Personality characteristics and health risk behaviors associated with current marijuana use among college students

doi:10.4236/ojpm.2011.13015

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Vol.1, No.3, 101-108 (2011)

doi:10.4236/ojpm.2011.13015

Open Journal of Preventive Medicine

Personality characteristics and health risk behaviors

associated with current marijuana use among college

students

Carla J. Berg1*, Taneisha S. Buchanan2, Linda Grimsley3, Jan Rodd3, Daniel Smith4

1Department of Behavioral Sciences and Health Education, Emory University School of Public Health, Atlanta, USA;

*Corresponding Author: cjberg@emory.edu

2Department of Medicine, University of Minnesota, Minneapolis, USA;

3Department of Nursing, Albany State University, Albany, USA;

4Institutional Effectiveness, Athens Technical College, Athens, Greece.

Received 7 September 2011; revised 16 October 2011; accepted 26 October 2011.

ABSTRACT

Objective: Marijuana is a prevalent substance

used among young adults and has serious psy-

cho soc ia l and he alth-rel ate d co nsequenc es . Thus,

identifying factors associated with marijuana

use is critical. The current study aimed to exa-

mine personality factors and health risk be-

haviors associated with marijuana use. Methods:

We administered an online survey to six col-

leges in the Southeast. Overall, we recruited

24,055 college students, yielding 4840 respon-

ses (20.1% response rate), with complete data

from 4,401 students. Results: Current (past 30

day) marijuana use was reported by 13.8% of

our sample. Users either reported infrequent

use of marijuana (i.e., between 1 and 5 days;

52.3%) or very frequent use of marijuana (i.e.,

between 26 and 30 days; 18.2%). Mutlivariate

analyses modeling correlates of marijuana use

(Nagelkerke R2 = 0.323) indicated that signifi-

cant factors included being younger (p < 0.001),

being male (p = 0.002), being Black (p = 0.002),

attending a fou r-year college (p = 0 .00 5) , b eing a

nondaily (p < 0.001) or daily smoker (p < 0.001)

vs. a nonsmoker, other tobacco use (p < 0.001),

greater alcohol use (p < 0.001), greater per-

ceived stress (p = 0.009), higher levels of sen-

sation seeking (<0.001) and openness to ex-

periences (p = 0.02), and lower levels of agree-

ableness (p = 0.01) and conscientiousness (p <

0.001). Conclusions: Identifying risk factors re-

lated to marijuana use is critical in developing

intervent ions targeti ng both use and prev ention.

Moreover, understanding different college set-

tings and the contextual factors associated with

greater marijuana use is critical.

Keywords: Marijuana Use ; Toba cco ; A lcoh ol U se;

College Students

1. INTRODUCTION

Marijuana has been the most common illicit substance

used in the United States for several decades [1,2]. It is

especially common among young adults, with approxi-

mately 16% of young adults (ages 18 to 25) having used

marijuana within the past month [1]. In addition, as

many as 9.4% of college freshman may have a marijuana

use disorder [3], and about 35% of users meet at least

one criterion for marijuana dependence [4].

Marijuana use has several important negative implica-

tions. In terms of morbidity and mortality, marijuana use

plays a major role in motor vehicle crashes [5], has ad-

verse effects on the respiratory and cardiovascular sys-

tems [6-10], increases susceptibility to cancer [11], and

impairs short- and long-term memory functioning [12].

Not only are there health consequences, but marijuana

use has important psychosocial effects. Marijuana use is

associated with impaired poor school performance, low

educational aspirations and expectations [13,14], low

educational attainment [15], reduced workplace produc-

tivity [16], and the postponement of marriage and em-

ployment [17].

Certain intra-individual characteristics are related to

marijuana use [18]. For example, one longitudinal study

over a 23 year span from early adolescence to adulthood

[13] found that chronic marijuana use was associated

with poor self-control [13], more externalizing behavior

[19], and greater sensation seeking [13]. Higher levels of

depressive symptoms have also been found to prospec-

tively predict different trajectories of marijuana use

C. J. Berg et al. / Open Journal of Preventive Medicine 1 (2011) 101-108

102

through adolescence [20]. In addition, stress has been a

factor associated with using marijuana [21]. Moreover,

marijuana use has been correlated with other problem

behaviors, such as rebelliousness [22], delinquency [22],

and risky sexual behavior [22]. It is also associated with

an increased risk of use of other substances [22,23], in-

cluding cigarette smoking [1,24] and alcohol use [1,24].

Given the aforementioned literature, the present study

aimed to examine correlates of marijuana use in a sam-

ple of Southeast U.S. college students. Specifically, we

examined sociodemographics (age, gender, race, paren-

tal education, and type of school attended), other health

risk behaviors (cigarette smoking, other tobacco use,

alcohol use, sexual activity), and psychosocial correlates

(depressive symptoms, perceived stress, and personality

traits including sensation seeking, extraversion, agree-

ableness, conscientiousness, emotional stability, and open-

ness to experience) in relation to marijuana use.

2. METHODS

In October, 2010, students at six colleges in the

Southeast were recruited to complete an online survey.

A random sample of 5000 students at each school (with

the exclusion of two schools who had enrollment less

than 5000) were invited to complete the survey (total

invited N = 24,055). Students received an e-mail con-

taining a link to the consent form with the alternative of

opting out. Students who consented to participate were

directed to the online survey. To encourage participation,

students received up to three e-mail invitations to par-

ticipate. As an incentive for participation, all students

who completed the survey received entry into a drawing

for cash prizes of $1000 (one prize), $500 (two prizes),

and $250 (four prizes) at each participating school. Of

students who received the invitation to participate, 4840

(20.1%) returned a completed survey. Our current a-

nalyses focus on 4401 participants who had complete

data. The vast majority of our sample (95.1%) was be-

tween the ages of 18 and 30 years old, with the oldest

participant being 48 years of age. The Emory University

Institutional Review Board approved this study, IRB#

00030631.

2.1. Measures

An online survey containing 230 questions assessed a

variety of health topic areas, which took approximately

20-25 minutes to complete. For the current investigation,

only the following variables were included.

Demographic characteristics assessed included stu-

dents’ age, gender, ethnicity, highest parental educa-

tional attainment, and type of school attended (i.e., two-

year versus four-year college). Ethnicity was categorized

as non-Hispanic White, Black, or Other due to the small

numbers of participants who reported other race/ethnici-

ties. Highest parental educational attainment was cate-

gorized as high school graduate or GED, some college,

or ≥ Bachelors degree based on the distribution of pa-

rental educational attainment. For ease of interpretation,

these categorizations were chosen.

Current Marijuana Use. To assess current marijuana

use, students were asked, “In the past 30 days, on how

many days did you use marijuana (pot, weed, hashish,

hash oil)?” (ACHA, 2008; CDC, 1997). Current users

were considered to be individuals who smoked at least

one day in the past 30 days.

Smoking Status. To assess smoking status, students

were asked, “In the past 30 days, on how many days did

you smoke a cigarette (even a puff)?” This question has

been used to assess tobacco use in the American College

Health Association (ACHA) surveys, National College

Health Risk Behavior Survey (NCHRBS), and Youth

Risk Behavior Survey (YRBS), and their reliability and

validity have been documented by previous research

[25,26]. Students who reported smoking on at least one

day in the past 30 days were considered current smokers,

and students who reported smoking on all 30 days of the

past month were considered daily smokers versus non-

daily smokers (i.e., those who smoked from 1 to 29 days

of the past 30 days). This is consistent with how ACHA,

Substance Abuse and Mental Health Association (SAM-

SHA), and others have defined “daily smokers” [27,28].

Other Tobacco Use. To assess other tobacco use, stu-

dents were asked, “In the past 30 days, on how many

days did you: Use chewing tobacco, snuff, or dip, such

as Redman, Levi Garrett, Beechnut, Skoal, Skoal Ban-

dits, or Copenhagen? Smoke cigars (Please do not in-

clude little cigars or cigarillos, such as Black and Milds,

when answering this question)? Smoke little cigars (such

as Black and Milds)? Smoke cigarillos (such as Swisher

Sweets cigarillos)? Smoke tobacco from a water pipe

(hookah)?” An aggregate variable for any other tobacco

use in the past month was created.

Alcohol Use. To assess alcohol use, students were

asked, “In the past 30 days, on how many days did you

drink alcohol?” (ACHA, 2008; CDC, 1997).

Number of Sexual Partners. Participants were asked,

“During the past 12 months, with how many people did

you have sexual intercourse?”

Depressive Symptoms. Participants were asked to

complete the Patient Health Questionnaire (PHQ-2) [29],

which is a 2-item depression screening tool, based on

DSM-4 diagnostic criteria, assessing frequency of de-

pressed mood (“feeling down, depressed or hopeless”)

and anhedonia (“little interest or pleasure in doing

things”) over the past two weeks. Responses were rated

C. J. Berg et al. / Open Journal of Preventive Medicine 1 (2011) 101-108

103

on a 4-point Likert scale and range from “not at all” (0)

to “nearly every day” (3). A total score > 3 has been

used to reflect clinical depression [29]. Using a mental

health professional interview as the criterion standard, a

PHQ-2 score ≥ 3 had a sensitivity of 83% and a specific-

ity of 92% for major depression, indicating that a PHQ-2

score of 3 is the optimal cutpoint for screening purposes.

Perceived Stress. Participants completed the Per-

ceived Stress Scale (PSS-4) [30] to assess the amount of

stress they experienced in the past month. Higher total

scores indicate greater levels of perceived stress.

Sensation Seeking. The Brief Sensation Seeking Scale

—4 item (BSSS-4) [31] is an abbreviated version of the

8-item Brief Sensation Seeking Scale. The BSSS-4 in-

cludes the items from the BSSS after examining the

psychometric properties of the BSSS [32] and retaining

one item from each of the four original subscales with

the highest item-total correlation. The four items are: a) I

would like to explore strange places; b) I like to do

frightening things; c) I like new and exciting experiences,

even if I have to break the rules; and d) I prefer friends

who are exciting and unpredictable. Psychometric analy-

ses revealed appropriate internal consistency (Cronbach

alpha of 0.75), convergent validity, and test-retest reli-

ability [31].

Big 5 Personality Traits. The Ten-Item Personality In-

ventory (TIPI) [33] is a brief measure that assesses cha-

racteristics included in traditional Big Five personality

inventories (i.e., Extraversion, Agreeableness, Conscien-

tiousness, Emotional Stability, and Openness to Experi-

ence), two items measuring each factor. Each item con-

sists of two descriptors, separated by a comma, using the

common stem, ‘‘I see myself as:’’. Each of the five i-

tems was rated on a 7-point scale ranging from 1 (dis-

agree strongly) to 7 (agree strongly). The TIPI takes a-

bout a minute to complete. This measure has demon-

strated appropriate internal consistency for two-item

scales (Cronbach alphas of 0.68, 0.40, 0.50, 0.73 and

0.45 for the Extraversion, Agreeableness, Conscien-

tiousness, Emotional Stability, and Openness to Experi-

ence scales respectively). Although somewhat inferior to

standard multi-item instruments, the TIPI demonstrates

adequate convergent validity, test–retest reliability, and

appropriate patterns of predicted external correlates [33].

2.2. Data Analysis

Participant characteristics were summarized using de-

scriptive statistics. Bivariate analyses were conducted

comparing current marijuana users versus nonusers us-

ing chi-squared tests for categorical variables and inde-

pendent samples t-tests for continuous variables. Binary

logistic regression was used to examine factors associ-

ated with current marijuana use. To control for the po-

tential influence of demographic characteristics on the

primary outcomes of interest (i.e., marijuana use), age,

gender, ethnicity were entered into each model, and then

factors associated with marijuana use at the p < 0.10

were entered using backwards stepwise entry. SPSS 18.0

was used for all data analyses. Statistical significance

was set at α = 0.05 for all tests.

3. RESULTS

Current (past 30 day) marijuana use was reported by

13.8% of the sample. Figure 1 displays the frequency of

use among current users. Notably, the majority (52.3%)

of marijuana users reported infrequent use of marijuana

(i.e., between 1 and 5 days) and a sizeable proportion

(18.2%) reported daily or almost daily use (i.e., between

26 and 30 days).

Bivariate analysis indicated that correlates of mari-

juana use included being younger (p < 0.001), being

male (p < 0.001), coming from a home with less edu-

cated parents (p < 0.001), attending a four-year college

(p < 0.001), being a current nondaily or daily smoker vs.

a nonsmoker (p < 0.001), current other tobacco use (p <

0.001), more days of alcohol use in the past 30 days (p <

0.001), having more sex partners in the past year (p <

0.001), greater likelihood of having significant depres-

sive symptoms (p < 0.001), greater perceived stress (p <

0.001), higher levels of sensation seeking (p < 0.001),

and lower levels of agreeableness (p < 0.001), conscien-

tiousness (p < 0.001), and emotional stability (p = 0.002;

see Table 1).

Mutlivariate analyses modeling correlates of mari-

juana use (Nagelkerke R2 = 0.323) indicated that sig-

nificant factors included being younger (p < 0.001), be-

ing male (p = 0.002), being Black (p = 0.002), attending

a four-year college (p = 0.005), being a nondaily (p <

0.001) or daily smoker (p < 0.001) vs. a nonsmoker,

other tobacco use (p < 0.001), greater alcohol use (p <

0.001), greater perceived stress (p = 0.009), higher levels

Figure 1. Frequency of marijuana use among current mari-

uana users. j

C. J. Berg et al. / Open Journal of Preventive Medicine 1 (2011) 101-108

104

Table 1. Participant characteristics and bivariate analyses comparing marijuana users and nonusers.

Va ri a bl e

Total

N = 4401

N (%) or M (SD)

Nonusers

N = 3795 (86.2%)

N (%) or M (SD)

Users

N = 606 (13.8%)

N (%) or M (SD)

p-value

Sociodemographics

Age (SD) 23.52 (7.12) 23.81 (7.47) 21.74 (3.90) <0.001

Gender (%)

Male

Female

1267 (28.8)

3134 (71.2)

1008 (26.6)

2787 (88.9)

259 (42.7)

347 (11.1)

<0.001

Ethnicity (%)

White

Black

Other

2009 (45.6)

1714 (38.9)

678 (15.4)

1722 (45.4)

1482 (39.1)

591 (15.6)

287 (47.4)

232 (38.3)

87 (14.4)

0.60

Parental education (%)

< Bachelors degree

≥ Bachelors degree

2729 (62.0)

1672 (38.0)

2401 (63.3)

1394 (36.7)

328 (54.1)

278 (45.9)

<0.001

Type of school (%)

Four-year

Two-year

2730 (62.0)

1671 (38.0)

2292 (60.4)

1503 (39.6)

438 (72.3)

168 (27.7)

<0.001

Other risk behaviors

Cigarette smoking past 30 days (%)

Nonsmoker

Nondaily smoker

Daily smoker

3358 (76.3)

594 (13.5)

449 (10.2)

3058 (80.6)

408 (10.8)

329 (8.7)

300 (49.5)

186 (30.7)

120 (19.8)

<0.001

Other tobacco use past 30 days (%)

Yes

3549 (82.0)

778 (18.0)

3281 (87.8)

457 (12.2)

268 (45.5)

321 (54.5)

<0.001

Alcohol use past 30 days (SD) 3.29 (5.16) 2.73 (4.68) 6.77 (6.49) <0.001

Sex partners in the past year (SD) 1.51 (3.82) 1.38 (3.97) 2.36 (2.50) <0.001

Psychosocial factors

Depressive symptoms (%)

Yes

3632 (91.5)

339 (8.5)

3197 (92.3)

265 (7.7)

435 (85.5)

74 (14.5)

<0.001

Perceived stress (SD) 6.17 (3.40) 6.04 (3.38) 7.01 (3.44) <0.001

Sensation seeking (SD) 3.32 (0.90) 3.26 (0.90) 3.70 (0.84) <0.001

Big 5 factors (SD)

Extraversion

Agreeableness

Conscientiousness

Emotional stability

Openness

8.74 (2.87)

9.97 (2.31)

11.06 (2.43)

9.52 (2.75)

10.80 (2.31)

8.72 (2.85)

10.05 (2.30)

11.21 (2.38)

9.57 (2.74)

10.77 (2.31)

8.93 (3.02)

9.42 (2.32)

10.07 (2.53)

9.18 (2.81)

10.96 (2.29)

0.11

<0.001

0.002

0.09

of sensation seeking (<0.001) and openness to experi-

ences (p = 0.02), and lower levels of agreeableness (p =

0.01) and conscientiousness (p < 0.001; see Table 2).

4. DISCUSSION

The current study documented novel findings, par-

ticularly that two-year college students versus four-year

college students were less likely to report current use of

marijuana. Moreover, findings indicated that lower lev-

els of agreeableness and conscientiousness and higher

levels of openness to experiences were associated with

marijuana use.

Prior research documenting that marijuana use is re-

lated to lower educational aspirations, expectations [13,14]

and attainment [15] might suggest that four-year college

students would report lower levels of marijuana use

compared to two-year college students. However, we

found the opposite, even after controlling for age and

other characteristics. Additional research might examine

qualitative differences in attitudes toward marijuana use

as well as contextual factors associated with marijuana

use in different college settings (e.g., technical schools,

state schools, liberal arts coleges, private schools, his l

C. J. Berg et al. / Open Journal of Preventive Medicine 1 (2011) 101-108

105

Table 2. Binary logistic regression model identifying correlates of marijuana users and nonusers.

Variable OR 95% CI p-value

Sociodemographics

Age 0.95 0.93, 0.98 <0.001

Gender

Male

Female

Ref

0.69

0.55, 0.87

0.002

Ethnicity

White

Black

Other

Ref

1.52

0.89

1.16, 1.98

0.63, 1.26

0.002

0.51

Parental education

< Bachelors degree

≥ Bachelors degree

Ref

1.08

0.86, 1.36

0.50

Type of school

Four-year

Two-year

Ref

0.67

0.50, 0.88

0.005

Other risk behaviors

Cigarette smoking past 30 days (%)

Nonsmoker

Nondaily smoker

Daily smoker

Ref

1.82

3.38

1.35, 2.45

1.06, 1.10

<0.001

Other tobacco use past 30 days (%)

Yes

Ref

4.37

3.42, 5.58

<0.001

Alcohol use past 30 days (SD) 1.08 1.06, 1.10 <0.001

Sex partners in the past year (SD) 1.02 1.00, 1.05 0.06

Psychosocial factors

Perceived stress (SD) 1.05 1.01, 1.08 0.009

Sensation seeking (SD) 1.41 1.22, 1.62 <0.001

Big 5 factors (SD)

Agreeableness

Conscientiousness

Openness

0.94

0.88

1.07

0.89, 0.99

0.84, 0.92

1.01, 1.13

0.01

<0.001

0.02

Nagelkerke R2 = 0.323.

torically black colleges and universities, tribal colleges,

etc.).

With regard to personality traits, lower levels of

agreeableness and conscientiousness and higher levels of

openness to experiences were associated with marijuana

use. Although these factors are associated with sensation

seeking (agreeableness: r = –0.07; conscientiousness: r =

–0.05; and openness: r = 0.25), they are not highly cor-

related with this well established correlate of marijuana

use. Thus, these findings contribute to literature aimed at

identifying individuals at risk for marijuana use and po-

tential targets for intervention. Low levels of conscien-

tiousness may indicate a risk for marijuana use but also

poor school performance, which has been previously

associated with marijuana use [13,14]. Moreover, those

low in agreeableness but high in openness to experience

might indicate that those less receptive to conventional

societal norms may be at risk for marijuana use.

The data support prior research findings indicating

that marijuana use is associated with greater sensation

seeking [13], higher levels of depressive symptoms [20],

greater stress [21], risky sexual behavior [22], alcohol

use [1,24], and cigarette smoking [1,24]. Specifically in

regard to cigarette smoking, this is a concern, as concur-

rent use of marijuana and tobacco is associated with in-

creased symptoms of cannabis dependence [34]. Addi-

tionally, both cigarette and marijuana smoke contain

carcinogenic compounds [35], which could result in in-

creased health risks.

Finally, in the combined sample of students from

two-year and four-year colleges, we found that approxi-

mately 14% used marijuana within the past month, with

half of these users smoking marijuana on five days or

less. However, the other half used marijuana at a fre-

C. J. Berg et al. / Open Journal of Preventive Medicine 1 (2011) 101-108

106

quency equivalent to at least once a week, with one fifth

of users smoking marijuana either daily or almost daily.

In contrast to national data sets, this study documented a

slightly lower rate of marijuana use than national sur-

veys [1], which may reflect the fact that the current sam-

ple was comprised of young adults attending either two-

or four-year colleges. One possibility is that marijuana

use may be more prevalent among non-college attending

adults [13-15].

The current findings have important implications for

research and practice. First, variability in marijuana use

among subgroups warrants further research, as our find-

ings documented a lower prevalence of marijuana use

than national statistics. This may be attributed to the ge-

ographic location, educational aspirations, or other cha-

racteristics of the participant pool. It is critical to under-

stand the underlying factors contributing to marijuana

use and develop successful interventions targeting young

adult marijuana use and co-occurring health risk behav-

iors. In the context of college health and mental health

services, providers are advised to comprehensively screen

for substance use and other health risks (e.g., number of

partners, safe sex practices). Health care providers should

be prepared to assess the severity of substance use and

determine appropriate interventions which may include

stress management and addressing symptoms of depress-

sion.

4.1. Limitations

A number of important limitations should be consid-

ered when interpreting data from this study. First, the

survey sample was largely female and drawn from six

Southeast colleges. Despite the fact that this sample re-

flects the characteristics of these school populations and

has good representation of White and Black ethnic back-

grounds, it may not generalize to other college popula-

tions. Second, the survey response rate was 20.1%,

which may seem low and might suggest responder bias.

However, previous online research has yielded similar

response rates (29% - 32%) among the general popula-

tion [36] and a wide range of response rates (17% - 52%)

among college students [37]. We are also unable to as-

certain how many participants did not open the e-mail or

had inactive accounts, which impacts what the true “de-

nominator” for this response rate may have been. Prior

work has demonstrated that, despite lower response rates,

internet surveys yield similar statistics regarding health

behaviors compared to mail and phone surveys [38]. In

addition, the cross-sectional nature of the data prohibits

the establishment of causality, as temporality, frequency

and dose/response issues cannot be assessed. Moreover,

the overall goal of the survey was not to fully assess ma-

rijuana use; thus, it lacked comprehensive assessments

of marijuana use history, attitudes, beliefs, etc. Finally,

data are derived from self-report and may be subject to

bias.

4.2. Conclusions

This study documents lower reported use of marijuana

among two-year college students as well as unique per-

sonality factors related to marijuana use among college

students, specifically lower agreeableness and conscien-

tiousness and greater openness to new experiences. This

study suggests that these personality characteristics may

assist researchers and practitioners in identifying those at

risk for marijuana use and develop targeted interventions

to address marijuana use among young adults.

5. ACKNOWLEDGEMENTS

This research was supported by the National Cancer Institute

(1K07CA139114-01A1; PI: Berg) and the Georgia Cancer Coalition

(PI: Berg). We would like to thank our collaborators across the state of

Georgia in developing and administering this survey.

REFERENCES

[1] Substance Abuse and Mental Health Services Admini-

stration (2009) Results from the 2008 National Survey on

Drug Use and Health: National Findings. Office of Ap-

plied Studies, Rockville.

[2] Johnston, L. (2009) Monitoring the Future national sur-

vey results on drug use, 1975-2009, Volume I: Secon-

dary school students. National Institute on Drug Abuse,

Bethesda.

[3] Caldeira, K.M., Arria, A.M., O’Grady, K.E., Vincent,

K.B. and Wish, E.D. (2008) The occurrence of cannabis

use disorders and other cannabis-related problems among

first-year college students. Addictive Behaviors, 33, 397-

411. doi:10.1016/j.addbeh.2007.10.001

[4] Nocon, A., Wittchen, H.U., Pfister, H., Zimmermann, P.

and Lieb, R. (2006) Dependence symptoms in young ca-

nnabis users? A prospective epidemiological study. Jour-

nal of Psychiatry Research, 40, 394-403.

doi:10.1016/j.jpsychires.2005.07.011

[5] National Highway Traffic Safety Administration. (2001).

Traffic Safety Facts 2001. Washington, DC.

[6] Mittleman, M.A., Lewis, R.A., Maclure, M., Sherwood,

J.B. and Muller, J.E. (2001) Triggering myocardial in-

farction by marijuana. Circulation, 103, 2805-2809.

[7] Polen, M.R., Sidney, S., Tekawa, I.S., Sadler, M. and

Friedman, G.D. (1993) Health care use by frequent ma-

rijuana smokers who do not smoke tobacco. Western

Journal of Medicine, 158, 596-601.

[8] Tashkin, D.P. (1990). Pulmonary complications of smok-

ed substance abuse. Western Journal of Medicine, 152,

525-530.

[9] Zhang, Z.F., Morgenstern, H., Spitz, M.R., Tashkin, D.P.,

Yu, G.P., Marshall, J.R., et al. (1999) Marijuana use and

increased risk of squamous cell carcinoma of the head

C. J. Berg et al. / Open Journal of Preventive Medicine 1 (2011) 101-108

107

and neck. Cancer Epidemiology, Biomarkers and Pre-

vention, 8, 1071-1078.

[10] Aryana, A. and Williams, M.A. (2007) Marijuana as a

trigger of cardiovascular events: Speculation or scientific

certainty? International Journal of Cardiology, 118, 141-

144. doi:10.1016/j.ijcard.2006.08.001

[11] Hashibe, M., Straif, K., Tashkin, D.P., Morgenstern, H.,

Greenland, S. and Zhang, Z.F. (2005) Epidemiologic re-

view of marijuana use and cancer risk. Alcohol, 35, 265-

275. doi:10.1016/j.alcohol.2005.04.008

[12] Pope, H.G. Jr. and Yurgelun-Todd, D. (1996) The resi-

dual cognitive effects of heavy marijuana use in college

students. Journal of the American Medical Association,

275, 521-527. doi:10.1001/jama.275.7.521

[13] Brook, J.S., Zhang, C. and Brook, D.W. (2011) Devel-

opmental trajectories of marijuana use from adolescence

to adulthood: Personal predictors. Archives of Pediatric

and Adolescent Medicine, 165, 55-60.

doi:10.1001/archpediatrics.2010.248

[14] Brook, J.S., Kessler, R.C. and Cohen, P. (1999) The on-

set of marijuana use from preadolescence and early ado-

lescence to young adulthood. Developmental Psychopa-

thology, 11, 901-914. doi:10.1017/S0954579499002370

[15] Lynskey, M. and Hall, W. (2000) The effects of adoles-

cent cannabis use on educational attainment: A review.

Addiction, 95, 1621-1630.

doi:10.1046/j.1360-0443.2000.951116213.x

[16] Lehman, W.E. and Simpson, D.D. (1992) Employee sub-

stance use and on-the-job behaviors. Journal of Applied

Psychology, 77, 309-321.

doi:10.1037/0021-9010.77.3.309

[17] Brook, J.S., Richter, L., Whiteman, M. and Cohen, P.

(1999) Consequences of adolescent marijuana use: In-

compatibility with the assumption of adult roles. Genetic,

Social, and General Psychology Monographs, 125, 193-

207.

[18] Tarter, R.E. (1988) Are there inherited behavioral traits

that predispose to substance abuse? Journal of Consult-

ing and Clinical Psychology, 56, 189-196.

doi:10.1037/0022-006X.56.2.189

[19] Brook, J.S., Lee, J.Y., Brown, E.N., Finch, S.J. and

Brook, D.W (2011). Developmental trajectories of mari-

juana use from adolescence to adulthood: Personality and

social role outcomes. Psychological Reports, 108, 339-

357. doi:10.2466/10.18.PR0.108.2.339-357

[20] Windle, M. and Wiesner, M. (2004) Trajectories of ma-

rijuana use from adolescence to young adulthood: pre-

dictors and outcomes. Developmental Psychopathology,

16, 1007-1027.

doi:10.1017/S0954579404040118

[21] Hyman, S.M. and Sinha, R. (2009) Stress-related factors

in cannabis use and misuse: Implications for prevention

and treatment. Journal of Substance Abuse and Treat-

ment, 36, 400-413. doi:10.1016/j.jsat.2008.08.005

[22] Degenhardt, L., Hall, W. and Lynskey, M. (2001) The

relationship between cannabis use and other substance

use in the general population. Drug and Alcohol De-

pendence, 64, 319-327.

doi:10.1016/S0376-8716(01)00130-2

[23] Lynskey, M.T., Heath, A.C., Bucholz, K.K., Slutske,

W.S., Madden, P.A., Nelson, E.C., et al. (2003) Escala-

tion of drug use in early-onset cannabis users vs co-twin

controls. Journal of American Medical Association, 289,

427-433. doi:10.1001/jama.289.4.427

[24] Magid, V., Colder, C.R., Stroud, L.R. and Nichter, M.

(2009) Negative affect, stress, and smoking in college

students: Unique associations independent of alcohol and

marijuana use. Addictive Behaviors, 34, 973-975.

doi:10.1016/j.addbeh.2009.05.007

[25] American College Health Association (2008) American

college health association: National college health assess-

ment Spring 2007 reference group data report (Abridged).

Journal of American College Health, 56, 469-479.

doi:10.3200/JACH.56.5.469-480

[26] Centers for Disease Control and Prevention (1997) Youth

risk behavior surveillance: National college health risk

behavior survey—United States, 1995. MMWR Surveil-

lance Summaries, 46, 1-54. Retrieved from

http://www.cdc.gov/mmwr/preview/mmwrhtml/0004985

9.htm.

[27] American College Health Association. (2009). American

college health association: National college health assess-

ment Spring 2008 reference group data report (Abridged).

Journal of American College Health, 57, 477-488.

doi:10.3200/JACH.57.5.477-488

[28] Office of Applied Studies (2006) The NSDUH Report,

Edicted by SAMHSA, Rockville.

[29] Kroenke, K., Spitzer, R.L. and Williams, J.B. (2003) The

Patient Health Questionnaire-2: Validity of a two-item

depression screener. Medical Care, 41, 1284-1292.

doi:10.1097/01.MLR.0000093487.78664.3C

[30] Cohen, S. and Lichtenstein, E. (1990). Perceived stress,

quitting smoking, and smoking relapse. Health Psychol-

ogy, 9, 466-478. doi:10.1037/0278-6133.9.4.466

[31] Stephenson, M.T., Hoyle, R.H., Palmgreen, P. and Slater,

M.D. (2003) Brief measures of sensation seeking for

screening and large-scale surveys. Drug and Alcohol

Dependence, 72, 279-286.

doi:10.1016/j.drugalcdep.2003.08.003

[32] Hoyle, R.H., Stephenson, M.T., Palmgreen, P., Lorch,

E.P. and Donohew, R.L. (2002) Reliability and validity

of a brief measure of sensation seeking. Personality and

Individual Differences, 32, 401-414.

doi:10.1016/S0191-8869(01)00032-0

[33] Gosling, S.D., Rentfrow, P.J. and Swann, W.B. (2003) A

very brief measure of the big-five personality domains.

Journal of Research in Personality, 37, 504-528.

doi:10.1016/S0092-6566(03)00046-1

[34] Ream, G.L., Benoit, E., Johnson, B.D. and Dunlap, E.

(2008) Smoking tobacco along with marijuana increases

symptoms of cannabis dependence. Drug and Alcohol

Dependence, 95, 199-208.

doi:10.1016/j.drugalcdep.2008.01.011

[35] Moir, D., Rickert, W.S., Levasseur, G., Larose, Y., Ma-

ertens, R., White, P., et al. (2008) A comparison of main-

stream and sidestream marijuana and tobacco cigarette

smoke produced under two machine smoking conditions

[Comparative Study]. Chemical Research in Toxicology,

21, 494-502. doi:10.1021/tx700275p

[36] Kaplowitz, M.D., Hadlock, T.D. and Levine, R. (2004) A

comparison of web and mail survey response rates Public

Opinion Quarterly, 68, 94-101.

[37] Crawford, S., McCabe, S. and Kurotsuchi-Inkelas, K.

(2008) Using the web to survey college students: Institu-

C. J. Berg et al. / Open Journal of Preventive Medicine 1 (2011) 101-108

108

tional characteristics that influence survey quality. Paper

presented at the American Association for Public Opin-

ion Association.

[38] An, L.C., Hennrikus, D.J., Perry, C.L., Lein, E.B., Klatt,

C., Farley, D.M., et al. (2007). Feasibility of Internet

health screening to recruit college students to an online

smoking cessation intervention. Nicotine & Tobacco Re-

search, 9, S11-S18. doi:10.1080/14622200601083418