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Journal of American College Health
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A/H1N1 Vaccine Intentions in College Students: An
Application of the Theory of Planned Behavior
Vinita Agarwal PhDa
a Department of Communication Arts, Salisbury University, Salisbury, Maryland
Accepted author version posted online: 29 Apr 2014.Published online: 15 Aug 2014.
To cite this article: Vinita Agarwal PhD (2014) A/H1N1 Vaccine Intentions in College Students: An Application of the Theory of
Planned Behavior, Journal of American College Health, 62:6, 416-424, DOI: 10.1080/07448481.2014.917650
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Major Article
A/H1N1 Vaccine Intentions in College Students:
An Application of the Theory of Planned Behavior
Vinita Agarwal, PhD
Abstract. Objective: To test the applicability of the Theory of
Planned Behavior (TPB) in college students who have not previ-
ously received the A/H1N1 vaccine. Participants: Undergraduate
communication students at a metropolitan southern university.
Methods: In January–March 2010, students from voluntarily par-
ticipating communication classes completed a hardcopy survey
assessing TPB and clinically significant constructs. Hierarchical
regression equations predicted variance in vaccine intentions of
students who had not received a flu shot (ND198; 70%
Caucasian). Results: The TPB model explained 51.7% (p<.001)
of variance in vaccine intentions. Controlling for side effects, self-
efficacy and perceived comparative susceptibility predicted inten-
tions when entered in the first block, whereas attitudes, subjective
norms, and perceived behavioral control significantly contribute
when entered in the second block. Conclusions: For students who
have not previously received a flu vaccine, vaccine communica-
tion should utilize self-efficacy and perceived comparative suscep-
tibility to employ the TPB to promote vaccine intentions.
Keywords: A/H1N1 vaccine intentions, college students,
pandemic influenza A (H1N1) 2009 virus, perceived comparative
susceptibility, Theory of Planned Behavior
Although the novel pandemic influenza A (H1N1)
2009 virus disproportionately impacted college
students in the 2009–2010 flu season, surveillance
data suggest that only 8% of college students accepted the
A/H1N1 vaccine.
1
Epidemiological studies indicate that
young adults up to 24 years of age in college settings are at
a higher risk of contracting influenza.
2
It is one of the objec-
tives of the Healthy Campus 2020 initiative of the Ameri-
can College Health Association to reduce the proportion of
college students who report adverse performance from
cold/flu/sore throat (from 18% in 2010 to 16.2% in 2020;
AI-1.4, Question 45A7) and increase the proportion of
college students who receive the influenza vaccine each
year (from 39.9% in 2010 to 43.9% in 2020; Question 40C,
Item IID-12).
3
The pandemic influenza A (H1N1) 2009 virus, also
known as the A(H1N1)pdm09 virus (A/H1N1), was identi-
fied in April 2009 as a genetically and antigenically distinct
form of the influenza A virus subtype previously found in
swine.
4
The A/H1N1 virus was declared a global pandemic
in June 2009. In the United States, the Centers for Disease
Control and Prevention’s (CDC’s) 2009 H1N1 influenza
vaccination campaign (A/H1N1 vaccine) was the primary
public health initiative to address the health threat, with a
goal to increase vaccination uptake among those identified
by epidemiological and virologic data to be at higher risk
of contracting infection.
5
The US Public Health Emergency
for 2009 H1N1 Influenza expired on June 23, 2010, when
the A/H1N1 influenza virus was classified as postpandemic.
However, the virus is expected to continue to behave as a
seasonal influenza A virus in the postpandemic stage, thus
underscoring the need to continue to update pandemic
surveillance and preparedness.
6
Young adults are susceptible to health-compromising
behaviors, in part due to a heightened sense of invulnerabil-
ity that leads them to ignore risks.
7,8
Evidence of the opti-
mistic bias in college students has been well documented.
For example, recent findings examining the A/H1N1 out-
break in Fall 2009 demonstrate that a sense of self-efficacy
contributes to vaccine intentions in students, and the rela-
tionship was moderated by comparative optimism after con-
trolling for perceived risk.
9
Further, studies from different
national contexts suggest that although young adults may
make changes in hygienic behavior in response to flu preven-
tion messages,
10
barriers to vaccine acceptance in this popu-
lation persist. These include factors such as a lack of
perception of vaccination as an efficacious antiepidemic
measure,
11
or a lack of perception of the A/H1N1 virus as a
credible threat.
12
In the United States, despite the
Dr Agarwal is with the Department of Communication Arts at
Salisbury University in Salisbury, Maryland.
Copyright Ó2014 Taylor & Francis Group, LLC
416
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institutional availability of preventive vaccines such as the
trivalent inactivated influenza vaccine (TIV), often free of
charge for the seasonal flu, low levels of vaccine accep-
tance have been noted among students.
13,14
Challenges
faced by CDC’s vaccination programs include effective
promotion of vaccination services to target audiences and
getting providers and immunization programs to work
together.
15
The 2009–2010 flu season A/H1N1 monovalent inacti-
vated vaccine and the live attenuated vaccine for the
A/H1N1 influenza virus were distinct from the seasonal tri-
valent inactivated (TIV) and live attenuated (LAIV) influ-
enza vaccines.
16
The 2013–2014 seasonal TIV includes the
H1N1 strain and is made to protect against 3 flu viruses—
the influenza A(H1N1) virus, an influenza A (H3N2) virus,
and an influenza B virus, alongside an additional quadriva-
lent vaccine that protects against 2 influenza A viruses and
2 influenza B viruses.
5
However, in order to be effective,
vaccine communication needs to be tailored to audiences’
immunization knowledge and beliefs. In addition to weigh-
ing vaccine characteristics, individuals also consider vac-
cine perceptions and their likelihood of infection when
weighing the acceptability of voluntary preventive vac-
cines.
17,18
For example, A/H1N1 vaccine–specific miscon-
ceptions such as fear of the live virus in the LAIV was
confused with the A/H1N1 vaccine, which has the inacti-
vated (killed) virus, which had a negative influence on vac-
cination acceptance.
19
Other factors such as the influence
of social networks supportive of vaccination
20
and past
influenza vaccine behaviors (eg, having had a flu shot in the
past 5 years) have also been found to influence vaccine
acceptance
21
and intentions.
22
As a value-expectancy model incorporating attitudes,
subjective norms, and perceived behavioral control to
understand intentions and behavior, the Theory of Planned
Behavior (TPB) can provide a useful framework to examine
vaccination intentions.
23,24
The TPB has been used as a the-
oretical framework to examine A/H1N1 vaccination among
different populations and contexts in a few studies glob-
ally.
25–27
For example, support was found for the TPB
model in predicting vaccination intentions among priority
group adults in the United Kingdom, highlighting the need
to target interventions to well-defined groups.
28
More
recently, support has also been found for augmented TPB
models incorporating perceived susceptibility,
29
anticipated
emotions,
30,31
and self-efficacy
32
in a range of contexts and
populations, thus highlighting the need to further examine
these variables in the TPB.
As the TPB has found support in a range of content
domains and populations,
33–35
by extending it to the
domain of student voluntary vaccination acceptance,
research can provide public health professionals with useful
insights for reaching specific audiences. This study extends
the applicability of the TPB to understand A/H1N1 vacci-
nation intentions in college students who have not accepted
the vaccine along with the contribution of self-efficacy and
perceived comparative susceptibility.
Theory of Planned Behavior
The TPB builds on the assumption that individuals can
rationally evaluate their options and beliefs associated with
a behavior before formulating their intention to perform the
behavior.
36
Further, the TPB posits that behavioral inten-
tion, or the assessment of whether or not a person plans to
perform a particular behavior, is the most important and
immediate antecedent of the actual performance of that
behavior (ie, stronger intentions predict a greater likelihood
of performing the behavior). According to the TPB, an indi-
vidual’s attitude toward the behavior, subjective norms of
behaviors, and perceived behavioral control toward the
behavior are the 3 determinants predicting behavioral
intentions.
36
Attitude toward the behavior is an individual’s positive
or negative belief about performing a specific behavior and
is determined by the individual’s beliefs about the conse-
quences of performing the behavior (behavioral beliefs)
alongside an evaluation of those consequences (outcome
evaluations).
36
In general, an individual is more likely to
perform a behavior if he or she has a positive attitude
toward the behavior (eg, student nurses’ intention to get the
influenza vaccine is predicted by their attitude toward the
vaccine
22
).
Subjective norms are a function of beliefs that significant
others (eg, close friends or family) approve or disapprove
of the behavior and are determined by one’s normative
beliefs (ie, the beliefs that underlie subjective norms) and
motivation to comply with those beliefs. According to the
TPB, an individual is more likely to perform a specific
behavior, such as obtain a vaccine, when the individual per-
ceives that important others hold positive beliefs about the
vaccine, recommend getting vaccinated, or receive the
vaccine.
36
Perceived behavioral control comprises an individual’s
beliefs about the presence of factors that may impede or
facilitate their ability to perform the behavior.
36
The con-
ceptual domain of perceived behavioral control includes
the components of self-efficacy (ease or difficulty of per-
forming a behavior) and controllability (the extent to which
the performance of the behavior is within the individual’s
volitional control).
37
In order to understand the distinct con-
tributions of self-efficacy and controllability, these can be
considered independently in the TPB model.
37
As self-effi-
cacy has been noted as a salient factor in college students,
32
the present research seeks to determine its specific contribu-
tion as well as the specific contribution of controllability
(perceived behavioral control) in the TPB model.
The goal of the present study is to examine the applica-
bility of the TPB, taking into account the contribution of
perceived comparative susceptibility in the A/H1N1 vac-
cine intentions of college students who have not received
the vaccine. The following hypotheses are tested:
H1a: Self-efficacy will negatively predict vaccination inten-
tions, controlling for perception of vaccine side effects
and perceived comparative susceptibility such that
A/H1N1 Vaccine Intentions in College Students
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greater self-efficacy will predict lower vaccination
intentions.
H1b: Perceived comparative susceptibility will positively
predict vaccination intentions, controlling for perception
of vaccine side effects and self-efficacy such that greater
perceived comparative susceptibility will predict higher
vaccination intentions.
H2a: Controlling for subjective norms and perceived behav-
ioral control, attitudes will positively predict vaccination
intentions after accounting for vaccine side effects, self-
efficacy, and perceived comparative susceptibility.
H2b: Controlling for attitudes and perceived behavioral
control, subjective norms will positively predict vaccina-
tion intentions after accounting for vaccine side effects,
self-efficacy, and perceived comparative susceptibility.
H2c: Controlling for attitudes and subjective norms, per-
ceived behavioral control will negatively predict vaccina-
tion intentions after accounting for vaccine side effects,
self-efficacy, and perceived comparative susceptibility.
METHODS
Setting, Population, and Recruitment
The student sample was derived from self-selected
undergraduate communication classes of a midsize south-
ern, metropolitan research university. The total university
undergraduate student body in Fall 2009–2010 academic
year (AY) was 22,031.
38
Undergraduate student enrollment
demographics in 2009–2010 AY reflect a predominantly
Caucasian student population with a roughly equal distribu-
tion of males and females (males: ND10,608; females:
ND11,423; 76.1% Caucasian, 11.1% African American;
total undergraduate enrollment: ND15,619), with under-
graduate class ranking reflecting a slightly lower enrollment
in the sophomore and junior years (freshman: nD4,026;
sophomore: nD2,972; junior: nD3,075; and senior: nD
4,130). A majority of the first-time freshmen (59.2%)
reported living on campus and the university reported an
overall 95% student housing occupancy rate. The university
comprises 12 schools conferring degrees in law, business,
arts and sciences, dentistry, social work, medicine, music,
engineering, and public health, among others.
38
Hardcopy survey administration was completed among
participating undergraduate communication classes in the
communication department between January 2010 and
March 2010. An e-mail was sent to faculty members of the
communication department soliciting study participation of
students in return for extra credit in class. As communication
students study media messages and effects, the study partici-
pants can be considered to be more aware of media messages
and goals than other majors. Participating classes ranged
from senior-level public relations (advanced public relations)
to introductory (introduction to mass communication) clas-
ses, and research methods and special topics (health commu-
nication) courses. Thus, participants ranged from freshmen,
sophomores, juniors, and seniors (Table 1). Students who
were not interested in participating in the survey were pro-
vided an alternative extra credit opportunity. The university
Institutional Review Board approved the study.
Participant recruitment was conducted by the researcher
providing an in-person introduction to the study in the par-
ticipating classes before hardcopy survey administration.
Because of the high media coverage and awareness of the
A/H1N1 virus during the data-gathering period, the intro-
duction explained that communication students were partic-
ipating in the study to understand the role of individual
factors in student intention to obtain the A/H1N1 vaccine.
Additional surveys were also given to instructors to hand
out to students who were absent or otherwise unable to
obtain the survey. Students who were interested in partici-
pating in the study were given the option to return the com-
pleted surveys at the end of 2 weeks during a class
announcement and sign their name on a sign-up sheet in
return for extra credit in the class. Participants could also
drop the survey in a box outside the researcher’s office with
a sign-up sheet for receiving class credit. In that case, the
researcher e-mailed the completed list to the class instruc-
tor. Because a mass e-mail for participant recruitment was
not sent out to the entire student population, a response rate
cannot be determined. However, the sample participant
demographics show these are reflective of the undergradu-
ate population at the university.
Measures
The TPB constructs of attitudes, subjective norms, per-
ceived behavioral control, and behavioral intention toward
the A/H1N1 vaccine were adapted from Ajzen’s TPB ques-
tionnaire.
23
The construct of perceived comparative suscep-
tibility was adapted from McQueen et al,
39
and vaccine
side effects and self-efficacy were adapted from Chapman
and Coups.
40
Unless otherwise mentioned, all variables
were averaged on a 1–5 Likert scale (1 Dthe lowest value
of the construct and 5 Dthe highest). Items that were
phrased in the semantically opposite direction (ie, 5 Dlow-
est value of construct and 1 Dhighest value of construct)
were reverse-coded such that the higher value of the con-
struct measured the higher numerical choice on the item
response set. Once all items for a scale were in the same
direction, the items were averaged to create the scale.
Demographic Characteristics
Participants were asked to report their age, sex, ethnicity,
class ranking, and whether they knew the university was
offering a free A/H1N1 vaccine (Table 1).
Psychological Measures
Participants reported their attitudes, subjective norms,
perceived behavioral control, perceived comparative sus-
ceptibility, self-efficacy, and behavioral intention on 5-point
interval-level Likert scales.
Agarwal
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TABLE 1. Selected Characteristics of Study Participants
Total sample Have never received flu shot Have received flu shot
Characteristic N%n%n%
Age (years) ND489 nD196 nD291
18–25 460 92.0 186 93.9 272 93.2
26–30 17 3.4 6 3.0 11 3.8
31–40 7 1.4 2 1.0 5 1.7
41–60 4 0.8 1 0.5 3 1.0
61 and older 1 0.2 1 0.5 0 0.0
Ethnicity ND476 nD192 nD282
Caucasian 376 75.2 138 69.7 237 81.2
African American 71 14.2 41 20.7 29 9.9
Asian 19 3.8 10 5.1 9 3.1
Pacific Asian 2 0.4 0 0.0 2 0.7
Other 8 1.6 3 1.5 5 1.7
Sex ND489 nD196 nD291
Male 206 41.2 80 40.4 125 42.8
Female 281 56.2 115 58.1 165 56.5
Other 2 0.4 1 0.5 1 0.3
Year in school ND486 nD196 nD288
Freshman 106 21.2 38 19.2 68 23.3
Sophomore 124 24.8 59 29.8 65 22.3
Junior 148 29.6 64 32.3 83 28.8
Senior 106 21.2 34 17.2 71 24.3
Other 2 0.4 1 0.5 1 0.3
Know university was offering free flu shot this spring ND486 nD195 nD290
Yes 352 70.4 128 64.6 223 76.4
No 133 26.6 66 33.3 67 22.9
Other 1 0.2 1 0.5 0 0.0
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A/H1N1 Vaccine Intentions in College Students
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Analyses
Frequencies and other descriptive statistics were used to
describe the sample. Factor analysis utilizing principal
components analysis (PCA) framework with Varimax rota-
tion was employed to assess the proportion of variance
explained by the factor in the data. Cronbach’s alpha coeffi-
cient was examined to assess internal consistency of items
toward measuring the construct. Participants who marked
“No” to the binary question: “Have you ever received a flu
shot” (Yes D1; No D2) were selected into the data file
used for the present study. Hierarchical multiple regression
equations were set up to test the TPB model. The statistical
software IBM SPSS Statistics 21 (IBM, Armonk, New
York) was used for data analysis.
RESULTS
Sample Description
Table 1 reports the study participant characteristics of all
participants and the study sample of students who did not
receive a flu shot. From the parent data file, those who
marked “No” to the condition “Have you ever received a
flu shot?” (nD198; 39.6%) were selected to a new data set
that was employed for the present analyses (94% between
18 and 25 years old; 70% Caucasian, 21% African Ameri-
can; 58% female). The study sample characteristics are
reflective of the population of undergraduate enrollment at
the university.
Univariate Analyses
Attitude
Attitude was defined as “a person’s overall evaluation of
performing the behavior in question,”
23
and included the
items “Getting the H1N1 vaccine from my university will
be beneficial for me” (λD.93), “Getting the H1N1 vaccine
from my university will be painful” (reverse coded),
“Getting the H1N1 vaccine from my university will be
good for me” (λD.92), “Getting the H1N1 vaccine from
my university is not important for me” (λD.64) (reverse
coded), and “Getting the H1N1 vaccine from my university
will be useful for me” (λD.89). All items loaded satisfacto-
rily, with the factor loading of 1 item being acceptable
(“H1N1 vaccine is important to me” [λD.64]). One item
(“Getting H1N1 vaccine from my university will be
painful” (λD¡.025) did not load satisfactorily and was
dropped from the analysis. Factor analysis (PCA with Vari-
max rotation) obtained a single factor solution (eigenvalue
D2.902, 72.5% variance; 4 items, MD2.61, SD D.90, N
D198). Reliability was good (aD.87).
Subjective Norms
Subjective norms was defined as a measure of family and
friends approval of the behavior
23
and comprised the
average of items including “My immediate family members
think I should get the H1N1 flu vaccine at my university
this spring (2010)” (λD.69), “I want to do what my imme-
diate family members think I should do about getting the
H1N1 flu vaccine this spring (2010)” (λD.30), “My imme-
diate family members would approve of me getting the
H1N1 flu vaccine at my university this spring (2010)” (λD
.67), and “Most of my family members received an H1N1
vaccine last fall (Fall 2009)” (λD.60), and similarly for
friends (“Friends think I should” [λD.67]; “Friends
approve of me getting a vaccine” [λD.58]; and “Friends
received a vaccine” [λD.67]). Factor analysis (PCA with
varimax rotation) indicated that most items loaded accept-
ably on factor 1 (λ>.55). Two items (“I want to do what
my immediate family members think...”[λD.30]; and “I
want to do what my friends think...”[λD.46]) did not
load satisfactorily and were dropped from the study. Factor
analysis (PCA with varimax rotation) obtained a 2-factor
solution (eigenvalue of first factor D2.514, 41.9% vari-
ance; 6 items, MD2.73, SD D.63, ND198). Reliability
was acceptable (aD.72).
Perceived Behavioral Control
Perceived behavioral control was defined as an individu-
al’s perception of their ability to perform a specific behav-
ior.
23
The scale was assessed as an average of 2 items
including “It is totally up to me whether I would like to
obtain an H1N1 flu vaccine at my university” and “It is
mostly up to me to decide whether or not I get an H1N1 flu
vaccine at my university” (rD.28, p<.001; 2 items, MD
4.08, SD D.61, nD198).
Perceived Comparative Susceptibility
Defined as “the likelihood of experiencing personal harm
if no action is taken,”
39,41
the 3 items assessing susceptibil-
ity loaded excellently and included “Compared to the aver-
age man/woman your age, how likely are you to get the
H1N1 flu?” (λD.86), “Compared to all students similar to
you who did get a flu shot, how likely do you think you are
to get the H1N1 flu?” (λD.88), and “Compared to all stu-
dents similar to you who did not get a flu shot, how likely
do you think you are to get the H1N1 flu?” (λD.86). Factor
analysis (PCA with Varimax rotation) obtained a 1-factor
solution (eigenvalue of first factor D2.241, 74.7% vari-
ance; 3 items, MD2.44, SD D.84, ND198). Reliability
was acceptable (aD.83).
Side Effects
Side effects were measured as “How likely do you think
it is that the flu vaccine would cause a person to have a
severe reaction?” (1 item, MD1.83, SD D.38, ND198).
Self-efficacy
Understood as the ease or difficulty in performing a
behavior in a specific domain,
37
self-efficacy was measured
420 JOURNAL OF AMERICAN COLLEGE HEALTH
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as the average of 2 items: “If I take precautions, I will lower
my risk of contracting the H1N1 infection enough that I
probably don’t need to get the H1N1 vaccine anyway,” and
“If I take all the necessary precautions, I don’t need to get
the H1N1 vaccine”; rD.57, p<.001; MD3.49, SD D.90,
ND198).
Behavioral Intention
Defined as whether or not a person plans to perform a
particular behavior,
23
items assessing this measure included
the average of “I intend to get an H1N1 vaccine at my uni-
versity this season” (λD.94), “I will try to get an H1N1
vaccine at my university this season” (λD.86), and “I plan
to get an H1N1 vaccine at my university this season” (λD
.95; 3 items, MD1.89, SD D.88, ND198). Factor analysis
(PCA with Varimax rotation) obtained a single-factor solu-
tion (eigenvalue D2.506, 83.5% variance; 3 items, MD
1.89, SD D.88, ND198). Reliability was good (aD.90).
Multivariate Analysis
To test the hypotheses, a hierarchical regression model
was constructed. Vaccine side effects, self-efficacy, and
perceived comparative susceptibility were entered as inde-
pendent variables in the first block. Attitude, subjective
norms, and perceived behavioral control were entered
together as independent variables in the second block.
Behavioral intention was entered as the dependent variable
(Table 2).
The overall model explained a substantial and significant
51.7% (p<.001) amount of variance in intentions
(Table 2). The first model with side effects, self-efficacy,
and perceived comparative susceptibility explained 13.8%
(p<.001) of variance in vaccine intentions. After account-
ing for side effects, self-efficacy, and perceived compara-
tive susceptibility, the TPB model comprising attitudes,
subjective norms, and perceived behavioral control
explained an additional 37.9% (p<.001) of variance in
vaccine intentions.
In the first block, self-efficacy made a significant contri-
bution (bD¡.255, p<.001) (Table 2) to intentions after
controlling for vaccine side effects and perceived compara-
tive susceptibility. Thus, higher self-efficacy predicted
lower vaccination intentions and H1a was supported. Per-
ceived comparative susceptibility made a significant contri-
bution to intentions after controlling for vaccine side
effects and self-efficacy (bD.238, pD.001) (Table 2).
Thus, H1b was supported.
In the second block, the regression coefficients demon-
strate that all TPB predictors, attitudes (bD.476, p<
.001), subjective norms (bD.335, p<.001), and perceived
behavior control (bD¡.306, p<.001), were significant
contributors to behavioral intention. Attitudes and per-
ceived behavioral control (in the negative direction) are
fairly close in strength, whereas subjective norms are close
in its contribution to A/H1N1 vaccination intentions. Thus,
H2a, H2b, and H2c are supported (Table 2).
COMMENT
The study is the first to demonstrate the substantial con-
tribution of the TPB constructs in vaccine intentions for
college students who have not previously received a flu
vaccine after accounting for the contribution of self-effi-
cacy and perceived comparative susceptibility. Further-
more, the findings demonstrate that controlling for vaccine
side effects, self-efficacy and perceived comparative sus-
ceptibility are important factors influencing student vacci-
nation decisions for this segment of students. Because prior
behaviors are a significant predictor of future intentions and
behaviors, the study makes a unique contribution by identi-
fying salient factors contributing to vaccination intentions
for this specific segment of students.
The support for the overall TPB model after accounting for
the contribution of self-efficacy and perceived comparative
susceptibility suggests important insights for vaccine com-
munication. Because preventive health behaviors for emer-
gent risks are often received with doubts such as those
regarding adequate vaccine testing and safety, highlighting
positive beliefs of the A/H1N1 vaccine as beneficial, useful,
helpful, and good can promote vaccination intentions. Sec-
ond, the study extends prior research finding positive influ-
ence of social networks on health behaviors by demonstrating
the contribution of subjective norms of friends and family (ie,
TABLE 2. Hierarchical Regression Model Testing the TPB in A/H1N1 Vaccine Intentions
Independent variable b(SE)SE btp DR
2
,F(x, y), p
Block 1
a. Side effects ¡.204 .165 ¡.086 ¡1.236 .218 DR
2
D.138
b. Self-efficacy ¡.255 .068 ¡.260 ¡3.742 <.001 F(x, y)D9.805 (3, 184), p<.001
c. Perceived comparative susceptibility .238 .074 .223 3.229 .001
Block 2
a. Attitude .476 .062 .487 7.725 <.001 DR
2
D.379
b. Subjective norms .335 .085 .237 3.938 <.001 F(x,y)D47.392 (3, 181), p<.001
c. Perceived behavioral control ¡.306 .077 ¡.211 ¡3.959 <.001
Note. DR
2
model
D.517, p<.001. Dependent variable = Behavioral intention.
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whether family and friends think it is good, or have received
the vaccine) in this audience segment. Third, independent of
the contribution of self-efficacy, vaccine intentions in this
group of college students is also significantly influenced by
perceived behavioral control—the perception that the vacci-
nation acceptance decision is completely in the hands of the
individual. Although this is in line with existing findings of
resistance to authority in college students in general, it also
suggests that this audience segment (ie, those who have not
previously accepted a flu vaccine) is significantly influenced
by a sense of individual control over decisions.
Furthermore, the study demonstrates support for 2 clini-
cally significant variables of self-efficacy and perceived
comparative susceptibility as important factors to take into
consideration. First, self-efficacy is an important contribu-
tor in vaccination intentions for students who have not pre-
viously obtained a flu vaccine such that students with
higher self-efficacy are less likely to plan to obtain the vac-
cine. Because of challenges inherent in increasing accep-
tance of voluntary, preventive vaccines in young adults (eg,
a disregard for authoritative recommendations
7,8,12
), vac-
cine communication among students who have not accepted
the flu vaccine can highlight how self-efficacy is demon-
strated through portraying vaccine acceptance. Second, per-
ceived comparative susceptibility has found support in
several risk preventive behaviors, and the study findings
extend its applicability in vaccination intentions of college
students. For this segment of students, the study finds that,
controlling for self-efficacy and perception of vaccine side
effects, increasing susceptibility compared with other stu-
dents like them promotes vaccination intentions.
Limitations
Although the study makes an important contribution to
the applicability of the TPB to the domain of student flu
vaccine intentions, several limitations should be noted.
First, because the study design was cross-sectional, the find-
ings are primarily correlational. Second, although the con-
venience in-class recruitment strategy compromised the
ecological validity of the study, the study sample is reflec-
tive of the overall undergraduate student population of the
university. Third, as participants were self-selected into the
study, the findings may be biased toward those students
who were more (or less) concerned about vaccination due
to preexisting beliefs about vaccination, and nonresponse
bias cannot be assessed. Fourth, since the survey was
administered to undergraduate students from classes in the
communications department, which generally have a
greater focus on media effects and health campaigns, care
should be taken to not overgeneralize its representative-
ness to a larger student population. Because studies on
college students in general reflect important similarities in
beliefs among college students (eg, in the existence of
optimistic bias), future studies can extend the findings
among a range of college student demographics. Fifth,
although the measures used in the study are from
validated scales, these rely on participant self-reports and
are susceptible to a recall bias.
Conclusions
The study demonstrates support for the TPB model in
college student vaccination decisions for the specific seg-
ment of students who have not received a flu vaccine. Fur-
thermore, for this specific segment of college students,
this study is the first to provide insight into the contribu-
tion of self-efficacy and perceived comparative suscepti-
bility. This is a particularly challenging group for public
health professionals to reach, partly because of the signifi-
cant influence of past behaviors on future intentions and
behaviors. Segmenting audiences helps understand the
beliefs and motivations of specific target audiences and is
key to the success of health communication efforts seeking
to reach population segments that can benefit from a spe-
cific health behavior with prevention messages and behav-
ior recommendations.
4
Implications for Student Health Centers
To reach college students who have not previously
received a flu shot, vaccine communication messages
should underscore individual choice and ability to obtain
the vaccine as an act of responsibility, as well as highlight
positive beliefs (eg, usefulness and benefits), susceptibility
compared with other college students, testimony of family
and friends, and control factors.
ACKNOWLEDGMENTS
The author is grateful to the executive editor and 2 anon-
ymous reviewers for their insightful comments and feed-
back that guided the development of the manuscript. The
author thanks the Department of Communication, Univer-
sity of Louisville, Louisville, Kentucky, for the support pro-
vided the study. Earlier versions of this paper were
presented at the Kentucky Conference in Health Communi-
cation, 2010, the National Communication Association,
2011, and the Eastern Communication Association, 2012.
FUNDING
No funding was used to support this research and/or the
preparation of the manuscript.
CONFLICT OF INTEREST DISCLOSURE
The author has no conflicts of interest to report. The
author confirms that the research presented in this article
met the ethical guidelines, including adherence to the legal
requirements, of the United States and received approval
from the Institutional Review Board of the University of
Louisville.
422 JOURNAL OF AMERICAN COLLEGE HEALTH
Agarwal
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NOTE
For comments and further information, address corre-
spondence to Vinita Agarwal, Department of Communica-
tion Arts, Salisbury University, FH 272, 1101 Camden
Avenue, Salisbury, MD 21801, USA (e-mail: vxagar-
wal@salisbury.edu).
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Received: 23 August 2013
Revised: 31 March 2014
Accepted: 20 April 2014
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