who used marijuana in the past 28 days than for the sample as a whole. For marijuana-using students, a larger proportion of male than female students (51.2% vs 34.8%) rode with a driver who had used marijuana. The risk of riding with a marijuana-using driver was increased for those who drove after using marijuana (RR, 4.42; 95% CI, 2.40-8.14). For each 1% increase in the reported percentage of friends who use marijuana, students were 2% more likely to ride with a marijuana-using driver (95% CI, 1.01-1.03). This translates into a 3.2-fold increase in the risk of riding with a marijuana-using driver for a 50% increase in the estimated number of friends using marijuana. Report of always wearing a seat belt was associated with reduced risk (RR, 0.55; 95% CI, 0.33-0.91).

Alcohol-Related Behaviors
Driving After Alcohol Use

The prevalence of driving after drinking was 4.4% among all students, 6.8% among the subpopulation of students who used alcohol in the past 28 days, and significantly higher for male than for female students (P = .01) (Table 2). Regression models showed 2 statistically significant risk factors for driving after drinking: riding with a drinking driver (RR, 7.24; 95% CI, 2.45-21.35) and the number of nonbinge drinking days (RR, 1.15; 95% CI , 1.09-1.22) (Table 4). Reporting always wearing a seat belt was associated with a much-reduced risk (RR, 0.20; 95% CI, 0.09-0.48).

Table Graphic Jump LocationTable 4.  Adjusted Relative Risk of Driving or Riding After Drinking Alcohol Among Underage College Studentsa
Riding With an Alcohol-Using Driver

For riding with a drinking driver, driving after drinking was the strongest risk factor (RR, 4.73; 95% CI, 2.54-8.08). The number of binge drinking days increased the risk of riding with a drinking driver (RR, 1.12; 95% CI, 1.08-1.17) somewhat more than the number of nonbinge drinking days (RR, 1.07; 95% CI, 1.01-1.13).

Comparisons Between Marijuana-Related and Alcohol-Related Behaviors

The χ2 tests comparing marijuana-related and alcohol-related behaviors (see proportions in Table 2) showed that among the full sample, there was no significant difference in the proportion who drive after marijuana use compared with after alcohol use (P = .29) or who ride with a driver using each substance (P = .63). However, among students who use substances, marijuana users have a higher prevalence of driving (P = .005) and riding (P < .001) after marijuana use than alcohol users have for driving or riding after alcohol use.

Among students who reported past-28-day use of either substance, 29.5% reported riding with a substance-using driver compared with 6.7% who did not report substance use (P < .001). The multivariate model to assess contribution from each substance type or combination to the risk of driving after any substance use (Table 5) showed that compared with using alcohol alone in the past 28 days, using only marijuana showed a substantial increase in the risk of driving after substance use (RR, 6.24; 95% CI, 1.89-21.17) with controlling for sex, days of substance use, reported seat belt use, and AUDIT score. Use of marijuana and alcohol was not associated with a statistically significant difference in risk. In this model, an increase in the number of days on which any substance was used was associated with an increased risk of driving after substance use (RR, 1.06; 95% CI, 1.03-1.09), as was having a positive AUDIT score (RR, 2.86; 95% CI, 1.07-7.65).

Table Graphic Jump LocationTable 5.  Relative Risk of Driving After Use of Any Substance Among 210 Underage College Students With Any Past-28-Day Use of Marijuana or Alcohol

This study found that underage male college students who used marijuana in the past 28 days had a high prevalence of driving after marijuana use and riding with a marijuana-using driver. This was more than double the prevalence of driving or riding after alcohol use among current alcohol users. Our findings were consistent with those of other studies demonstrating that for alcohol, the behaviors of driving after substance use and riding with friends who have been using are strongly associated.32 Driving after drinking also increased the risk of driving after marijuana use. An older age at first marijuana use was associated with a 20% reduction in the risk of driving after marijuana use for each year increment in the age at first use. As expected, a higher percentage of the respondent’s friends reported to be using marijuana indicated an increased risk of riding with a marijuana-using driver.

Our finding that using only marijuana increased the risk of substance-impaired driving is logically consistent with other studies indicating that driving after marijuana use is perceived as safer than driving after alcohol use23 and done more frequently.33,34 Our data also suggest that, similar to many risk behaviors, peers have a strong role in influencing behavior related to driving after substance use; individuals who rode with a marijuana-using driver were more than 5 times more likely to drive after marijuana use.

It could be beneficial to have effective strategies to combat the myth that driving after marijuana use is safe and change social norms toward having a safe ride home not only for alcohol use but for any substance use episode. The CRAFFT screening tool, named for the first letters of key words in the 6 screening questions (Car, Relax, Alone, Forget, Friends, Trouble), is a validated instrument that can help pediatric providers identify patients who might benefit from counseling about the risk of marijuana-impaired driving.35 Further research will be needed to understand whether such counseling is effective. In the changing policy environment surrounding marijuana, it will be important to continue to follow the trends both in arrests and self-reports, particularly among adolescent populations whose driving skills are still being developed.

Our study had limitations. Study participants were not different from refusers for the variables we could measure, but unmeasured differences could bias the results. The response rate of 52.8% is not unusual for studies of college students. Although the sample is representative of the colleges from which the data were drawn, it is not representative of all colleges. The small number of nonwhite students in our sample may mean that the risks identified in this study may not be representative of all college populations.

Our ascertainment of all variables was limited to self-report, creating the possibility for recall and social desirability bias. The Timeline Followback method used in the study is well validated for helping avoid the bias that comes with the passing of time since the event in question.3638 Participants were informed that we obtained a federal certificate of confidentiality for the study, which we hope helped them feel comfortable disclosing behaviors related to alcohol and drug use. Prior work with college students suggests that self-reported substance-related risk behaviors are valid compared with other data sources.39

An additional limitation is that we did not assess the time between substance use and driving, the level of impairment, or the incidence of motor vehicle crashes. Because we did not ask about how many hours each episode of substance use lasted, we defined binge drinking as consuming 4 or 5 drinks in a day. This differs from the NIAAA definition of binge drinking as consuming 4 or 5 drinks in 2 hours, so we may have overestimated the number of days in which NIAAA-defined binge drinking occurred. We ascertained whether alcohol and marijuana were used on the same day but not whether they were used concurrently.

The number of marijuana-using individuals in our sample may have limited our ability to detect certain associations between risk factors and driving or riding after use of this substance. Although our results indicate that driving and riding after marijuana use varies by sex, our data did not permit us to examine how sex may modify the relationship between risk factors and driving or riding after marijuana use. These outcomes were relatively rare among female participants, and the number was too small to support investigating this interaction in the regression models.

Despite the limitations of our study, our findings are an important and timely contribution to the literature on older adolescents driving after drug use. They supplement our knowledge that marijuana use increases the risk of motor vehicle crashes by estimating how common it is for underage students to have taken this risk within the past 28 days.

Accepted for Publication: November 19, 2013.

Corresponding Author: Jennifer M. Whitehill, PhD, Department of Public Health, School of Public Health and Health Sciences, University of Massachusetts Amherst, 715 N Pleasant St, Arnold House 326, Amherst, MA 01003 (jmw@umass.edu).

Published Online: May 12, 2014. doi:10.1001/jamapediatrics.2013.5300.

Author Contributions: Drs Whitehill and Moreno had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Whitehill, Moreno.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Whitehill, Moreno.

Critical revision of the manuscript for important intellectual content: Rivara.

Statistical analysis: Whitehill.

Obtained funding: Rivara, Moreno.

Conflict of Interest Disclosures: None reported.

Funding/Support: This study was supported by grant R01DA031580-03 from the National Institutes of Health Common Fund, managed by the Office of the Director/Office of Strategic Coordination, and by grant T32HD057822 from the National Institute of Child Health and Human Development.

Role of the Sponsor: The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Additional Contributions: Mara Stewart, BSN, Lauren Kacvinsky, BS, and the Social Media and Adolescent Health Research Team assisted with data collection and management, and Janessa Graves, PhD, MPH, Alex Quistberg, PhD, MPH, and Jin Wang, PhD, offered suggestions about data analysis. Mss Stewart and Kacvinsky received compensation for their roles; the others did not.

Li  MC, Brady  JE, DiMaggio  CJ, Lusardi  AR, Tzong  KY, Li  G.  Marijuana use and motor vehicle crashes. Epidemiol Rev. 2012;34(1):65-72.
PubMed   |  Link to Article
Asbridge  M, Hayden  JA, Cartwright  JL.  Acute cannabis consumption and motor vehicle collision risk: systematic review of observational studies and meta-analysis. BMJ. 2012;344:e536. doi:10.1136/bmj.e536.
Link to Article
Johnson  MB, Kelley-Baker  T, Voas  RB, Lacey  JH.  The prevalence of cannabis-involved driving in California. Drug Alcohol Depend. 2012;123(1-3):105-109.
PubMed   |  Link to Article
Dennis  B, Farnam  TW. Too high to drive? marijuana-friendly Colorado debates blood-level limits.Washington Post. March 2, 2013:A01.
Pickett  W, Davison  C, Torunian  M, McFaull  S, Walsh  P, Thompson  W.  Drinking, substance use and the operation of motor vehicles by young adolescents in Canada. PLoS One. 2012;7(8):e42807. doi:10.1371/journal.pone.0042807.
PubMed   |  Link to Article
Shope  JT, Bingham  CR.  Teen driving: motor-vehicle crashes and factors that contribute. Am J Prev Med. 2008;35(3)(suppl):S261-S271.
PubMed   |  Link to Article
Mann  RE, Stoduto  G, Butters  J,  et al.  Age group differences in collision risk. J Safety Res. 2010;41(5):445-449.
PubMed   |  Link to Article
Insurance Institute for Highway Safety. Fatality facts: teenagers, 2011.http://www.iihs.org/iihs/topics/t/teenagers/fatalityfacts/teenagers/2011. Accessed April 16, 2013.
US Department of Health and Human Services, Substance Abuse and Mental Health Services Administration, Center for Behavioral Health Statistics and Quality. Results from the 2011 National Survey on Drug Use and Health: Summary of National Findings. Rockville, MD: Substance Abuse and Mental Health Services Administration; 2012.
Romano  E, Pollini  RA.  Patterns of drug use in fatal crashes. Addiction. 2013;108(8):1428-1438.
Link to Article
Carter  AC, Brandon  KO, Goldman  MS.  The college and noncollege experience: a review of the factors that influence drinking behavior in young adulthood. J Stud Alcohol Drugs. 2010;71(5):742-750.
PubMed
Bureau of Labor Statistics. College Enrollment and Work Activity of 2012 High School Graduates. Washington, DC: US Dept of Labor; 2013.
Pinchevsky  GM, Arria  AM, Caldeira  KM, Garnier-Dykstra  LM, Vincent  KB, O’Grady  KE.  Marijuana exposure opportunity and initiation during college: parent and peer influences. Prev Sci. 2012;13(1):43-54.
PubMed   |  Link to Article
Fromme  K, Corbin  WR, Kruse  MI.  Behavioral risks during the transition from high school to college. Dev Psychol. 2008;44(5):1497-1504.
PubMed   |  Link to Article
Fleming  CB, White  HR, Haggerty  KP, Abbott  RD, Catalano  RF.  Educational paths and substance use from adolescence into early adulthood. J Drug Issues. 2012;42(2):104-126.
PubMed   |  Link to Article
Primack  BA, Kim  KH, Shensa  A, Sidani  JE, Barnett  TE, Switzer  GE.  Tobacco, marijuana, and alcohol use in university students: a cluster analysis. J Am Coll Health. 2012;60(5):374-386.
PubMed   |  Link to Article
O’Malley  PM, Johnston  LD.  Epidemiology of alcohol and other drug use among American college students. J Stud Alcohol Suppl. 2002;S14(14):23-39.
PubMed
Garnier-Dykstra  LM, Caldeira  KM, Vincent  KB, O’Grady  KE, Arria  AM.  Nonmedical use of prescription stimulants during college: four-year trends in exposure opportunity, use, motives, and sources. J Am Coll Health. 2012;60(3):226-234.
Link to Article
American College Health Association. National College Health Assessment II: Reference Group Executive Summary Fall 2012. Hanover, MD: American College Health Association; 2013.
Bergen  G, Shults  RA, Beck  LF, Qayad  M.  Self-reported alcohol-impaired driving in the U.S., 2006 and 2008. Am J Prev Med. 2012;42(2):142-149.
PubMed   |  Link to Article
Centers for Disease Control and Prevention.  Vital signs: alcohol-impaired driving among adults–United States, 2010. MMWR Morb Mortal Wkly Rep. 2011;60(39):1351-1356.
PubMed
Arria  AM, Caldeira  KM, Vincent  KB, Garnier-Dykstra  LM, O’Grady  KE.  Substance-related traffic-risk behaviors among college students. Drug Alcohol Depend. 2011;118(2-3):306-312.
PubMed   |  Link to Article
Arterberry  BJ, Treloar  HR, Smith  AE, Martens  MP, Pedersen  SL, McCarthy  DM.  Marijuana use, driving, and related cognitions. Psychol Addict Behav. 2013;27(3):854-860.
PubMed   |  Link to Article
Hingson  RA, Zha  W, Weitzman  ER.  Magnitude of and trends in alcohol-related mortality and morbidity among US college students ages 18-24, 1998-2005. J Stud Alcohol Drugs Suppl.2009;(16):12-20.
PubMed
Barrett  SP, Darredeau  C, Pihl  RO.  Patterns of simultaneous polysubstance use in drug using university students. Hum Psychopharmacol. 2006;21(4):255-263.
PubMed   |  Link to Article
Grossbard  JR, Mastroleo  NR, Kilmer  JR,  et al.  Substance use patterns among first-year college students: secondary effects of a combined alcohol intervention. J Subst Abuse Treat. 2010;39(4):384-390.
PubMed   |  Link to Article
Sobell  LC, Sobell  MB, Leo  GI, Cancilla  A.  Reliability of a timeline method: assessing normal drinkers’ reports of recent drinking and a comparative evaluation across several populations. Br J Addict. 1988;83(4):393-402.
PubMed   |  Link to Article
Saunders  JB, Aasland  OG, Babor  TF, de la Fuente  JR, Grant  M.  Development of the Alcohol Use Disorders Identification Test (AUDIT): WHO Collaborative Project on Early Detection of Persons with Harmful Alcohol Consumption–II. Addiction. 1993;88(6):791-804.
PubMed   |  Link to Article
Allen  JP, Litten  RZ, Fertig  JB, Babor  T.  A review of research on the Alcohol Use Disorders Identification Test (AUDIT). Alcohol Clin Exp Res. 1997;21(4):613-619.
PubMed   |  Link to Article
Goudie  RJBMS, De Neve  J-E, Oswald  AJ, Wu  S. Happiness as a Driver of Risk-Avoiding Behavior: A Conceptual Framework With an Application to Seatbelt Wearing and Automobile Accidents. London, England: Centre for Economic Performance, London School of Economics; 2012.
Zou  G.  A modified poisson regression approach to prospective studies with binary data. Am J Epidemiol. 2004;159(7):702-706.
PubMed   |  Link to Article
LaBrie  JW, Kenney  SR, Mirza  T, Lac  A.  Identifying factors that increase the likelihood of driving after drinking among college students. Accid Anal Prev.2011;43(4):1371-1377.
PubMed   |  Link to Article
Lacey  JH, Kelley-Baker  T, Furr-Holden  D,  et al. 2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Alcohol Results. Washington, DC: National Highway Traffic Safety Administration; 2009.
Lacey  JH, Kelley-Baker  T, Furr-Holden  D,  et al. 2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results. Washington, DC: National Highway Traffic Safety Administration; 2009.
Knight  JR, Shrier  LA, Bravender  TD, Farrell  M, Vander Bilt  J, Shaffer  HJ.  A new brief screen for adolescent substance abuse. Arch Pediatr Adolesc Med. 1999;153(6):591-596.
PubMed   |  Link to Article
Norberg  MM, Mackenzie  J, Copeland  J.  Quantifying cannabis use with the Timeline Followback approach: a psychometric evaluation. Drug Alcohol Depend. 2012;121(3):247-252.
PubMed   |  Link to Article
Pedersen  ER, Grow  J, Duncan  S, Neighbors  C, Larimer  ME.  Concurrent validity of an online version of the Timeline Followback assessment. Psychol Addict Behav. 2012;26(3):672-677.
PubMed   |  Link to Article
Vakili  S, Sobell  LC, Sobell  MB, Simco  ER, Agrawal  S.  Using the Timeline Followback to determine time windows representative of annual alcohol consumption with problem drinkers. Addict Behav. 2008;33(9):1123-1130.
PubMed   |  Link to Article
Turner  J, Keller  A, Bauerle  J.  The longitudinal pattern of alcohol-related injury in a college population: emergency department data compared to self-reported data. Am J Drug Alcohol Abuse. 2010;36(4):194-198.
PubMed   |  Link to Article

Figures

Tables

Table Graphic Jump LocationTable 1.  Demographic and Substance Use Characteristics of Underage College Students
Table Graphic Jump LocationTable 2.  Past-28-Day Prevalence of Driving or Riding After Marijuana or Alcohol Use Among Underage College Students
Table Graphic Jump LocationTable 3.  Adjusted Relative Risk of Driving or Riding After Marijuana Use Among Underage College Studentsa
Table Graphic Jump LocationTable 4.  Adjusted Relative Risk of Driving or Riding After Drinking Alcohol Among Underage College Studentsa
Table Graphic Jump LocationTable 5.  Relative Risk of Driving After Use of Any Substance Among 210 Underage College Students With Any Past-28-Day Use of Marijuana or Alcohol

References

Li  MC, Brady  JE, DiMaggio  CJ, Lusardi  AR, Tzong  KY, Li  G.  Marijuana use and motor vehicle crashes. Epidemiol Rev. 2012;34(1):65-72.
PubMed   |  Link to Article
Asbridge  M, Hayden  JA, Cartwright  JL.  Acute cannabis consumption and motor vehicle collision risk: systematic review of observational studies and meta-analysis. BMJ. 2012;344:e536. doi:10.1136/bmj.e536.
Link to Article
Johnson  MB, Kelley-Baker  T, Voas  RB, Lacey  JH.  The prevalence of cannabis-involved driving in California. Drug Alcohol Depend. 2012;123(1-3):105-109.
PubMed   |  Link to Article
Dennis  B, Farnam  TW. Too high to drive? marijuana-friendly Colorado debates blood-level limits.Washington Post. March 2, 2013:A01.
Pickett  W, Davison  C, Torunian  M, McFaull  S, Walsh  P, Thompson  W.  Drinking, substance use and the operation of motor vehicles by young adolescents in Canada. PLoS One. 2012;7(8):e42807. doi:10.1371/journal.pone.0042807.
PubMed   |  Link to Article
Shope  JT, Bingham  CR.  Teen driving: motor-vehicle crashes and factors that contribute. Am J Prev Med. 2008;35(3)(suppl):S261-S271.
PubMed   |  Link to Article
Mann  RE, Stoduto  G, Butters  J,  et al.  Age group differences in collision risk. J Safety Res. 2010;41(5):445-449.
PubMed   |  Link to Article
Insurance Institute for Highway Safety. Fatality facts: teenagers, 2011.http://www.iihs.org/iihs/topics/t/teenagers/fatalityfacts/teenagers/2011. Accessed April 16, 2013.
US Department of Health and Human Services, Substance Abuse and Mental Health Services Administration, Center for Behavioral Health Statistics and Quality. Results from the 2011 National Survey on Drug Use and Health: Summary of National Findings. Rockville, MD: Substance Abuse and Mental Health Services Administration; 2012.
Romano  E, Pollini  RA.  Patterns of drug use in fatal crashes. Addiction. 2013;108(8):1428-1438.
Link to Article
Carter  AC, Brandon  KO, Goldman  MS.  The college and noncollege experience: a review of the factors that influence drinking behavior in young adulthood. J Stud Alcohol Drugs. 2010;71(5):742-750.
PubMed
Bureau of Labor Statistics. College Enrollment and Work Activity of 2012 High School Graduates. Washington, DC: US Dept of Labor; 2013.
Pinchevsky  GM, Arria  AM, Caldeira  KM, Garnier-Dykstra  LM, Vincent  KB, O’Grady  KE.  Marijuana exposure opportunity and initiation during college: parent and peer influences. Prev Sci. 2012;13(1):43-54.
PubMed   |  Link to Article
Fromme  K, Corbin  WR, Kruse  MI.  Behavioral risks during the transition from high school to college. Dev Psychol. 2008;44(5):1497-1504.
PubMed   |  Link to Article
Fleming  CB, White  HR, Haggerty  KP, Abbott  RD, Catalano  RF.  Educational paths and substance use from adolescence into early adulthood. J Drug Issues. 2012;42(2):104-126.
PubMed   |  Link to Article
Primack  BA, Kim  KH, Shensa  A, Sidani  JE, Barnett  TE, Switzer  GE.  Tobacco, marijuana, and alcohol use in university students: a cluster analysis. J Am Coll Health. 2012;60(5):374-386.
PubMed   |  Link to Article
O’Malley  PM, Johnston  LD.  Epidemiology of alcohol and other drug use among American college students. J Stud Alcohol Suppl. 2002;S14(14):23-39.
PubMed
Garnier-Dykstra  LM, Caldeira  KM, Vincent  KB, O’Grady  KE, Arria  AM.  Nonmedical use of prescription stimulants during college: four-year trends in exposure opportunity, use, motives, and sources. J Am Coll Health. 2012;60(3):226-234.
Link to Article
American College Health Association. National College Health Assessment II: Reference Group Executive Summary Fall 2012. Hanover, MD: American College Health Association; 2013.
Bergen  G, Shults  RA, Beck  LF, Qayad  M.  Self-reported alcohol-impaired driving in the U.S., 2006 and 2008. Am J Prev Med. 2012;42(2):142-149.
PubMed   |  Link to Article
Centers for Disease Control and Prevention.  Vital signs: alcohol-impaired driving among adults–United States, 2010. MMWR Morb Mortal Wkly Rep. 2011;60(39):1351-1356.
PubMed
Arria  AM, Caldeira  KM, Vincent  KB, Garnier-Dykstra  LM, O’Grady  KE.  Substance-related traffic-risk behaviors among college students. Drug Alcohol Depend. 2011;118(2-3):306-312.
PubMed   |  Link to Article
Arterberry  BJ, Treloar  HR, Smith  AE, Martens  MP, Pedersen  SL, McCarthy  DM.  Marijuana use, driving, and related cognitions. Psychol Addict Behav. 2013;27(3):854-860.
PubMed   |  Link to Article
Hingson  RA, Zha  W, Weitzman  ER.  Magnitude of and trends in alcohol-related mortality and morbidity among US college students ages 18-24, 1998-2005. J Stud Alcohol Drugs Suppl.2009;(16):12-20.
PubMed
Barrett  SP, Darredeau  C, Pihl  RO.  Patterns of simultaneous polysubstance use in drug using university students. Hum Psychopharmacol. 2006;21(4):255-263.
PubMed   |  Link to Article
Grossbard  JR, Mastroleo  NR, Kilmer  JR,  et al.  Substance use patterns among first-year college students: secondary effects of a combined alcohol intervention. J Subst Abuse Treat. 2010;39(4):384-390.
PubMed   |  Link to Article
Sobell  LC, Sobell  MB, Leo  GI, Cancilla  A.  Reliability of a timeline method: assessing normal drinkers’ reports of recent drinking and a comparative evaluation across several populations. Br J Addict. 1988;83(4):393-402.
PubMed   |  Link to Article
Saunders  JB, Aasland  OG, Babor  TF, de la Fuente  JR, Grant  M.  Development of the Alcohol Use Disorders Identification Test (AUDIT): WHO Collaborative Project on Early Detection of Persons with Harmful Alcohol Consumption–II. Addiction. 1993;88(6):791-804.
PubMed   |  Link to Article
Allen  JP, Litten  RZ, Fertig  JB, Babor  T.  A review of research on the Alcohol Use Disorders Identification Test (AUDIT). Alcohol Clin Exp Res. 1997;21(4):613-619.
PubMed   |  Link to Article
Goudie  RJBMS, De Neve  J-E, Oswald  AJ, Wu  S. Happiness as a Driver of Risk-Avoiding Behavior: A Conceptual Framework With an Application to Seatbelt Wearing and Automobile Accidents. London, England: Centre for Economic Performance, London School of Economics; 2012.
Zou  G.  A modified poisson regression approach to prospective studies with binary data. Am J Epidemiol. 2004;159(7):702-706.
PubMed   |  Link to Article
LaBrie  JW, Kenney  SR, Mirza  T, Lac  A.  Identifying factors that increase the likelihood of driving after drinking among college students. Accid Anal Prev.2011;43(4):1371-1377.
PubMed   |  Link to Article
Lacey  JH, Kelley-Baker  T, Furr-Holden  D,  et al. 2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Alcohol Results. Washington, DC: National Highway Traffic Safety Administration; 2009.
Lacey  JH, Kelley-Baker  T, Furr-Holden  D,  et al. 2007 National Roadside Survey of Alcohol and Drug Use by Drivers: Drug Results. Washington, DC: National Highway Traffic Safety Administration; 2009.
Knight  JR, Shrier  LA, Bravender  TD, Farrell  M, Vander Bilt  J, Shaffer  HJ.  A new brief screen for adolescent substance abuse. Arch Pediatr Adolesc Med. 1999;153(6):591-596.
PubMed   |  Link to Article
Norberg  MM, Mackenzie  J, Copeland  J.  Quantifying cannabis use with the Timeline Followback approach: a psychometric evaluation. Drug Alcohol Depend. 2012;121(3):247-252.
PubMed   |  Link to Article
Pedersen  ER, Grow  J, Duncan  S, Neighbors  C, Larimer  ME.  Concurrent validity of an online version of the Timeline Followback assessment. Psychol Addict Behav. 2012;26(3):672-677.
PubMed   |  Link to Article
Vakili  S, Sobell  LC, Sobell  MB, Simco  ER, Agrawal  S.  Using the Timeline Followback to determine time windows representative of annual alcohol consumption with problem drinkers. Addict Behav. 2008;33(9):1123-1130.
PubMed   |  Link to Article
Turner  J, Keller  A, Bauerle  J.  The longitudinal pattern of alcohol-related injury in a college population: emergency department data compared to self-reported data. Am J Drug Alcohol Abuse. 2010;36(4):194-198.
PubMed   |  Link to Article

Correspondence

CME
Also Meets CME requirements for:
Browse CME for all U.S. States
Accreditation Information
The American Medical Association is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians. The AMA designates this journal-based CME activity for a maximum of 1 AMA PRA Category 1 CreditTM per course. Physicians should claim only the credit commensurate with the extent of their participation in the activity. Physicians who complete the CME course and score at least 80% correct on the quiz are eligible for AMA PRA Category 1 CreditTM.
Note: You must get at least of the answers correct to pass this quiz.
Please click the checkbox indicating that you have read the full article in order to submit your answers.
Your answers have been saved for later.
You have not filled in all the answers to complete this quiz
The following questions were not answered:
Sorry, you have unsuccessfully completed this CME quiz with a score of
The following questions were not answered correctly:
Commitment to Change (optional):
Indicate what change(s) you will implement in your practice, if any, based on this CME course.
Your quiz results:
The filled radio buttons indicate your responses. The preferred responses are highlighted
For CME Course: A Proposed Model for Initial Assessment and Management of Acute Heart Failure Syndromes
Indicate what changes(s) you will implement in your practice, if any, based on this CME course.
Submit a Comment

Multimedia

Some tools below are only available to our subscribers or users with an online account.

1,176 Views
3 Citations

Related Content

Customize your page view by dragging & repositioning the boxes below.

See Also...
Articles Related By Topic
Related Collections
PubMed Articles
Jobs
JAMAevidence.com

The Rational Clinical Examination: Evidence-Based Clinical Diagnosis
Alcohol Abuse

The Rational Clinical Examination: Evidence-Based Clinical Diagnosis
Original Article: A Primer on the Precision and Accuracy of the Clinical Examination

×