Open Journal of Leadership
2012. Vol.1, No.2, 5-11
Published Online June 2012 in SciRes (http://www.SciRP.org/journal/ojl) http://dx.doi.org/10.4236/ojl.2012.12002
Following the Leader: Examining Leadership Characteristics,
Alcohol Use, and Hooking Up among College Students
Rose Marie Ward*, Judith L. Weiner
Miami University, Oxford, USA
Received April 5th, 2012; revised May 18th, 2012; accepted June 10th, 2012
Although it is generally assumed that leadership traits are linked to positive outcomes, it is unclear how
they might be related to less desirable health behaviors. In a sample of 623 undergraduate students, a se-
ries of structural equation models examined the relationship between transformational leadership traits
and risky health behaviors (i.e., alcohol consumption and hooking up). The models fit the data well and
indicated that higher levels of transformational leadership traits were related to higher levels of alcohol
consumption and risky sexual behaviors. It seems that those students who endorse higher transformational
leadership characteristics are also embracing negative health behaviors.
Keywords: Alcohol; Hooking Up; College Students; Transformational Leadership
Introduction
Risky health behaviors are on the rise in college students. It
is estimated that 40% - 45% of college students are engaging in
heavy episodic drinking each month with the proportion of
college female drinking increasing more than college males
(NCASA, 2007). Another risky health behavior that is increas-
ing in prevalence is “hooking up” or sexual interactions with no
expectations of a relationship (Bogle, 2008; Paul, McManus &
Hayes, 2000; Reiber & Garcia, 2010). Moreover, risky alcohol
consumption and sexual behaviors seem to co-exist (Goldstein,
Barnett, Pedlow, & Murphy, 2007; Testa & Parks, 1996). As
reported alcohol consumption increases, reported numbers of
sexual experiences increases. In addition, both alcohol use and
sexual experience have been linked to negative outcomes (e.g.,
sexual assault; Testa & Dermen, 1999; academic outcomes;
Bryant, Schulenberg, O’Malley, Bachman, & Johnston, 2003).
Another trend on college campuses is the implementation of
“leadership institutes” or programs that seek to increase lead-
ership characteristics among college students. These leadership
institutes seem to be related to education and personal gains
(Cress, Astin, Zimmerman-Oster, & Burkhardt, 2001). How-
ever, it is unclear how leadership traits are related to social
traits (e.g., alcohol consumption and sexual behavior) that are
also increasing during the collegiate experience. The purpose of
the current study is to determine if leadership characteristics are
predictive of levels of risky health behaviors.
Leadership and College Students
Recently, the concept of leadership has been examined
through the lens of transactional and transformational leader-
ship styles. These leadership styles have been characterized by
seven leadership factors (i.e., charisma, inspirational, intellec-
tual stimulation, individualized consideration, contingent re-
ward, management-by-exception, and laissez-faire; Bass, 1985).
Through several extensive studies, this leadership model was
reduced to six factors combining the charismatic and inspira-
tional components (Bass, 1988, 1990; Bass & Avolio, 1994).
As the concept of the leadership styles evolved, Avolio, Bass,
and colleagues (Avolio, Bass, & Jung, 1995; Bass & Avolio,
1997) further expanded the measurement of the styles by de-
veloping the Multifactor Leadership Questionnaire (MLQ 5X)
that supports a nine-factor model and quickly became the most
widely used measure of leadership (Eagly, Johannesen-Schmidt,
& van Engen, 2003). Within this model, five factors were de-
termined to assess transformational leadership (i.e., idealized
influence attributes, idealized influence behaviors, inspirational
motivation, intellectual stimulation, and individualized consid-
eration; Avolio et al., 1999; Den Hartog, Van Muijen, & Koop-
man, 1997).
Transformational leadership is considered to be an effective
method that nurtures followers and inspires them to effectively
contribute to the organization (Bass, 1990; Bass & Bass, 2009).
Bass (1990) explains that transformational leaders are goal
oriented with the mission of the organization or group as a
driving force. As previously mentioned, transformational lead-
ership is comprised of five assets. The first asset is idealized
influence attributes or qualities that instill pride in others
through association with the leader. The second characteristic
of transformational leadership is idealized influence behaviors
or the ability to communicate the goals and mission of the or-
ganization. The next aspect is inspirational motivation or com-
municating optimism and excitement concerning the goals and
future of the organization. Another aspect is intellectual stimu-
lation or the ability to examine multiple viewpoint while solv-
ing problems. The final asset of transformational leadership is
individualized consideration or providing attention and men-
torship to followers (Avolio et al., 1999). Because transforma-
tional leadership relates to the success of organizations (Bass,
1990; Eagly et al., 2003), it will be the focus of the current
investigation.
Furthermore, in research that compared males and females
on leadership styles, females were more likely than males to be
*Corresponding author.

R. M. WARD, J. L. WEINER
transformational leaders (Eagly, et al., 2003). In Eagly and col-
leagues’ (2003) meta-analysis of leadership studies, women had
statistically significantly higher scores on the measures of
transformational leadership (as measured by the subscales of
the MLQ 5X). However, the effect sizes across these studies
were small according to Cohen’s (1988) classifications of effect
sizes. Whereas the meta-analysis was comprehensive in its fo-
cus, the analysis was on gender differences on the leadership
styles and not specific to college students. It is unclear from the
literature if the same pattern would exist for a collegiate sam-
ple.
There are programs aimed at developing leadership traits in
college students. For example, LeaderShape
(http://www.leadershape.org/) is a leadership development
program that seems to increase transformational leadership
traits (Bass & Bass, 2009). Additionally, several colleges have
leadership institutes as part of their academic structure (e.g.,
Brown’s Leadership Institute and the Leadership Institute at
Harvard). Some programs target leaders or to increase leader-
ship traits in attempt to combat a specific issue. Banyard and
colleagues (2009) utilized student leaders in their sexual assault
bystander programming (Banyard, Moynihan, & Crossman,
2009) due to their influence on others. The general assumption
across these programs are that leadership traits and skills are
linked to positive outcomes; however, studies examining spe-
cific types of college student leaders provide evidence to the
contrary for health outcomes.
Traditionally, students who are collegiate athletes and mem-
bers of Greek social societies tend to be viewed as leaders on
their respective college campuses. As such, researchers exam-
ine the differences of these students when compared to their
collegiate peers. With respect to alcohol use, athletes and
members of Greek organizations consume more alcohol than
their peers. Specifically, leaders on athletic teams tend to drink
more and experience more negative consequences than their
teammates and other non-athletes (Leichliter, Meilman, Presley,
& Cashin, 1998). In addition, leaders in Greek societies drink
more than members and non-members. Moreover, Greek lead-
ers experience more alcohol-related consequences than other
members (Cashin, Presley, & Meilman, 1998). In general,
leaders consume more alcohol than non-leaders (Spratt & Tur-
rentine, 2001). Furthermore, if it can be assumed that being an
athlete is a sign of leadership, athletes drink more and have
higher levels of risky sex compared to non-athletes (Grossbard,
Lee, Neighbors, Hendershot, & Larimer, 2007). However, there
are no studies available that examine leadership traits level in
relation to risky sexual behavior and alcohol consumption.
Risky Health Behaviors and College Students
Alcohol use is common on college campuses. Alcohol use
rates on college campus have remained steady (NCASA, 2007)
despite near universal movements on college campus to educate
students about the effects of alcohol. For example, researchers
estimate that over 40% of college students drink heavily
(O’Malley & Johnston, 2002). Not only are college students
regular consumers of alcohol, they also experience the largest
proportion of negative consequences associated with alcohol
(e.g., black outs, injuries, academic issues, regretted sexual
experiences, legal issues, sickness, hangover), and the number
of negative consequences experienced by college students is
increasing (NCASA, 2007). These consequences have costs to
the student (e.g., grades, health, injury, and even death), the
university (e.g., property destruction), and society. In addition,
50% of college male drinkers and 35% of female college drink-
ers report drinking and driving (NCASA, 2007). Approximately
24% of students report that they have missed class as result of
drinking (Weschler, et al., 1998). College students report ex-
periencing black outs or memory loss (52% of heavy drinkers,
Weschler et al., 1999), unprotected sex (17.1%, Harford et al.,
2002), and injuries (30%, Jacobs, 2005) as a result of their al-
cohol consumption. Moreover, Abbey (2002) estimates that in
50% of sexual assault either the perpetrator or the victim or both
are under the influence of alcohol. Furthermore, heavy drinking
in college is related to higher rates of alcohol consumption and
dependence 25 years after college (Sloan et al., 2011).
Alcohol consumption in college student differs across the
genders. College women and men reported participating in
frequent binge drinking (20.9% and 25.2% of college students,
respectively), frequently being drunk (24.6% and 34.9%, re-
spectively), and drinking 10 or more drinks on a drinking occa-
sion in the past 30 days (16.8% and 29.2%, respectively;
NCASA, 2007). Whereas the participation rates currently differ,
they might not for long. Women have experienced around a
30% increase in these behaviors since 1993 (NCASA, 2007).
Another high-risk behavior common to college students is
hooking up. Hooking up or sexual behaviors outside the com-
mitment of a relationship (Bogle, 2008; Paul & Hayes, 2002) is
fairly common on college campuses with 50% of students indi-
cating that they hooked up in the last year (Owen, Rhoades,
Stanley, & Fincham, 2010). Researchers have argued that this
recent trend towards hooking up reflects a shift in the dating
paradigm (e.g., Bogle, 2008). Similar to risky alcohol con-
sumption, hooking up is related to a number of negative out-
comes (STI, unintended pregnancy; Grello et al., 2006; LaBrie,
Earleywine, Schiffman, Pedersen, & Marriot, 2005; Paul et al.,
2000). In addition, hooking up is related to college student’s
alcohol consumption (Grello et al., 2006; Paul et al., 2000;
Owen, Rhoades, Stanley, & Fincham, 2010). Similar to trends
in alcohol use, men more than women tend to hook up (Grello
et al., 2003; Manning, Longmore, & Giordano, 2005). In addi-
tion, in comparison to women, men are more likely to view the
hook ups as positive (Owen & Ficham, 2010).
Leadership traits are generally considered desirable and
characteristics one might want to develop (as evidenced by the
leadership institutes). In college students, however, leadership
positions in athletics and Greek organizations have been linked
to riskier alcohol consumption and sexual behaviors. It is un-
clear from the literature if leadership traits in general will also
be related to levels of risky behaviors. Therefore, the purpose of
the current project is to examine the relationship between lead-
ership traits as measured by the MLQ 5X and risky behaviors
(i.e., alcohol use and risky sex). In addition, a secondary pur-
pose is to examine the role of gender with respect to leadership
and risky behaviors.
Methods
Participants
Eleven small and medium-sized colleges and universities
from the Midwest, Northwest, and Northeast United States
participated. A total of 623 students completed the survey. The
majority of the sample indicated that they were female (55.9%,
6

R. M. WARD, J. L. WEINER
n = 348; male: 30.3%, n = 189; not selected: 13.8%, n = 86).
They had a mean age of 21.54 (SD = 4.80), reported being
Caucasian (74.2%, n = 462), and were not married (73.0%, n =
455). A majority of the participants reported that their parents
were well educated (Mother education—college or above,
49.28%, n = 307; Father education—college or above, 54.74%,
n = 341). In addition, a variety of family incomes (from under
$25K to over $200K) and year in school (from first year student
to graduate student) were represented (freshmen: 17.5%, n =
109; sophomore: 13.5%, n = 84; junior: 20.4%, n = 127; senior:
17.8%, n = 111; 5th year: 6.3%, n = 39; graduate student: 9.8%,
n = 61). Approximately 6.3% (n = 39) of the participants indi-
cated that they participated in varsity sports. In addition, 18.5%
(n = 115) are members of Greek organizations and an addition
8.2% (n = 51) intend on pledging a Greek organization. Addi-
tionally, 20.4% (n = 127) indicated that they were currently in a
leadership position.
Recruitment Procedure
After receiving IRB approval from the first author’s institu-
tion and each respective institution, potential participants were
selected via a two-step method. During the first step, approxi-
mately 500 email addresses were randomly retrieved from each
school’s respective online directory. The second step included
the online survey program testing the email address to deter-
mine if it was a working email address. Additional participants
at one mid-sized Midwestern universities signed up for the
study via an online recruitment tool, Sonasystems.com. Many
of the students using Sonasystems.com received course credit
in their Introduction to Psychology class for their participation.
Online Survey Procedure
The current project is part of a larger project on leadership,
sexual health, and alcohol. Potential participants were sent an
email invitation requesting their participation in the study. One
reminder email was sent approximately one week following the
initial contact to participants who did not complete the survey.
The online survey was housed by Prezza Checkbox software at
the principal investigator’s host institution. All data collected
were protected behind the institution’s firewall and IP addresses
were not pursued
Measures
Participants were asked basic demographic questions re-
garding age, gender, sexual orientation, marital status, parental
marital status, and parental education levels.
Multifactor Leadership Question (MLQ-5X; Avolio, Bass,
& Jung, 1995). The 45-item inventory is a self- report measure
that assesses transformational, transactional, and passive/
avoidant leadership characteristics. The MLQ-5X has nine
scales—five of which measure transformational leadership. The
Idealized Influence (Attributed) scale has four items and as-
sesses the ability to garner respect through association (four
items; e.g., “I instill pride in others for being associated with
me.”). The Idealized Influence (Behaviors) assesses the com-
munication of values (four items; e.g., “I talk about my most
important values and beliefs.”). The Inspirational Motivation
scale measures behaviors that exhibit excitement about future
goals (four items; e.g., “I talk optimistically about the future.”).
Intellectual Stimulation assesses problem-solving perspectives
(four items; e.g., “I seek differing perspectives when solving
problems.”). The final scale for Transformative Leadership is
Individualized Consideration or developing and mentoring
followers (four items; “I spend time teaching and coaching.”).
Participants were instructed to report how frequently they en-
gage in the behaviors and actions listed. Participants responded
using a five-point Likert scale (0 = “Not at all” to 4 = “Fre-
quently, if not always”). Scales were averaged, and higher
scores indicated that the participant endorsed more of each
aspect of leadership. Previous research indicates good internal
reliability and good test-retest reliability (Avolio & Bass, 1995).
For the current study, only the scales pertinent to transforma-
tional leadership were used; the five scales had .69, .72, .83, .77,
and .66 internal consistencies, respectively. Means and standard
deviations of the scales are in Table 1 as those used in national
data collections of college-student drinking (e.g., NCASA,
2007). Participants were asked whether they ever consumed an
alcoholic drink, the number of days in a typical week that they
drink, the number of drinks they had on a typical drinking oc-
casion, the highest number of drinks they had had on one occa-
sion in the last 30 days, and the number of drinks, on average,
they consumed for each day of the week. To facilitate their
responses to these items, participants were provided with the
definition of a standard drink (12 ounces of beer, 4 ounces of
wine, or a 1-ounce shot of liquor; Wechsler, Lee, Kuo, Seibring,
Nelson, & Lee, 2002.
Risky Sex. Participants were asked three questions concern-
ing their sexual experience. They were asked for the number of
sexual experiences in the last week (sexual experiences were
defined as any situation which was sexual in nature). In addi-
tion, participants were asked the number of hook ups they had
in the last week. Consistent with the literature, a definition for
hooking up was not provided. Finally, participants were asked
to indicate the average number of people involved in the hook
ups over the last week.
Results
Descriptive Statistics
Participants reported drinking an average of 1.75 days (SD =
1.46) with an average of 3.99 standard drinks (SD = 3.10) per
drinking occasion. On average, their highest drinking occasion
in the last 30 days was 6.35 drinks (SD = 5.21). Some partici-
pants reported drinking on every day of the week (Number of
standard drinks—Monday: M = .08, SD = .47; Tuesday: M
Table 1.
Descriptives of multifactor leadership questionnaire.
Scale Mean
Standard
Deviation
Cronbach’s
Alpha
Idealized Influence Attributed2.52 .68 .69
Idealized Influence Behavior2.61 .69 .72
Inspirational/Motivational 2.73 .74 .83
Intellectual Stimulation 2.63 .69 .77
Individualized Consideration2.61 .67 .66

R. M. WARD, J. L. WEINER
8
= .22, SD = 1.03; Wednesday: M = .32, SD = 1.32; Thursday:
M = 1.50, SD = 2.74; Friday: M = 3.25, SD = 3.57; Saturday:
M = 3.55, SD = 3.61; Sunday: M = .24, SD = 1.07).
With respect to the risky sex variables, participants reported
having an average of 1.41 (SD = 2.91) sexual encounters. They
reported hooking up an average of 1.27 times (SD = 2.68) in
the last week. In those hook up experiences, they reported hav-
ing an average of .67 people (SD = .59).
Gender Differences
An oneway MANOVA examined gender differences across
the five leadership scales. The overall model was significant,
Wilk’s Lambda = .95, p = .01, partial 2 = .05. The follow up
oneway ANOVAs indicated significant gender differences for
Idealized Influence Behavior, F(1, 328) = 6.98, p = .01, and
Inspirational Motivation, F(1, 328) = 4.94, p = .03. See Table 2
for the means. Consistent with previous literature, an oneway
MANOVA indicated significant gender differences across the
alcohol consumption variables, Wilk’s Lambda = .85, p < .001,
partial 2 = .12. The follow up oneway ANOVAs indicated
significant gender differences for typical number of drinks on a
drinking occasion, F(1, 401) = 16.05, p < .001, and peak drink-
ing occasion, F(1, 401) = 30.21, p < .001. However, in contrast
to the literature, an oneway MANOVA examining gender dif-
ferences in risky sex occurrences was non-significant, Wilk’s
Lambda = .99, p = .83, partial η2 = .01.
Structural Equation Models
The relationships between the constructs were assessed
within a structural equation modeling framework using Mplus
version 5.21. Models were proposed based upon theoretical
predictions and examined using the following criteria: 1) theo-
retical salience; 2) global fit indices (chi-square goodness of fit,
Comparative Fit Index: CFI & Tucker-Lewis Index: TLI); 3)
microfit indices (parameter estimates, Root Mean Squared Er-
ror of Approximation: RMSEA, and residuals); and 4) parsi-
mony Each of the criteria was equally weighed in the selection
of the final model. The criteria for theoretical fit maintain that
the model must be predicted from documented theory and pre-
vious research. To evaluate the global fit indices, a non-sig-
nificant chi-square indicates that the data does not significantly
differ from the hypotheses represented by the model. Addition-
ally for CFI and TLI, fit indices of above .90 (preferably
above .95) will be the criteria utilized to indicate a well-fitting
model (CFI: Hu & Bentler, 1999; TLI: Hu & Bentler, 1999).
For RMSEA, a fit of less than .05 will be taken to indicate a
well-fitting model (Browne & Cudeck, 1992). Finally, the re-
quirement of parsimony leads to the selection of a model with
the fewest parameters that still meets the other criteria.
Two primary models were tested. The first model (see Fig-
ure 1) examined the transformational leadership characteristics
and gender predicting alcohol use and risky sexual behaviors.
The model fit the data well, 2 (n = 543, 49) = 191.42, CFI
= .97, TLI = .96, RMSEA = .07. The second model (see Figure
2 for the parameter estimates) was similar to the first model
except that gender was removed. The second model also fit the
data well, 2 (n = 543, 41) = 165.23, CFI = .98, TLI = .97,
RMSEA = .08. Since the second model is nested within the first
model, a chi-square difference test examined the difference in
the fit statistics, 2 (8) = 26.19, p = .0001. The test suggests
that the second model is a significant improvement over the
first model.
Discussion
The characteristics of transformational leadership predict levels
of alcohol consumption and hooking up in a collegiate sample.
It seems that even when gender is accounted for the transfor-
mational leadership characteristics relate to higher levels of
risky behaviors. This finding is consistent with studies that
examined leaders on athletic teams (e.g., Leichliter et al., 1998)
and in Greek organization (e.g., Cashin et al., 1998). It seems
that regardless of the context of the leadership (i.e., athletic
team, Greek organization, or in general) that transformational
leadership traits are related to less positive health behaviors.
Table 2.
Means and standard deviations on variables by gender.
Male Female
Transformational L eadership
Idealized Influence (Attributed) 2.49 (.73) 2.53 (.65)
Idealized Influence (Behavior) 2.48 (.72) 2.68 (.67)
Inspirational 2.63 (.79) 2.78 (.70)
Intellectual Stimulation 2.55 (.74) 2.66 (.66)
Individualized Consideration 2.49 (.68) 2.65 (.65)
Alcohol
Number of Drinking Days per Week 1.80 (1.46) 1.74 (1.46)
Typical Number of Drinks 4.88 (4.10) 3.56 (2.39)
Peak Drinking Occasion in Past 30 Days 8.40 (6.74) 5.39 (3.96)
Risky Sex
Number of Sexual Encounters 1.25 (3.23) 1.48 (2.77)
Number of Hook Ups in Last Week 1.55 (3.80) 1.15 (2.12)
Number of Hook Up Partners .64 (.58) .67 (.60)

R. M. WARD, J. L. WEINER
.73***
.86***
.97***
.73***
.97***
.58***
.92***
.93***
.93***
.94***
.93***
-.20***
-.004
.46***
.13**
.17*** .31***
Alcohol
Use
Typical Number of
Drinking Days Per Week
Typical Number of
Drinks per Drinking Day
Highest Drinking
Occasion in Past 30 Days
Risky Sex
Number of Sexual
Encounters
Number of Hook Ups
No. of People involved in
Recent Hook Up
Gender
Transformational
Leadership
Idealized Influence
(Attributed)
Idealized Influence
(Behavior)
Inspirational/
Motivational
Intellectual
Stimulation
Individualized
Consideration
X2 (n = 543, 49) = 191.42
CFI = .97
TLI = .96
RMSEA = .07
Figure 1.
Transformational leadership and gender predict risky sex and alcohol behaviors, *p < .05; **p < .01; ***p < .001.
.74***
.86***
.97***
.72***
.98***
.57***
.92***
.93***
.93***
.94***
.93***
.43***
.13**
.30***
Alcohol
Use
Typical Number of
Drinking Days Per Week
Typical Number of
Drinks per Drinking Day
Highest Drinking
Occasion in Past 30 Days
Risky Sex
Number of Sexual
Encounters
Number of Hook Ups
No. of People involved in
Recent Hook Up
Transformational
Leadership
Idealized Influence
(Attributed)
Idealized Influence
(Behavior)
Inspirational/
Motivational
Intellectual
Stimulation
Individualized
Consideration
X2 (n = 543, 41) = 165.23
CFI = .98
TLI = .97
RMSEA = .08
Figure 2.
Transformational leadership predicts alcohol use and risky sex, *p < .05; **p < .01; ***p < .001.
Interestingly, the multivariate analyses of the leadership
characteristics and risky sexual behaviors did not replicate the
previously literature completely (e.g., Eagly et al., 2003). With
respect to the leadership characteristics, women reported higher
levels of two of the subscales of transformational leadership.
Further research is needed to determine if the lack of difference
on the other aspects of transformational leadership is unique to
the collegiate population. Moreover, there were no gender dif-
ferences on the sexual experience items. This finding is sur-
prising given the numerous studies to the contrary (e.g., Bogle,
2008; Owen et al., 2010; Paul & Hayes, 2002). It is possible
that the utilization of online survey methods might have lead to
this result. Online surveys may be lead to only certain students
electing to complete the survey and possibly less socially de-
sirable responses (in contrast to Bogle’s interviews).
Transformational leadership characteristics being linked to

R. M. WARD, J. L. WEINER
risky health behaviors has implications. Whereas these leader-
ship characteristics are related to positive outcomes (e.g., suc-
cessful organizations; Cress et al., 2001) and are considered
traits desirable to promote, it is plausible that the promotion of
these traits are also leading to increases in negative health be-
haviors as well. However, a longitudinal study is needed to test
this relationship and establish a causal link. Potentially, the
relationship between leadership traits and risky health behav-
iors could be the influence of a third variable (e.g., coping).
Participants with leadership traits might use the risky behaviors
to cope with the stress associated with their leadership charac-
teristics.
Additional research is also needed to determine if the trans-
formational leadership characteristics are related to the negative
outcomes associated with risky behaviors. Whereas the current
study links the characteristics to the risky behaviors and previ-
ous literature relates being an athletic leader or Greek organiza-
tion leaders to more negative consequences (e.g., blacking out;
Cashin et al., 1998), it is unclear is the leadership traits will
relate to higher levels of consequences. Potentially, leadership
characteristics might buffer the experiences of the negative
consequences.
In the research, transformational leadership traits, alcohol
consumption, and hooking up have differences across the gen-
ders. However, in the structural equation models, the influence
of gender on these variables did not significantly improve the
models. It is possible that the impact of the transformational
leadership characteristics on the risky health behaviors is more
predictive than gender. In addition, gender might moderate the
relationship between the variables. The model should be exam-
ined separately across gender and utilizing tests of invariance.
Given the relative dearth of literature in the risky health behav-
ior and leadership area, additional research is needed.
This research is not without limitations. The data were col-
lected via online questionnaires using email invitations. Unfor-
tunately, the response rates for these invitations were low and
potentially lead to a response bias. However, the levels of al-
cohol consumption (Weschler et al., 2002), leadership traits
(Bass & Avolio, 1997), and hooking up (Paul & Hayes, 2002)
are consistent with published values. In addition, the data were
collected cross-sectionally. Further longitudinal research is
needed to explore the direction and nature of the relationships.
In addition, as mentioned previously potential third variables
might be mediating the relationship between transformational
leadership traits and risky health behaviors.
In college students, high levels of alcohol consumption and
risky sexual behaviors are associated with a number of negative
consequences (e.g., lower grades, accidentals, injuries, sexual
assault, pregnancy, death; Abbey, 2002; Grello et al., 2006;
Weschler et al., 1999). In contrast, leadership characteristics
related to positive outcomes (Cress et al., 2001). However, in
college students, it seems that these same characteristics are
linked to higher levels of risky health behaviors. Given the
recent movement to increase leadership characteristics in col-
lege students, it is important to examine the potential negative
impact that an increase in these traits might have.
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