Psychology
2011. Vol.2, No.4, 355-358
Copyright © 2011 SciRes. DOI:10.4236/psych.2011.24055
Third-Person Perception and Health Beliefs
John Chapin
Pennsylvania State University, Monaca, USA.
Email: jrc11@psu.edu
Received March 26th, 2011; revised May 2nd, 2011; accepted June 11th, 2011.
A survey of 316 medical professionals was used to study third-person perception (TPP) within the context of a
public health issue, intimate partner violence (IPV) and to explore theoretical linkage between TPP and the
health belief model. Medical professionals exhibit TPP, believing they are less influenced than patients by media
depictions of IPV. In terms of the Health Belief Model, one element, perceived susceptibility, emerged as a pre-
dictor of TPP.
Keywords: Third-Person Perception, Health Belief Model, Intimate Partner Violence
In lay terms, third-person perception (Davison, 1983) is the
belief that media messages affect others more than they affect
oneself. The phenomenon has become a mainstay of communi-
cations theory, with a growing literature documenting the im-
pact of third-person-perception (TPP) on attitudes and behav-
iors (For reviews, see Conners, 2005; Golan & Day, 2008).
TPP has been documented in a number of contexts, including
advertisements (Chia, 2009; Sigal, 2009), news coverage (Coe
et al., 2008; Frederick & Neuwirth, 2008), and on-line games
(Boyle, McLeod, & Rojas, 2008; Zhong, 2009).
While TPP is well established in the literature, the phe-
nomenon remains of interest to scholars and practitioners, be-
cause people act on their perceptions. The most established
attitudinal/behavioral link is the willingness to censor (Boyle,
McLeod, & Rojas, 2008; Cohen & Weimann, 2008). For in-
stance, college students who exhibit third-person perception
regarding Internet pornography are also more willing to censor
content or support stricter legislation (Zhao & Cai, 2008). Per-
son-perception has also been linked with a number of attitudes
and behaviors, including voting decisions (Golan, Banning, &
Lundy, 2008; Jeffres et al., 2008), support for legal action (Day,
2008; Frederick & Neuwirth, 2008), and decreased risk behav-
iors (Chapin, 2000; Lewis, Watson, & Tay, 2007).
A smaller, but growing literature is exploring TPP and health.
The purpose of the current study is to examine TPP within the
context of a public health issue (intimate partner violence) and
to explore theoretical linkage between TPP and the health belief
model.
Only in recent years has the medical community begun to
fully recognize intimate partner violence (IPV) as a public
health crisis. According to a popular website for medical pro-
fessionals (emedicinehealth.com), women in the U.S. are more
likely to have been injured, raped, or murdered by a male part-
ner than by all other types of attackers. Twice as many women
report sexual assault by their husbands as report assault by
strangers. Every year, about 2,000 women are murdered by
their current or former male partners in the U.S. One in seven
women going to the doctor’s office have a history of partner
abuse. One in four women seeking care in the emergency de-
partment, for any reason, is a domestic-violence survivor, and
one in four women has been abused at some point in her life.
The current study surveys medical professionals about third-
person perception, health beliefs, and IPV.
TPP and Health
While third-person perception is a broad concept, applicable
to any type of media messages, only a small percentage of pub-
lished findings explore TPP regarding health-related topics. A
study of Chinese college students (Chia & Wen, 2009) found
TPP regarding the impact of idealized body images in adver-
tisements. Students who exhibited higher degrees of TPP also
tended to make more negative self-assessments about their own
body image. The findings have clear implications for eating
disorders, as well as mental health issues. Two studies (Cho &
Boster, 2008; Chock et al., 2007) documented TPP regarding
anti-drug advertisements among adolescents. College students
exhibiting first-person perception, the belief that oneself is
more influenced by media messages than are others, also ex-
hibit increased information seeking about bird flu (Wei, Lo, &
Lu, 2008); thus TPP may be linked with more active media
consumption. Another study of adolescents (Chapin, 2000)
documented TPP regarding safer-sex messages. Adolescents
who exhibited higher degrees of TPP were more likely to en-
gage in sexual activity at earlier ages and less likely to use
condoms during intercourse.
Health Belief Model
One of the cornerstones of health communication is the
Health Belief Model (HBM). The model is a cognitive decision
theory. As such, it assumes that individuals make rational deci-
sions about their health, based on an internal cost/benefit analy-
sis. According to the model, there are four types of health be-
liefs: 1) perceived susceptibility, 2) perceived severity, 3) per-
ceived benefits, and 4) perceived barriers.
A vast literature documents the ability of the HBM to predict
health behaviors. Two of the elements, perceived susceptibility
and perceived severity, emerge as strong predictors. For in-
stance, Lin, Simoni and Zemon (2005) studied sexual behaviors
and HIV risk among Taiwanese college students. The rate of
HIV infection in Taiwan has risen 15% each year since 1997,
ranking it among the highest in HIV/AIDS cases in Asia. Ac-
J. CHAPIN
356
cording to the Global Sex Survey, the Taiwanese are one of the
least sexually active peoples in the world, but they engage in
unprotected sex more frequently: 38% reported having unpro-
tected sex without knowledge of their partner’s sexual history.
The study reported that 57% of female and 69% of male stu-
dents were sexually active. Consistent with previous surveys,
only 27% of males and 18% of females reported consistent
condom use; on the other end of the spectrum, 11% of males
and 18% of females reported never using condoms. Elements of
the HBM did not predict the number of sexual partners or the
frequency of sex, but did predict consistent condom use. Stu-
dents who believed they were susceptible to HIV infection,
believed condoms would protect them from infection (per-
ceived benefits), and reported fewer barriers (access to con-
doms, embarrassment, cost) were the most likely to use con-
doms consistently. Perceived severity also predicted condom
use, but in the opposite direction: students who viewed HIV as
a treatable condition were more likely to use condoms consis-
tently than students who viewed AIDS as a death-sentence. A
likely reason for this unexpected finding is stigma—if some-
thing is too horrible to think about—we don’t.
A key to applying the HBM to IPV is understanding beliefs.
A study of domestic violence in the military revealed that over
half of enlisted women (57%) support routine domestic vio-
lence screening among the ranks (Carlson et. al, 2006). Women
in the military differ from civilians in that 73% of enlisted
women vs 43% of civilian women believe routine screening
and reporting would increase womens’ risks of subsequent
violent attacks. When battered women leave their abusive part-
ners, they are at their highest risk of murder. Because the mili-
tary reports domestic abuse among the ranks, the risk of vio-
lence could similarly be heightened as batterers are exposed
and their careers are at stake. Several factors emerged as barri-
ers to disclosing abuse, including perceived damage to their
own or their partner’s military careers, embarrassment, and loss
of control (about when or if to involve the police).
Another study (Campo, Poulos, & Sipple, 2005) applied the
HBM to hazing. Hazing is under-reported for a number of rea-
sons, but 20 to 50 hazing-related deaths are reported from col-
lege campuses in the United States each year. Around a third
(36%) of the college students surveyed reported that they were
involved in activities that constitute hazing. Most occurred
within fraternities or varsity athletic programs. The most com-
monly reported hazing activities were drinking contests/games
and sleep deprivation. Overall, students agreed that hazing was
harmful, but were neutral about perceived benefits including: 1)
their susceptibility to harm; 2) whether their friends approved
of their activities; 3) the enjoyment of hazing activities; 4) and
the belief that hazing builds group cohesion. Three factors that
best predicted students’ ability to remove themselves from po-
tentially dangerous situations included having friends outside
the organization, perceived likelihood of being harmed, and
friends within the organization that support the decision. Per-
ceived susceptibility fits well with the HBM. The other two
elements are purely social. If students will maintain friendships
both inside and outside the organization, they are better able to
withstand the pressure to endure h a z i n g.
Hypotheses
Based on the preceding review of the literature, the following
hypo theses are posited:
H1: Medical professionals will believe patients are more af-
fected than themselves by media depictions of IPV (Third-
person perception).
H2: TPP will increase as elements of the HBM (perceived
susceptibility, perceived severity, perceived benefits, and per-
ceived barriers) increase.
In order to test the behavioral component of TPP, an addi-
tional hypothesis is posited:
H3: Beliefs about community attitudes and willingness to in-
tervene in IPV cases will be predicted by TPP.
Method
Participants
A total of 316 medical professionals participated in the study,
between July 2009 and June 2010. Participants were medical
students/interns (69%), nurses (24%), and administrators (7%)
in Pennsylvania. Individuals were targeted for inclusion be-
cause they either currently screened patients for IPV or were
preparing to do so in the future. The sample was 89% female,
90% Caucasian, ranging in age from 27 to 66 (X = 32.1, SD =
13.3). The sample is representative of people enrolled in nurs-
ing programs in this region.
Procedures
Participants were recruited by a women’s center providing
IPV training to improve screening quality in the region. All
study measures were completed prior to the training to prevent
priming or skewing results. Participation was voluntary. In
some cases, participants did not respond to all survey items.
The most common items skipped were age and race. Missing
cells were not including in analysis, resulting in a lower N for
some tests. The study was approved by the university’ s IRB for
use with human subjects. APA ethical guidelines were strictly
adhered to.
Materials
Third-person perception was measured with a standard in-
strument (Rubin, Rubin, Graham, Perse, & Seibold, 2009).
Participants completed the following two items on a Likert-type
scale (1 = not at all; 7 = very much): 1) how much are patients
affected by media depictions of intimate partner violence? 2)
how much are YOU affected by media depictions of intimate
partner violence? A measure of TPP is obtained by subtracting
the “other” rating from the “self” rating. TPP is indicated by a
negative mean, which can be interpreted as the perception that
others are more influenced than oneself.
Two items measured beliefs about community attitudes and
willingness to intervene in IPV cases: “Most community mem-
bers are willing to intervene in cases of spousal abuse once they
become aware.” “Most community members do not approve of
spousal abuse.” Both items were measured on a Likert-type
scale ranging from strongly disagree (1) to strongly agree (7).
The Health Belief Model was measured through a series of
questions, each measured on a Likert-type scale ranging from
strongly disagree (1) to strongly agree (7): 1) perceived suscep-
tibility: “Compared to other people my age in the US, my
chances of being abused by an intimate partner are lower”; 2)
J. CHAPIN 357
perceived severity: “The physical impact of domestic abuse can
be severe;” the emotional impact of domestic abuse can be
severe.” These two items were summed; 3) perceived benefits:
“Domestic violence services available to patients at the hospital
are useful and easily accessible”; 4) perceived barriers: “There
are numerous obstacles which impact a victim’s ability to leave
their situation.” All of the items were summed to create a HBM
scale. The resulting scale demonstrated low to moderate inter-
nal consistency (α = .71).
Participants also self-reported their age, race, and gender.
Results
Table 1 displays zero-order correlations among the variables
predicting third-person perception. Doing so allows readers to
compare and weigh the relationships across variables. Standard
multiple regression was used to identify the predictors of TPP.
Analysis of residual plots indicates that assumptions regarding
normality, linearity and homoscadasticity were met. Table 2
displays the regression analysis.
H1 predicted TPP, that medical professionals believe they
are less likely than patients to be influenced by media portray-
als of IPV. TPP is indicated by a group mean significantly less
than zero. As predicted, Participants believed they (X = 2.2, SD
= 1.1) were less influenced by news coverage of crime than
others (X = 3.4, SD = 1.1), t (301) = 2.1, p < .000. H1 was sup-
ported. The finding is consistent with the literature. No rela-
tionship between TPP and demographic variables (age, gender,
and race) was predicted, and none emerged. Because TPP is
indicated by a negative mean, signs are reversed in the table for
ease of interpretation.
H2 predicted TPP would increase as elements of the Health
Belief Model (perceived susceptibility, perceived severity, per-
ceived benefits, and perceived barriers) increased. While a sig-
nificant relationship between the HBM and TPP is indicated on
Table 1, the relationship fails to explain any unique variance in
the regression model. A single HBM element, perceived sus-
ceptibility, emerges as the strongest predictor of TPP: 41.4% of
participants agreed or strongly agreed with the statement,
“Compared to other people my age in the US, my chances of
being abused b y an in tim ate par tn er ar e lowe r.” N earl y on e th ird
(30.2%) disagreed or strongly disagreed with the statement. The
remaining 11.8% responded in the middle of the scale. The
remaining components of the HBM were not significantly re-
lated to TPP. H2 was partially supported.
H3 tested the attitudinal/behavioral component of TPP, pre-
dicting a relationship between TPP and beliefs about attitudes
and willingness to intervene in IPV cases. While most partici-
pating medical professionals (84.3%) agreed or strongly agreed
that most communi ty membe rs do not approve of IPV, less than
one fourth (23.1%) believe most community members are will-
ing to intervene in IPV cases. TPP predicts beliefs about will-
ingness to intervene, but not beliefs about attitudes. H3 is par-
tially supported.
Discussion
The purpose of the current study was to examine third-person
perception within the context of a public health issue (intimate
partner violence) and to explore theoretical linkage between
TPP and the health belief model.
Nurses and medical interns were selected to participate in the
study, because they are likely to screen incoming patients for
IPV. Findings suggest medical professionals do exhibit TPP,
believing they are less influenced than are patients by media
depictions of IPV. Previous findings indicate that people who
exhibit TPP engage in less information seeking about the topic
and may be less critical viewers. This is especially problematic
in the case of IPV, because medical dramas, police dramas, and
court dramas tend to showcase extreme cases for dramatic ef-
fect. Ultimately, misperceptions gleaned from TV could nega-
tively impact effective screening of IPV and the quality of pa-
tient care. In this case, TPP was related to beliefs about com-
munity members’ willingness to intervene in IPV cases. Be-
tween advertisements, public service announcements, news
coverage, and entertainment programs, there is a rich area of
health-relate d me ssages yet to be explored in future research.
In terms of the Health Belief Model, one element, perceived
Table 1.
Zero-order correlations among variables predicting third-person perception.
2 3 4 5 6 7 8
1. TPP .24** .18* .18* .09 .09 .08 .05
2. HBM/Susceptibility - .14 .16* .14 .01 .04 .06
3. HBM - .60** .75** .67** .24** .18*
4. Interve ntion - .21** .03 .13 .09
5. Attitude - .36 ** .10 .19*
6. HBM/Severity - .06 .13
7. HBM/Benefits - .33**
8. HBM/Barriers -
Note. *p < .05, **p < .01. 1) TPP (Third-person perception); 2) HMB/Susceptibility (Health Belief Model, Susceptibility to IPV); 3) HBM (Health Belief Model); 4)
Intervention (Perceived wil lingnes s of communit y members to intervene in IPV cases); 5) Attitude (Perceived approval of community members of IPV); 6) HBM/Severity
Severity of IPV for victims); 7) HBM/Benefits (Benefits of hospital resources for IPV victims); 8) HBM/Barriers (Barriers to victims for IPV services). (
J. CHAPIN
358
Table 2.
Summary of linear regression analysis for variables predicting third-
person perception.
Adj. r2 = .10
N = 306
Predictor B SE B β
HBM/Susceptibility .11 .06 .16*
HMB .04 .10 .08
*p < .05
susceptibility, emerged as a predictor of TPP. A similar con-
struct, optimistic bias, has been linked with TPP in the past
(Chapin, 2000; Salwen & Dupagne, 2003). Perceived suscepti-
bility and perceived severity tend to be the strongest predictors
of attitudes and behaviors in the HBM literature. In this case,
98.7% agreed or strongly agreed that the emotional impact of
IPV is severe and 98.1 agreed or strongly agreed that the physi-
cal impact of IPV is severe. The lack of variance may explain
the insignificant finding. While it was not the focus of this paper,
it’s interesting to note that both community attitudes about IPV
and willingness to intervene were more strongly related to the
HBM than to TPP. The finding solidifies the value of the model
for IPV scholars and advocates. It also provides the groundwork
for future linkages between the HBM and TPP literatures.
A number of limitations should be considered before inter-
preting the results of this study. The study is based on a con-
venience sample of medical personnel gathered for training on
intimate partner violence. Test measures were collected prior to
the training to limit skewed responses, but participants were
aware of the topic and some priming may have occurred.
Conflict of Interest Statement
None to report.
References
Boyle, M., McLeod, D., & Rojas, H. (2008). The role of ego enhance-
ment and perceived message exposure in third-person perception
judgments concerning violent video games. American Behavioral
Scientist, 52, 165-185. doi:10.1177/0002764208321349
Campo, S., Poulos, G. & Sipple, J. (2005). Prevalence and profiling:
Hazing among college students and points of intervention. American
Journal of Health Behavior, 29, 137-149.
Carlson, A., Campbell, J., Garza, M., Campo, P., Dienemann, J., Kub,
J., Jones, A., & Lloyd, D. (2006). Domestic violence in the military:
Women’s policy preferences and beliefs concerning routine screen-
ing and mandatory repor ting. Military Medicine, 171, 729-735.
Chapin, J. (2000). Third-person perception and optimistic bias among
urban minority at-risk youth. Communication Research, 27, 51-81.
doi:10.1177/009365000027001003
Chia, S. (2009). When the east meets the west: An examination of
third-person perceptions about idealized body image in Singapore.
Mass Communication and Society, 12, 423-445.
doi:10.1080/15205430802567123
Chia, S., & Wen, N. (2009). College men’s third-person perceptions
about idealized body image and consequent behavior. Paper pre-
sented at the annual meeting of the International Communication
Association.
Cho, H., & Boster, F. (2008). First and third person perceptions on
anti-drug ads among adolescents. Communication Research, 35,
169-189. doi:10.1177/0093650207313158
Chock, T., Fox, J., Angelini, J., Lee, S., & Lang, A. (2007). Telling me
quickly: How arousing fast-paced PSAs decrease self-other distinc-
tions. Communication Research, 34, 618-63 6.
doi:10.1177/0093650207307900
Coe, K. Tewksbury, D., Bond, B., Drogos, K., Porter, R., Yahn, A., &
Zhang, Y. (2008). Hostile news: Partisan use and perceptions of ca-
ble news programming. Journal of Communication, 58, 201-219.
doi:10.1111/j.1460-2466.2008.00381.x
Cohen, J., & Weimann, G. (2008). Who’s afraid of reality shows? Ex-
ploring the effects of reality shows and the concern over their social
effects on willingness to censor. Communication Research, 35,
382-397. doi:10.1177/0093650208315964
Conners, J. (2005). Understanding third-person effect. Communication
Research Trends, 24, 3- 22.
Davison, W. (1983). The third-person effect in communication. Public
Opinion Quarterly, 47, 1-15. doi:10.1086/268763
Day, A. (2008). Out of the living room and into the voting booth: An
analysis of corporate public affairs advertising under the third-person
effect. American Behavioral Scientist, 52, 243-260.
doi:10.1177/0002764208321354
Frederick, E., & Neuwirth, K. (2008). The second-person effect and its
role in formation of active issues publics. Mass Communication and
Society, 11, 514-538. doi:10.1080/15205430802368613
Golan, G., Banning, S., & Lundy, L. (2008). Likelihood to vote, candi-
date choice, and the third-person effect. American Behavioral Scien-
tist, 52, 278-290. doi:10.1177/0002764208321356
Golan, G., & Day, A. (2008). The first-person effect and its behavioral
consequences: A new trend in the twenty-five year history of
third-person effect research. Mass Communication and Society, 11,
539-556. doi:10.1080/15205430802368621
Jeffres, L., Neundorf, K., Bracken, C., & Atkin, D. (2008). Integrating
theoretical traditions in media effects: Using third-person effects to
link agenda-setting and cultivation. Mass Communication and Soci-
ety, 11, 470-491. doi:10.1080/15205430802375303
Lewis, I., Watson, B., & Tay, R. (2007). Examining the effectiveness of
physical threats in road safet y advertising: The role of the third-person
effect, gender and age. Transportation Research, 10, 48-60.
Lin, P., Simoni, J. & Zemon, V. (2005). The health belief model, sexual
behaviors, and HIV risk among Taiwanese immigrants. AIDS Educa-
tion and prevention, 17, 469- 483. doi:10.1521/aeap.2005.17.5.469
Rubin, B., Rubin, A., Graham, E., Perse, E., & Seibold, D. (2009).
Communication research measures II: A sourcebook. New York:
Routledge.
Salwen, M., & Dupagne, M. (2003). News of Y2K and experiencing
Y2K: Exploring the relationship between the third-person effect and
optimistic bias. Media Psychology, 5, 57-82.
doi:10.1207/S1532785XMEP0501_3
Sigal, B. (2009). The third-person effect in Israeli women’s attitude to
TV commercials and their images. Paper presented at the annual
meeting of the International Communication Association.
Wei, R., Lo, V., & Lu, H. (2008). Third-person effects of health news:
Exploring the relationships among media exposure, presumed media
influence, and behavioral intentions. American Behavioral Scientist,
52, 261-277.
Zhao, X., & Cai, X. (2008). From self-enhancement to supporting cen-
sorship: The third-person effect process in the case of Internet por-
nography, Mass Communication and Society, 11, 437-462.
doi:10.1080/15205430802071258
Zhong, Z. (2009). Third-person perceptions and online games: A com-
parison of perceived antisocial and prosocial game effects. Journal of
Computer-Mediated Communication, 14, 286-306.
doi:10.1111/j.1083-6101.2009.01441.x