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ORIGINAL PAPER
Sexually Explicit Media Use by Sexual Identity: A Comparative
Analysis of Gay, Bisexual, and Heterosexual Men in the United States
Martin J. Downing Jr.
1
•Eric W. Schrimshaw
2
•Roberta Scheinmann
1
•
Nadav Antebi-Gruszka
2
•Sabina Hirshfield
1
Received: 23 March 2016 / Revised: 5 August 2016 / Accepted: 9 August 2016
Springer Science+Business Media New York 2016
Abstract Advances in production and distribution of sexually
explicit media (SEM) online have resulted in widespread use
among men. Limited research has compared contexts of use and
behaviors viewed in Internet SEM by sexual identity. The current
study examined differences in recent SEM use (past 6 months) by
sexual identity among an ethnically diverse sample of 821 men
who completed an online survey in 2015. Both gay and bisexual
men reported significantly more frequent use of Internet SEM
compared to heterosexual men. Although most participants
reported viewing SEM at home (on a computer, tablet, or
smartphone),significantly more gaymen reported SEMuse
at a sex party or commercial sex venue than either heterosexual
or bisexual men. Sexual identity predicted viewing of high-risk
and protective behaviors in separate logistic regression models.
Specifically, compared to heterosexual men, gay and bisexual
men had increased odds of viewing condomless anal sex (gay
OR 5.20, 95 % CI 3.35–8.09; bisexual OR 3.99, 95 % CI 2.24–7.10)
and anal sex with a condom (gay OR 3.93, 95 % CI 2.64–5.83;
bisexual OR 4.59, 95 % CI 2.78–7.57). Compared to gay men,
heterosexual and bisexual men had increased oddsof viewing
condomless vaginal sex (heterosexual OR 27.08, 95% CI
15.25–48.07; bisexual OR 5.59, 95 % CI 3.81–8.21) and vaginal
sex with a condom (heterosexual OR 7.90, 95 % CI 5.19–12.03;
bisexual OR 4.97, 95 % CI 3.32–7.44). There was also evidence
of identity discrepant SEM viewing as 20.7 % of heterosexual-
identified men reported viewing male same-sex behavior and
55.0 % of gay-identified men reported viewing heterosexual
behavior.Findings suggest theimportance of assessingSEM use
across media types and contexts and have implications for
research to address the potential influence of SEM on sexual
behavior (e.g., investigate associations between viewing
condomless vaginal sex and engaging in high-risk encounters
with female partners).
Keywords Sexually explicit media Pornography
Internet Sexual identity Sexual orientation
Introduction
Advances in the production and distribution of sexually explicit
media (SEM) have resulted in widespread availability and con-
sumption on the Internet (Escoffier, 2009; Rosser et al., 2012;
Weinberg,Williams, Kleiner, &Irizarry, 2010). Consistentwith
this greater availability of SEM online, data from the General
SocialSurvey (GSS) havedocumented asteady increase inSEM
consumption among US men since the 1970s (Wright, 2013).
According to recent figures from TrafficJunky Media Kit
(2015), a leading advertising network for adult content Web
sites, their top three SEM Web sites receive a combined average
of over 92 million daily visitors; visitors are overwhelmingly
male (75 %), heterosexual (75 %), and age 18–44 (74 %). Not
surprisingly, men are more likely than women to access SEM
(Albright,2008) and todo somorefrequently (Hald &S
ˇtulhofer,
2016; Morgan, 2011;Paul,2009; Weinberg et al., 2010). Nev-
ertheless, much of what we know about SEM use among men
pertains to their frequency of use, though emerging research
attention is being paid to the types of media they consume (e.g.,
heterosexual, bisexual, gay, or lesbian), behavioral content and
preferences, and contexts of use.
In a review of Internet-based SEM research conducted over a
10-yearperiod,Short,Black,Smith,Wetterneck,andWells
&Martin J. Downing Jr.
mdowning@healthsolutions.org
1
Public Health Solutions, 40 Worth Street, 5th Floor, New York,
NY 10013, USA
2
Mailman School of Public Health, Columbia University,
New York, NY, USA
123
Arch Sex Behav
DOI 10.1007/s10508-016-0837-9
(2012) noted that most of the studies published during this
timeframe contained predominantly heterosexual samples
or did not assess participants’ sexual identity. To our knowl-
edge, there are no U.S. studies that havecompared the behav-
ioral content of Internet SEM viewed by sexual identity or
sexual orientation. Do men tend to viewSEM that corresponds
to their sexual identity or are they more diverse in what they
watch? This is an important distinction to make as researchers
consider the role of SEM in sexual behavior, particularly
behaviors that increase one’s risk for HIV and other sexually
transmitted infections (STIs),and effective waysto reach SEM
audiences with risk reduction messaging (e.g., Rosser et al.,
2012). Peter and Valkenburg (2012) assessed the frequency of
viewingInternet SEM featuringpenetrative sex,group sex, sex
with only men, and sex with only women among exclusively
and nonexclusively heterosexual men in the Netherlands.
However,it is not clear from theiranalyses whether theauthors
examined differences in content viewed by sexual identity.
Hald and S
ˇtulhofer (2016) recentlyconducted exploratory fac-
tor analyses of pornography types by sexual orientation in a
Croatian sample, noting similarities among heterosexual and
non-heterosexual men in viewing group sex behaviors (e.g.,
bukkake, gang bang scenes featuring one woman and at least
three men).
Given the importance of understanding cultural contrib-
utors to men’s sexual aggression against women, much of the
extant research on SEM content has focused on heterosexual
media and the portrayal of violence toward women (Salmon
& Diamond, 2012; Sun, Bridges, Johnason, & Ezzell, 2016;
Wright & Tokunaga, 2016). Additional areas deserving attention
are non-heterosexual media, comparisons of sexual content
across media types, and specific sexual risk behaviors per-
formed by SEM actors (i.e., condomless vaginal and anal sex),
especially in light of recent cross-sectional evidence that view-
ing condomless sexual encounters in Internet SEM is predictive
of engaging in high-risk sex (as discussed below). What remains
unclear is whether men are differentially exposed to high-risk
SEM content (i.e., attributed to sexual identity, context of SEM
use, or viewing preferences), which has implications for targeting
SEM-based HIV/STI prevention strategies. Nevertheless, some
comparisons of sexual behaviors in gay and heterosexual DVD-
based SEM have found that heterosexual videos were less likely
to depict anal sex (Salmon & Diamond, 2012), condom use during
anal sex (Grudzen et al., 2009), and external ejaculation (Salmon
& Diamond, 2012). By the early 1990s, producers of gay male
SEM committed to showing condoms during anal sex scenes for
the occupational safety of performers and to model safer sex for
viewers (Bishop, 2015). Although the heterosexual SEM industry
never fully adopted this practice, it did implement a testing policy
aimedat preventing acquisitionand transmissionof HIVand other
STIs (Escoffier, 2009; Goldstein, Steinberg, Aynalem, & Kerndt,
2011).
It is critical to understand the content of SEM because a
significant and growing body of research has suggested that
viewing SEM, and specific behaviors in SEM, may influence
real-life behavior among heterosexual and non-heterosexual
viewers. Several studies have revealed potential benefits of view-
ingSEM. Specifically, some researchhas shown that viewingSEM
isassociated with havinga more positiveattitude aboutsex (Hald &
Malamuth, 2008; Hald, Smolenski, & Rosser, 2013). Viewing of
SEM also increases the appeal of certain behaviors (e.g., anal sex),
regardless of gender or sexual orientation (Weinberg et al., 2010).
Among heterosexuals, investigators have found that they use SEM
to increase arousal before or during sex, to learn new sexual posi-
tions and activities, to relieve stress and sexual frustration, and to
fantasize about having sex with the performers (Albright, 2008;
Boies, 2002; Hare, Gahagan, Jackson, & Steenbeek, 2015;Paul&
Shim, 2008; Sun et al., 2016; Traeen & Daneback, 2013). Per-
ceived positive effects of SEM use by men who report same-sex
encounters include an interest in trying new sexual behaviors or
positions, enjoyment of sex, and understanding of one’s sexual
orientation (Hald et al., 2013; Nelson, Leickly, Yang, Pereira, &
Simoni, 2014a).
Despite the potential benefits of SEM use, other research
has raised concerns that viewing specific behavioral content
may contribute to negative sexual health outcomes. The prolif-
eration of SEM online has coincided not only with a rise in use,
but also with reported decreases in safer sex behaviors among
some viewers (Peter & Valkenburg, 2011a;Rosseretal.,2012;
Wright, Tokunaga, & Kraus, 2016). Moreover, technological
innovations have since led to an increase in production and
distribution of amateur sexual content (Cronin & Davenport,
2001; Downing, Schrimshaw, Antebi, & Siegel,2014b;Green,
2004). Amateur content,which is not subject to SEM industry
HIV/STI testing or condom use policies (Griffith et al., 2012),
has alter ed‘‘the narrative and sexual e xpectations presupp osed
by most porn movies’’ (Escoffier, 2009, p. 347). While some
have speculated that increased competition from a booming
Internet-based amateur industry prompted gay male SEM stu-
dios to abandon their condom use policies (Hurley, 2009), pro-
ducers of commercial bareback (i.e., condomless anal sex) videos
argue that advances in HIV treatment and prevention (e.g.,
antiretroviral therapy, pre-exposure prophylaxis) have signif-
icantlyloweredtheriskof HIV transmission,making it possible
to meet consumer demands (Kinser, 2014;Nichols,2011).
Indeed, there has been a substantial rise in sales of SEM fea-
turing condomless sex (Escoffier, 2009). Furthermore, a r ecent
content analysis of 302 gay male SEM videos on the Internet
found depictions of condomless anal sex in 34 % of the sample
(Downing et al.,2014b); this was considerably higher thanthat
previously observed in DVD-based SEM (18 %) by Grudzen
et al. (2009).
The expanded access to SEM online has perhaps had the
greatest impact on gay, bisexual, and other men who have sex
Arch Sex Behav
123
with men (GBMSM). Limited research suggests that a greater
proportion of GBMSM view Internet SEM than heterosexual
men (Traeen, Nilsen, & Stigum, 2006). Several studies with
online samples of GBMSM found a high prevalence of Internet
SEM viewership in the past 3 months ([95 %) (Rosser et al.,
2013; Stein, Silvera, Hagerty, & Marmor, 2012). GBMSM are
also more frequent consumers of Internet SEM than hetero-
sexual men (Duggan & McCreary, 2004; Peter & Valkenburg,
2011b). Although SEM may have positive effects on the sexual
lives of GBMSM (Hald et al., 2013), widespread use may not be
without adverse consequences. Videos that depict condomless
anal sex are potentially problematic, as they may influence the
intrapersonal sexual scripts of viewers (S
ˇtulhofer, Bus
ˇko, &
Landripet, 2010) and lead some men to engage in similar activ
ities(Jonas, Hawk, Vastenburg,& deGroot, 2014; Wilkersonet al.,
2012). Multiple studies to date have documented that GBMSM
who viewed a greater proportion of SEM depicting bareback sex
had increased odds of reporting recent anal sex without a condom
(Nelson et al., 2014b; Rosser et al., 2013; Schrimshaw, Antebi-
Gruszka, & Downing, 2016a; Stein et al., 2012). Furthermore,
consumption of SEM featuring condomless anal sex may be
most problematic for men who use it as a source of sexual
information and therefore may normalize such behaviors (Ku-
bicek, Beyer, Weiss, Iverson, & Kipke, 2010;Nelsonetal.,
2014a).
Within the literature on SEM use among GBMSM, however,
researchershave primarily examinedoutcomes of interestwithin
the full sample rather than examining potential differences by
sexual identity (i.e., gay vs. bisexual). Most of the published
studies that found associations between viewing condomless
anal sex in SEM and engaging in recent anal sex without a con-
dom included substantial proportions of gay-identified men
([80 %; Nelson et al., 2014b; Schrimshaw et al., 2016a; Stein
et al., 2012), which likely accounts for the limited attention to
potential sexual identity differences. Stein et al. (2012)repor-
ted that participants who did not provide data on their SEM
viewing history were more likely to identify as bisexual. Bisexual
men remain underrepresented, and perhaps unaccounted for, in
studies of SEM use and subsequent behavioral impact. Similar
concerns have been raised regarding the lack of differentiation
between gay and bisexual men in other sexual health research
(Schnarrs et al., 2012) as well as the relative absence of bisexual
men in studies of disclosure and openness about one’s sexual
orientationand identity (Schrimshaw,Downing, &Cohn, 2016b)
and those that examine associations between sexual orientation
and mental health (Dodge et al., 2012; Schrimshaw, Siegel,
Downing, & Parsons, 2013b). There is clearly a need for parity
in sexual health research with heterosexual and non-hetero-
sexual populations, particularly studies that investigate viewing
of diverse SEM content and the potential influenceof viewing on
sexual behavior, including male and female partners.
Despite the increased attention to bareback sex in gay male
SEM,there is alack ofequivalent research onthe useof condoms
in heterosexual and bisexual media. We found a single study that
assessed attitudes toward condom use in SEM among male col-
legestudents(Kraus & Rosenberg,2016).Theauthorsreported
thatgay men held moresupportiveattitudestowardcondomuse
in SEM than heterosexual men. Yet, there were several limi-
tations of that study including: the assessment of condom use
attitudeswithout reference to specific sexualbehaviors such as
vaginalor analsex;no assessmentof the sexual behaviors(with
andwithoutcondoms)thatparticipantsviewedinSEM;andthe
inclusionof smallsubsamplesof gay (n=32) and bisexualmen
(n=17)compared toheterosexual men (n=155).Thus,research
is needed to address not only whether men are differentially
exposed to high-risk SEM content (as a potential factor of how
they sexually identify), but also to examine preferences for con-
dom use during vaginal and anal sex scenes among heterosexual
and bisexual viewers. Answers to these questions are needed
beforeresearcherscanbegintoaddressthepotentialbehavioral
impact of condomless sex in heterosexual and bisexual SEM.
Researchers have also called for more attention to venues
ofSEMuse(Rosseretal.,2012). Whileit is reasonableto believe
thatmost men accessSEM athome, scant attentionhas beenpaid
to other environments where SEM may be available or accessed.
Beyond commercial sex venues where sexually explicit videos
may be streaming for patrons (Holmes, O’Byrne, & Gastaldo,
2007; Rosser et al., 2012), there is reason to suspect that men are
increasingly accessing Internet-based SEM at work (Albright,
2008; Kuchment & Springen, 2008;Perrinetal.,2008). More-
over, widespread access to the Internet via smartphones and
tablets has likely contributed to greater use of SEM at home and
in other venues. What remains unclear is whether or not viewing
context differs by sexual identity.
The current paper reports on findings from an online sur-
vey of self-identified heterosexual, gay, and bisexual men
who viewed Internet-based SEM in the past 6 months. This
study aims to extend prior research by comparing frequency
of SEM use, viewing contexts (where and how men access
SEM; use of substances while viewing SEM; masturbation
during SEM use), content of SEM viewed (vaginal and anal sex,
with and without condoms), and viewer preferences for condom
use during vaginal and anal sex scenes by sexual identity among
an ethnically diverse sample. By taking a more inclusive approach
to examining SEM use, researchers will be better prepared to
address concerns about the influence of SEM on sexual behavior
across media types (e.g., SEM that targets heterosexual, bisexual,
and/or gay audiences).
Method
Participants
Interested individuals were asked to complete an online survey
about their experiences with and preferences regarding SEM.
Arch Sex Behav
123
Eligible participants had to: (a) be 18 years of age or older; (b) be
able to read and respond in English; and (c) reside within the
U.S. or its territories. We excluded anyone who selected‘‘Prefer
not to answer’’ when asked about their recent sexual partners.
Although the study was open to individuals of all gender types,
the current report is based on data from 821 participants who
identified their current gender as male, reported viewing Internet
SEM in the past 6 months, and self-identified as straight/hetero-
sexual, gay/homosexual, or bisexual. We focus on men asthey
are the primary users of SEM. Table1describes participant
characteristics.
Recruitment activities occurred from January 23, 2015–
November 1, 2015. To reach a diverse audience of SEM view-
ers, consistent with our eligibility criteria, study advertise-
ments were posted online to social networking Web sites (e.g.,
Twitter), a sexual networking Web site (BGCLive.com), a GPS-
based smartphone application for sexual partnering (Scruff),
Craigslist (Volunteers), research-oriented Web sites (e.g., Social
Psychology Network), and Amazon Mechanical Turk. Palm
cards featuring the study logo and detailed description were
distributed via LGBT (Lesbian, Gay, Bisexual, and Transgen-
der) organizations and professional meetings. Study invitations
were also sent to members of a national research participant reg-
istry affiliated with the lead author’s institution. The study
employed both general (e.g., online survey of viewer attitudes
aboutsexualbehaviorsshownin sexuallyexplicitvideosonthe
Internet;‘‘…study seeks to better understand attitudes of indi-
viduals who watch pornographic videos on the Internet’’; ‘‘Re-
searchers seek porn watchers’’) and specific recruitment lan-
guage (e.g., ‘‘…study of viewer attitudes about PrEP in the
Adult Film Industry’’; ‘‘Do you like to watch bareback sex?’’
‘‘Are you concerned about HIV testing standards in the pornog-
raphy industry?’’). Study advertisements posted to social net-
working Web sites incorporated relevant hashtags (#porn,
#PrEP) to engage a broader audience. Online recruitment noti-
ces provided or embedded a link to access the survey. Where
possible, recruitment notices indicated that participants should be
18 years of age or older, that the survey would take approximately
15–20 min to complete, and that there would be an opportunity
to enter a random drawing for a $20 Amazon.com electronic
gift card upon completing the survey.
There were a total of 2529 visits to the study landing page.
Of those, 186 (7.4 %) broke off immediately, and 32 (1.3%)
chose not to consent to participate. Among the 2311 individ-
uals whoconsented to participate, 1070(46.3 %) provided only
partial data.
1
We excluded 153(12.3 %) completed surveys for
providing disqualifying or duplicate data. The overall analytic
sample included 1088 surveys. Of those, 821 male-identified
participantsindicatedthat they viewed InternetSEM in the past
6 months and reported their sexual identity as gay/homosexual
(65.0 %), bisexual (18.6 %), or straight/heterosexual (16.3 %).
More than half (65.4 %) of the 821 men were recruited from
sexual networking Web sites and GPS-based smartphone appli-
cations, 19.6 % through research-oriented Web sites or a research
participant registry, 8.2 % from Amazon Mechanical Turk, 4.1 %
from Craigslist, 1.6% from social networking Web sites, and
1.1 % through study palm cards.
Procedure
The institutional review board at Public Health Solutions
approved all study procedures. A waiver of documentation of
written consent was obtained, given the Internet-based research
approach. Potential participants accessedthe study landing page
by clicking on an online study banner advertisement or study
invitation link. Palm cards directed anyone interested in par-
ticipatingto scan a QR codeor visit the study URL. Participants
provided informed consent online by reading the consent form
1
We examined differences in participant characteristics and Internet
SEM use between complete and partial cases. Several differences were
noted after applying a Bonferroni correction. A greater proportion of
bisexual-identified men had partial surveys (45.6 %) compared to
heterosexual-identified men (32.4 %) (p=.003). No other sexual
identity differences were noted. Men with complete surveys were
significantly older (M=38.08, SD =12.16) than those with partial
Footnote 1 continued
surveys (M=34.48, SD =11.24), F(1, 1467) =32.31, p\.001. A
greater proportion of men who identified their race as White (71.8 %)
completed the survey compared to men who identified as Black (54.2 %,
p\.001) or Asian, Pacific Islander, Native American or Alaska Native,
Native Hawaiian or Other Pacific Islander, or Other (44.8 %, p\.001).
Further, significantly fewer men reporting up to a high school degree or
GED completed the survey (46.1 %) compared to men with some col-
lege, Associate’s degree or Technical degree (59.3 %, p\.001), a 4-year
college degree (67.8 %, p\.001), or a professional or graduate degree
(68.6 %, p\.001). Significantly fewer men reporting an annual income
of less than $10,000 completed the survey (50.0 %) compared to those
who earned $40,000–$79,999 (63.1 %, p=.002), $80,000–$119,999
(73.2 %, p\.001), or $120,000 or more (68.7 %, p=.003). Similarly,
significantly fewer men who preferred not to answer the item about
annual income completed the survey (51.7 %) than men who reported
earning $80,000–$119,999 per year (73.2 %, p=.001). A significantly
greater proportion of men who reported a zip code corresponding to a US
state in the West region completed the survey (73.3 %) compared to men
in the Northeast (58.8 %, p=.001), Southeast (55.2 %, p\.001), and
Midwest (60.4 %, p=.001) regions. There were no differences between
complete and partial cases in relationship status, HIV status, current
residence, or use of Internet SEM in the past 6 months (yes, no).
There were significantly more completed surveys among men who
viewed SEM at home on a computer (67.6 vs. 40.3 % of men who did not
view SEM at home on a computer, p\.001), at work on a computer (73.8
vs. 59.9 % of men who did not view SEM at work on acomputer, p\.05),
or while attending a commercial sex venue (72.4 vs. 58.5 % of men who
did not view SEM while attending a commercial sex venue, p\.001).
Further, there were significantly more completed surveys among men
who viewed vaginal sex with a condom (87.9 vs. 54.4 % of men who did
not view this behavior), vaginal sex without a condom (89.1 vs. 49.6 % of
men who did not view this behavior), anal sex with a condom (87.9 vs.
39.3 % of men who did not view this behavior), and anal sex without a
condom (89.3 vs. 26.2 % of men who did not view this behavior), pvalues
\.001.Lastly, we observed no differences between complete and partial
cases in the types of Internet SEM viewed in the past 6 months.
Arch Sex Behav
123
Table 1 Comparisons of participant characteristics and recruitment source by sexual identity
Heterosexual
(a)
n=134
Gay
(b)
n=534
Bisexual
(c)
n=153
v
2
u
c
Post hoc
Race and ethnicity (N=804) 106.03*** 0.26
White or Caucasian 98 (73.1) 216 (41.5) 32 (21.3) a[b, c; b[c
Black or African-American 19 (14.2) 240 (46.2) 109 (72.7) a\b, c; b\c
Hispanic or Latino 11 (8.2) 47 (9.0) 3 (2.0) b[c
Asian, Pacific Islander, Native American or Alaska Native,
Native Hawaiian, or Other
6 (4.5) 17 (3.3) 6 (4.0)
Relationship status (N=818) 68.99*** 0.20
Single and not currently in a relationship 55 (41.0) 388 (72.9) 112 (73.7) a\b, c
In a steady relationship 25 (18.7) 79 (14.8) 18 (11.8)
Married or domestic partnership 54 (40.3) 65 (12.2) 22 (14.5) a[b, c
Education (N=818) 8.38 0.07
BHigh school graduate/GED 15 (11.3) 71 (13.3) 21 (13.7)
Some college, Associate’s degree/Technical degree 50 (37.6) 211 (39.7) 72 (47.1)
College graduate (4 years) 42 (31.6) 144 (27.1) 43 (28.1)
Professional or graduate degree 26 (19.5) 106 (19.9) 17 (11.1)
Annual income (N=776) 4.19 0.05
\$10,000 15 (11.7) 70 (13.9) 20 (13.8)
$10,000–$39,999 46 (35.9) 192 (38.2) 63 (43.4)
$40,000–$79,999 36 (28.1) 144 (28.6) 36 (24.8)
$80,000–$119,999 19 (14.8) 65 (12.9) 16 (11.0)
$120,000 or more 12 (9.4) 32 (6.4) 10 (6.9)
Current living situation (N=806) 12.81* 0.09
A house 84 (62.7) 239 (45.6) 74 (50.0) a[b
An apartment 42 (31.3) 233 (44.5) 59 (39.9) a\b
Other 8 (6.0) 52 (9.9) 15 (10.1)
HIV status (N=769) 223.75*** 0.38
Negative 74 (56.1) 272 (54.8) 113 (80.1) a, b\c
Positive
a
0 188 (37.9) 16 (11.3) b[c
Indeterminate or never got test results 0 12 (2.4) 2 (1.4) NA
Never tested 58 (43.9) 24 (4.8) 10 (7.1) a[b, c
Geographic region (N=813) 16.94* 0.10
Northeast 23 (17.4) 69 (13.0) 28 (18.7)
Southeast 37 (28.0) 171 (32.2) 55 (36.7)
Midwest 33 (25.0) 106 (20.0) 34 (22.7)
Southwest 16 (12.1) 51 (9.6) 14 (9.3)
West 23 (17.4) 134 (25.2) 19 (12.7) b[c
Recruitment source (N=821) 434.13*** 0.51
Sexual networking 13 (9.7) 396 (74.2) 128 (83.7) a\b, c
Social networking 4 (3.0) 9 (1.7) 0 NA
Craigslist 23 (17.2) 6 (1.1) 5 (3.3) a[b, c
Research (i.e., Web sites, participant registry) 33 (24.6) 112 (21.0) 16 (10.5) a, b[c
Amazon Mechanical Turk 61 (45.5) 3 (0.6) 3 (2.0) NA
Palm cards 0 8 (1.5) 1 (0.7) NA
n(%) presented. Other living situation includes a room in someone else’s house or apartment, drug treatment, detox, shelter or drop in center for
homeless people, or some other place
*** p\.001; * p\.05. Bonferroni corrections applied to post hoc comparisons (p\.017). NA (not analyzed due to low cell counts)
a
Bivariate analysis restricted to gay and bisexual men. v
2
.u
c
(Cramer’s V)
Arch Sex Behav
123
on the study landing page and clicking their agreement to par-
ticipate.
The survey included a ReCaptcha function to validate human
responses (i.e.,‘‘Please enter the code shown below in order to
proceed.’’) and offer protection from bots. This feature followed
the consent page. Internet provider (IP) addresses were collected
for each survey entry to further reduce the likelihood of partic-
ipant fraud. Survey entries with matching IP addresses (match-
ing on all four quadrants) were considered to be duplicate cases.
For duplicate cases: (1) if both entries had complete data, the
initial entry was kept for analysis; (2) if the initial entry was
incomplete, the complete entry was kept for analysis.
Participants were asked to complete an online survey that
includeditems to assess demographicinformation, recent sexual
behavior, HIV/STI testing history, history of viewing sexually
explicit videos online, and the contentof sexually explicitvideos
viewed duringthe past 6 months.The survey tookapproximately
15mintocomplete.
Due to concerns regarding survey length, participants were
offered the opportunity to be entered into a random drawing for
one of five $20 Amazon.com electronic gift cards. Those who
wereinterested in being consideredfor therandom drawing were
asked to provide an e-mail address for entry. E-mail addresses
were used to distribute e-gift cards to the winners of the drawing.
Participants who completed the survey through Amazon Mechan-
ical Turk received US $0.40, but were not eligible to enter the
randomdrawing as this servicedoes notallowfor the collection
of personal information such as an e-mail address.
Measures
Participant characteristics
The online survey included a set of demographicquestionsto
assess age, race and ethnicity, gender identity, sexual identity,
relationship status, education, annual income, housing status,
HIV testing history and status, and zip code (to assess partici-
pants’ geographic region in the U.S.). For sexual identity,
participants were asked the following question:‘‘Do you think
of yourself as…?’’ Response options included lesbian, gay or
homosexual, straight or heterosexual, bisexual, or something
else.
Internet SEM use
Survey participants were asked to report (yesor no) ifthey had
viewed pornographic videos on the Internet (on a computer,
tablet, or smartphone) in the past 6 months. The survey also
included several items to assess the types of SEM that participants
watchedon the Internet(i.e., videos featuringa manand a woman,
only men, only women, at least two men and one woman
engaging in sexual acts with each other, and at least two women
andone man engaging insexual acts witheach other). Participants
were asked to report how often in the past 6 months they watched
pornographic videos on the Internet (on a computer, tablet, or
smartphone) (adapted from Nelson et al., 2014b). Response
options included less than once a month, once a month, two to
three times a month, at least once a week, every day, two to three
times a day, once an hour, and more than once an hour. Partic-
ipants were also asked to report the number of hours spent
viewing pornographic videos on the Internet in a typical week
(Downing, Antebi, & Schrimshaw, 2014a). A single follow-up
itemassessedthelength,inminutes,of a typicalviewingsession
(adaptedfrom Nelson et al., 2014b).Thesurveyincludeditems
to better understand how participants access pornographic
videoson the Internet(i.e.,throughWebsiteswith freeviewing,
paid subscription) and viewing context (i.e., at home on a
computer, at home on a tablet or smartphone, at home on a
television, at work on a computer, at work on a tablet or
smartphone, at a sex party, in a bar, club or at an adult video
store). Further, participants were asked to report the percent-
age of time they masturbate while watching pornographic
videos on the Internet (none of the time =0% to every
time =100 %). The survey also included a single item to assess
the frequency of substance use in the context of watching
Internet SEM (Downing et al., 2014a). Response options
included none of the time, some of the time, about half of the
time, more than half of the time, and every time.
Behaviors viewed in Internet SEM
Participants were asked about the sexual behaviors that actors
were performing in pornographic videos they watched on the
Internet in the past 6 months. The list of sexual behaviors, along
with instructions to check all that apply, included: solo acts of
masturbation, mutual masturbation, oral sex, vaginal sex with a
condom, vaginal sex without a condom, anal sex with a condom,
anal sex without a condom (barebac ki ng, raw, breeding, seeding),
rimming, fisting (vaginal or anal), bondage, sadomasochism
(S&M), cock and ball torture (CBT), sounding (urethral),
watersports (golden showers, pissing/urinating), and felching
(sucking or eating cum out of someone’s anus). Further, par-
ticipants were asked to report whether or not any of the
pornographic videosthey had viewed on the Internet in thepast
6 months featured group sex scenes with more than two actors
(Nelson et al., 2014b). Response options included: group sex
with only men, group sex with only women, and group sex with
men and women.
Condom use preferences in SEM
Participants were asked about their preference for viewing
condom use during vaginal and anal sex in SEM (Rosser et al.,
2013). Specifically, those who indicated that they viewed any
Arch Sex Behav
123
vaginal sex in the past 6 months were asked whether they prefer to
watch actors perform vaginal sex with condoms or without. Sim-
ilarly, those who indicated that they viewed any anal sex in the past
6 months were asked whether they prefer to watch actors perform
anal sex with condoms or without. Response options for both items
included: without condoms (-1), with condoms (1), and I do not
care either way (0).
Data Analysis
Data cleaning and analyses were performed with IBM SPSS
version 22 (IBM, 2013). We reviewed all surveys reporting
any use of Internet SEM during the past 6 months to ensure
that participants also selected at least one type of SEM (i.e.,
featuring a man and a woman, only men, only women, at lea st
two men and one woman engaging in sexual acts with each
other, and at least two women and one man engaging in sexual
acts with each other) or sexual behavior that they viewed.
Two participants in the overall analytic sample indicated that
they viewed at least one type of SEM during the past 6 months,
butdid not report viewingany specific sexualbehaviors (perhaps
to indicate that they did not watch any of the behaviors included
with the item). Because both participants did report at least one
type of SEM viewed, we retained these surveys for analysis.
Descriptive statistics are reported for all participants unless
otherwise indicated. Comparisons between dichotomous or cat-
egorical variables were conducted using chi-square analysis.
Effect sizes for chi-square tests are reported using u
c
(Cramer’s V)
(Kline, 2013). Comparisons of categorical variables on continuous
variables were conducted using one-way analysis of variance
(ANOVA) for normally distributed variables and Kruskal–
Wallis ANOVA for non-normally distributed variables (with
post hoc comparisons using Mann–Whitney Utests). Statisti-
callysignificantassociationsarereportedat p\.05.Bonferroni
corrections were applied to the alphavalues obtained frompost
hoc comparisons. We modeled viewing of high-risk (condom-
less anal and vaginal sex) and protective behaviors (anal and
vaginal sex with a condom) using logistic regression (with sexual
identity as the predictor variable) controlling for participant char-
acteristicssignificantly associated (at p\.001)with sexualidentity
in bivariate analysis and interactions between sexual identity
and HIV status.Odds ratios and 95 % confidence intervals (CI)
are reported for logistic regression models. We also modeled
condom use preferences in SEM using linear regression, with
viewingof anal and vaginalsex (with and withouta condom) as
predictor variables and controlling for participant character-
istics (i.e., sexual identity, race and ethnicity, relationship sta-
tus, and HIV status). Unstandardizedbetas and standard errors
are reported for linear regression models.
Results
Comparisons of Participant Characteristics by Sexual
Identity (N5821)
Mean age for the sample was 37.98 years (SD =12.02). There
were no significant age differences by sexual identity [hetero-
sexual (M=36.22, SD =11.53), gay (M=38.66, SD =12.13),
bisexual (M=37.15, SD =11.94)], F(2, 821) =2.67, p=.07.
Most of the participants identified their race as Black (45.8 %) or
White (42.1 %). Heterosexual-identified men were more likely
than gay- and bisexual-identified men to be White and less likely
to be Black. Similarly, gay men were more likely than bisexual
men to be White or Hispanic/Latino and less likely to be Black.
Approximately two-thirds (67.8 %) of the sample reported that
they were single and not currently in a relationship. However,
heterosexual men were more likely than gay and bisexual men to
bemarriedorinadomesticpartnershipandlesslikelytobe
single. Nearly half of participants had at least a 4-year college
degree (46.0 %) and earned less than $40,000 per year (49.5 %).
There were no differences in education or income by sexual
identity. Most participants indicated that their current residence
was a house (48.4 %) or apartment (40.7 %). Heterosexual men
were more likely than gay men to report that they currently lived
in a house. Among those who had ever been tested for HIV, more
than half reported that their most recent HIV test was negative
(55.9 %). Gay men were more likely than bisexual men to report
their HIV serostatus as positive; because no participant identi-
fyingas heterosexual reportedan HIV-positivestatus, werestricted
this analysis to gay and bisexual men.
As shown in Table 1, gay and bisexual men were recruited
primarily through sexual networking and research-oriented
Web sites. Heterosexual men were recruited primarily through
Amazon Mechanical Turk and Craigslist. The most represented
geographic region was the Southeast (32.0 %) followed by the
West (21.4 %), Midwest (21.1 %), Northeast (14.6 %), and South-
west (9.9 %). A significantly greater proportion of gay men
reported a zip code corresponding to a US state in the West
region compared to bisexual men.
SEM Viewing Context and Frequency of Use
Mostparticipantsreported viewing SEM at home:on a computer
(85.6 %); on a tablet or smartphone (71.9 %); on a television
through an Internet connection (24.2 %); or on a television from
a DVD or On-Demand service (23.9 %). Although less com-
mon, men also reported viewing SEM at work on a tablet or
smartphone(16.1 %) ora computer (5.4 %).Venue-based SEM
viewing was also reported: in a bar, club, or at an adult video
store (17.9%); at a sex party (12.4%). Nearly all men in the
Arch Sex Behav
123
study reported accessing Internet SEM from Web sites with
free viewing (95.7%). Only a small percentage of men indi-
cated having a paid subscription for Internet SEM (10.5 %).
Heterosexual men were more likely than gay men to report
viewing SEM at work on a computer, but less likely than gay
men to view it at home on a television (e.g., DVD, On-De-
mand),at a sexparty,orin a commercialsexvenuesuchasabar,
club, or adult video store (Table 2). Gay men were more likely
thanbisexualmen to reportviewingSEMwhileat a sexpartyor
acommercialsexvenue.Whenasked aboutsubstanceuse in the
context of viewing Internet SEM, more than two-thirds (69.2 %)
of heterosexual men indicated that they did this none of the time.
Although there were no differences between gay and bisexual
men, gay men were more likely than heterosexual men to report
that they used substances while viewing Internet SEM. Hetero-
sexual men were less likely than bisexual men to indicate doing
this some of the time.
As shown in Table 2, heterosexual men were more likely to
view Internet SEM once a week or less compared to gay and
bisexual men who were more likely to view Internet SEM at
least once a day. Gay and bisexual men viewed more hours of
Internet SEM in a typical week (Mdn =3h, IQR =1–5 for
both groups) compared to heterosexual men (Mdn =2h,
IQR =1–3.75), v
2
(2, N =819) = 17.19, p\.001. Further, a
significantly greater proportion of heterosexual men reported
SEM viewing sessions lasting 10 min or less compared to gay
and bisexual men. Differences by sexual identity in the per-
centage of time that participants masturbate while watching
Internet SEM approached significance (gay [Mdn =94.00,
IQR =64.00–100.00], bisexual [Mdn =90.00, IQR =50.00–
100.00], heterosexual [Mdn =85.50, IQR =54.25–100.00]),
v
2
(2, N =812) =5.20, p=.07.
Behaviors Viewed in Internet SEM and Condom Use
Viewing Preferences
The most common sexual behaviors men reported viewing in
SEM were oral sex (86.2 %), anal sex without a condom (84.0 % ),
anal sex with a condom (65.3 %), rimming (64.8 %), solo acts of
masturbation (53.1 %), vaginal sex without a condom (40.8 %),
and mutual masturbation (39.2 %). Men also reported viewing, to
a lesser extent, felching (28.5 %), vaginal sex with a condom
(26.4 %), bondage/sadomasochism/cock and ball torture/sound-
ing (24.7 %), watersports(23.9 %), and fisting (18.1 %). Group
sex scenes featuring only men were highly reported (80.1 %)
followed by scenes featuring men and women (46.5%), and
only women (12.8 %).
Heterosexual men were significantly less likely than gay
and bisexual men to report that they viewed SEM featuring only
men, group sex with only men, mutual masturbation, anal sex
with orwithout a condom,and rimming(Table 2). However, one
in five heterosexual-identified men reported viewing SEM that
featured only men. Heterosexual men were less likely than gay
mento report viewing SEMthat featuredwatersports and felching.
They were more likely than gay and bisexual men to report that
they viewedSEM featuring group sex with onlywomen, group
sex with men and women, and vaginal sex without a condom.
Heterosexual men were alsomore likely than gay men to report
viewing SEM that featuredvaginal sex with a condom.
Gay men were significantly more likely than bisexual men
to report that they viewed SEM featuring group sex with only
men, bondage, sadomasochism, cock and ball torture, sounding,
fisting,watersports, and felching. However,they wereless likely
thanbisexual men to reportviewing SEMthat featured groupsex
with only women, group sex with men and women, solo acts of
masturbation, and vaginal sex with or without a condom.
Sexual identity significantly predicted viewing of anal sex
with a condom (referent: heterosexual; gay OR 3.93, 95 % CI
2.64–5.83; bisexual OR 4.59, 95 % CI 2.78–7.57), anal sex
without a condom (referent: heterosexual; gay OR 5.20, 95 %
CI 3.35–8.09; bisexual OR 3.99, 95 % CI 2.24–7.10), vaginal
sex with a condom (referent: gay; heterosexual OR 7.90, 95 %
CI 5.19–12.03; bisexual OR 4.97, 95 % CI 3.32–7.44), and
vaginal sex without a condom (referent: gay; heterosexual
OR 27.08, 95 % CI 15.25–48.07; bisexual OR 5.59, 95 % CI
3.81–8.21) in separate logistic regression models. In multi-
variable analyses controlling for race and ethnicity, relationship
status, and HIV status, sexual identity remained a significant
predictorfor viewing riskand protective behaviors.Specifically,
sexual identity significantly predicted viewing of anal sex with a
condom (gay AOR 4.53, 95 % CI 2.75–7.47; bisexual AOR
3.53, 95 % CI 1.96–6.35), anal sex without a condom (gay AOR
4.94, 95 % CI 2.75–8.87; bisexual AOR 4.03, 95 % CI
2.00–8.11), vaginal sex with a condom (heterosexual AOR 9.47,
95 % CI 5.44–16.46; bisexual AOR 4.69, 95 % CI 2.98–7.39),
and vaginal sex without a condom (heterosexual AOR 22.94,
95 % CI 11.83–44.49; bisexual AOR 5.76, 95 % CI 3.73–8.89).
Men who self-identified as Black or African American, com-
pared to White or Caucasian, had significantly increased odds of
reporting that they viewed anal sex with a condom (AOR 1.52,
95 % CI1.06–2.20). Men withan HIV-positive status,compared
to HIV-negative, had significantly decreased odds of reporting
that they viewed anal sex with a condom (AOR 0.49, 95 % CI
0.33–0.72). Participant characteristics were not significantly
associated with viewing of anal sex without a condom, vaginal
sex with a condom, or vaginal sex without a condom. Adding the
interaction between HIV status and sexual identity did not result
in a significant change to any of the multivariable models.
Of those participants who viewed Internet SEM featuring
anal sexin the past6 months, nearly two-thirds (61.3 %)reported
a preference for viewing condomless anal sex and only 6.8 %
reported a preference for viewing anal sex with condoms. Gay
men were more likely than bisexual men to indicate a preference
for viewing condomless anal sex. Among those who viewed
Internet SEM featuring vaginal sex in the past 6 months, more
Arch Sex Behav
123
Table 2 Comparisons of sexually explicit media use, behaviors viewed, and preferences for condom use by sexual identity
Heterosexual
(a)
Gay
(b)
Bisexual
(c)
v
2
u
c
Post hoc
Viewed SEM in the past 6 months…(N=821)
At home on a computer 89.6 85.2 83.7 2.23 0.05
At home on a tablet or smartphone 65.7 74.0 69.9 3.99 0.07
At work on a computer 9.7 4.3 5.2 6.15* 0.09 a[b
At work on a tablet or smartphone 12.7 17.2 15.0 1.79 0.05
At home on a television (e.g., DVD, On-Demand) 14.9 27.5 19.0 11.86** 0.12 a\b
At home on a television via Internet connection 20.1 26.0 21.6 2.75 0.06
In a bar, club, or at an adult video store 5.2 23.2 10.5 30.70*** 0.19 a\b; b[c
At a sex party 4.5 15.9 7.2 17.62*** 0.15 a\b; b[c
Internet SEM viewing frequency (N=816) 31.34*** 0.14
Once a week or less 37.9 18.4 17.8 a[b, c
Two to three times a week 32.6 30.3 29.6
Once a day or more 29.5 51.3 52.6 a\b, c
Length of typical SEM viewing session (N=818) 10.60* 0.08
B10 min 41.7 28.7 25.5 a[b, c
30–45 min 38.6 45.2 47.7
1 h or more 19.7 26.1 26.8
Substance use while viewing Internet SEM (N=814) 11.68* 0.08
None of the time 69.2 54.4 55.6 a[b
Some of the time 18.8 29.0 32.0 a\c
Half or more of the time 12.0 16.7 12.4
Types of Internet SEM viewed
a
SEM featuring only men 20.7 98.3 96.0 513.16*** 0.80 a\b, c
SEM featuring a man and a woman 98.5 55.0 88.3 124.26*** 0.40 a[b, c; b\c
SEM featuring only women 83.6 3.3 41.1 387.55*** 0.72 a[b, c; b\c
SEM featuring at least two men and one woman 76.9 52.9 80.4 50.42*** 0.26 a[b; b\c
SEM featuring at least two women and one man 88.5 22.5 61.8 215.32*** 0.53 a[b, c; b\c
Internet SEM behaviors (N=821)
Solo acts of masturbation 58.2 49.6 60.8 7.62* 0.10 b\c
Mutual masturbation 24.6 42.3 41.2 14.37** 0.13 a\b, c
Oral sex 89.6 85.2 86.9 1.78 0.05
Vaginal sex without a condom 88.8 22.7 62.1 229.32*** 0.53 a[b, c; b\c
Vaginal sex with a condom 56.0 13.9 44.4 129.07*** 0.40 a[b; b\c
Anal sex without a condom 61.2 89.1 86.3 63.07*** 0.28 a\b, c
Anal sex with a condom 37.3 70.0 73.2 55.81*** 0.26 a\b, c
Rimming 32.1 72.7 66.0 77.42*** 0.31 a\b, c
Fisting (vaginal or anal) 14.9 21.0 11.1 8.91* 0.10 b[c
Bondage, sadomasochism, cock and ball torture, sounding
b
24.6 27.9 13.7 12.84** 0.12 b[c
Watersports
c
13.4 28.7 16.3 19.52*** 0.15 a\b; b[c
Felching
d
12.7 33.9 23.5 25.93*** 0.18 a\b; b[c
Group sex with only men 8.2 95.9 88.2 525.17*** 0.80 a\b, c; b[c
Group sex with only women 44.8 2.8 19.6 176.99*** 0.46 a[b, c; b\c
Group sex with men and women 85.8 32.6 60.8 137.38*** 0.41 a[b, c; b\c
Preferences for vaginal sex condom use in SEM (N=413) 10.19* 0.11
No preference 31.7 45.1 41.5
Without condoms 65.0 50.5 50.0 a[b
Arch Sex Behav
123
than half (54.7 %) reported a preference for viewing condom-
less vaginal sex and 5.1 % reported a preference for viewing
vaginal sex with a condom. Compared to gay men, heterosexual
men were more likely to indicate a preference for viewing con-
domless vaginal sex. Bisexual men did not differ from either gay
or heterosexual men in their preference for viewing condomless
vaginal sex.
We modeled condom use preferences for vaginal sex in SEM
using linear regression, with viewing of vaginal sex with a con-
dom and without a condom as predictor variables. Unstandard-
ized betas and standard errors are reported in Table 3.Themodel,
controlling for participant characteristics (i.e., sexual identity,
race and ethnicity, relationship status, and HIV status), explained
23.9 % of the variance in condom use preferences for vaginal sex
in SEM. Viewing vaginal sex with a condom and without a
condom was both significantly associated (in expected direc-
tions) with condom use preferences for vaginal sex. Similarly,
we modeled condomuse preferences for anal sexin SEM, with
viewing of anal sex with a condom and without a condom as
predictor variables. The model, controlling for participant
characteristics, explained 21.7 % of the variance in condom
use preferences for anal sex in SEM. Viewing anal sex with a
condom and without a condom was both significantly asso-
ciated (in expected directions) with condom use preferences
for anal sex.
Discussion
This study is one of the first to compare the behavioral content
of Internet SEM viewed by sexual identity, building on prior
work by Peter and Valkenburg (2012). Findings suggest that
the behaviors men view in SEM tended to reflect their sexual
identity. Specifically, heterosexual men were more likely than
gay and bisexual men to report that they viewed SEM featuring
women, vaginal sex, group sex with only women, and group sex
with menand women duringthe past 6 months.Gay and bisexual
men were more likely than heterosexual men to report that they
viewed SEM featuring only men, mutual masturbation, and
group sex with only men during the past 6 months.
Nevertheless, the findings also indicated that many men
viewed SEM content inconsistent with their stated sexual iden-
tity. It was not uncommon for heterosexual-identified men to
report viewing SEM containing male same-sexbehavior (20.7 %)
and for gay-identified men to report viewing heterosexual behav-
ior in SEM (55.0 %). It was also not uncommon for gay men to
report that they viewed vaginal sex with (13.9 %) and without a
condom (22.7 %) during the past 6 months. Stein et al. (2012)
found that nearly half of their sample of MSM had ever viewed
heterosexual SEM. Interestingly, though not clear why, bisex-
ual men were more likely than gay men, but not heterosexual
men, to report viewing solo acts of masturbation in SEM. Hetero-
sexual men did not differ from gay men in their viewing of SEM that
featured fisting, bondage, sadomasochism, cock and ball tor-
ture, and sounding. However, gay men were more likely than
heterosexual and bisexual men to report viewing SEM that
featured watersports and felching, behaviors that have been
found in certain genres (e.g., kink, fetish) of gay male SEM
(Downing et al., 2014b). Likewise, gay men were more likely
than bisexual men to report viewing of SEM that featured
fisting, bondage, sadomasochism, cock and ball torture, and
sounding in the past 6 months.
These data further suggest a need for clarification of what
is considered bisexual SEM. Hald and S
ˇtulhofer (2016) assessed
variations of bisexual behavior in SEM, including several (e.g.,
threesomes, orgy) that loaded onto a bisexual viewing factor for
heterosexual men. Given the presence of sexual identity dis-
crepancy in SEM viewing (as reported in the current study and
by Hald & S
ˇtulhofer, 2016), there are important questions that
warrantsubsequentinquiry.More specifically,arebisexualsex
scenes mostly embedded within heterosexual, lesbian, and/or
gay SEM or is there a distinct presence of this media type
beyond the gender and quantity of actors in a particular scene?
Catalog analysis of leading adult industry studios coupledwith
a behavioral content analysis of select videos will likely pro-
vide some answers to these questions. Nevertheless, viewers
Table 2 continued
Heterosexual
(a)
Gay
(b)
Bisexual
(c)
v
2
u
c
Post hoc
With condoms 3.3 4.3 8.5
Preferences for anal sex condom use in SEM (N=754) 10.66* 0.08
No preference 33.0 29.2 41.3 b\c
Without condoms 61.7 64.4 49.7 b[c
With condoms 5.3 6.4 9.1
Percentages presented. SEM (sexually explicit media)
*** p\.001; ** p\.01, *p\.05. Bonferroni corrections applied to post hoc comparisons (p\.017)
a
Missing data resulted in analytic samples ranging from 743 to 802.
b
Urethral sounding.
c
Golden showers, pissing/urinating.
d
Sucking or eating cum
out of someone’s anus. v
2
.u
c
(Cramer’s V)
Arch Sex Behav
123
may have a different perspective based on their SEM search
patterns and preferences that deserves further consideration.
This study provides important insights into the contexts of
SEM use. Not surprisingly, participants overwhelmingly repor-
ted viewing SEM at home either on a computer, on a tablet or
smartphone,or on atelevision. Nevertheless, a modestproportion
of men reported viewing SEM while attending sex parties or
commercial sex venues. Gay men were significantly more likely
than heterosexual and bisexual men to have viewed SEM at a sex
party or commercial sex venue. This is perhaps due to group dif-
ferences in frequency of attendance or the type of venue atten-
ded. Some research has also suggested that men who are less
open about their sexuality, particularly heterosexual- and
bisexual-identified men who engage in same-sex encounters,
avoid these types of venues for fear of discovery (Schrimshaw,
Downing, & Siegel, 2013a). Since multiple researchers have
established cross-sectional associations between viewing con-
domless anal sex in SEM and engaging in condomless anal sex
among GBMSM (Nelson et al., 2014b;Schrimshawetal.,
2016a; Stein et al., 2012), this finding does raise concerns about
the potential role of SEM in facilitating high-risk encounters in
sexually charged environments. Knowing that some men con-
sume SEM in these contexts may be critical to tailoring delivery
strategies of risk reduction messages. Additionally, study find-
ings provide further evidence that the workplace is a common
site for accessing SEM (Albright, 2008;Perrinetal.,2008),
particularlyon a tablet orsmartphone. Although thefrequency of
accessing SEM at work on a computer was low, heterosexual
men were significantly more likely than gay men to have done so
during the past 6 months. Further research in this area might
consider whether men who view SEM at work are more sexually
compulsive and whether viewing in this context has a negative
impact on productivity and interpersonalworkplace relationships.
As other researchers have reported (Duggan & McCreary,
2004; Peter & Valkenburg, 2011b), the current study found that
use of Internet SEM varied by sexual identity with heterosexual
men accessing it less frequently than gay and bisexual men.
Heterosexual men were also more likely to report viewing
sessions of 10 min or less. Study findings suggest that hetero-
sexual men are less likely to smoke, consume alcohol or other
drugswhile viewing Internet SEMcompared togay and bisexual
men. Indeed,nearly half ofgay (45.7 %)and bisexualmen (44.4 %)
indicated using substances at least some of the time in this
context. Moreover,bisexual menwere significantlymore likely
than heterosexual men to report that they did this some of the
time. Additional research could assess the substances men are
using while viewing SEM and what motivates their substance
use in this context. Furthermore, there was a high rate of mas-
turbation while viewing Internet SEM though no differences by
sexualidentity werefound. This findingis not surprisingas other
studies have reported similar rates of masturbation among men
while consuming SEM (Kraus & Rosenberg, 2014;Nelsonetal.,
2014b).
Despite growing attention to the potential negative implica-
tionsof bareback sex ingay maleSEM (e.g., Nelsonet al., 2014a;
Rosser et al., 2012;Schrimshawetal.,2016a), there has been a
lack of equivalent research pertaining to the use of condoms for
vaginal and anal sex in heterosexual and bisexual media. The
current study sought to bridge this gap in the literature by assessing
thetypes of sexualbehaviors that men(of diverse sexualidentities)
viewed in Internet SEM during the past 6 months, including con
domless vaginal and anal sex. Consistent with findings from
recent content analyses of gay male and heterosexual SEM
(Downing et al., 2014; Grudzen et al., 2009;Salmon&
Diamond,2012),participants overwhelmingly reportedviewing
Internet SEM that featured at least one of these risk behaviors.
Table 3 Multiple linear regressions predicting condom use preferences
in SEM
Condom Use
Preferences in
SEM
Anal
bSE
Viewing of anal sex without a condom -0.59*** 0.08
Viewing of anal sex with a condom 0.29*** 0.05
Gay or homosexual -0.07 0.07
Bisexual -0.03 0.08
Black or African-American 0.25*** 0.05
Hispanic or Latino 0.24** 0.08
Asian, Pacific Islander, Native American or Alaska
Native, Native Hawaiian, or Other
0.13 0.12
In a steady relationship -0.002 0.06
Married or domestic partnership -0.05 0.06
HIV-positive -0.13** 0.05
Never tested for HIV 0.01 0.08
Vaginal
bSE
Viewing of vaginal sex without a condom -0.53*** 0.07
Viewing of vaginal sex with a condom 0.37*** 0.06
Straight or heterosexual -0.14
0.08
Bisexual -0.02 0.07
Black or African-American 0.13
0.07
Hispanic or Latino 0.25* 0.11
Asian, Pacific Islander, Native American
or Alaska Native, Native Hawaiian, or Other
-0.13 0.13
In a steady relationship -0.01 0.08
Married or domestic partnership 0.02 0.07
HIV-positive -0.18* 0.08
Never tested for HIV 0.07 0.08
Unstandardized coefficients (b) and standard error (SE) are reported
*** p\.001; ** p\.01; * p\.05;
p\.10
Arch Sex Behav
123
Moreover, this study builds on research by Kraus and Rosenberg
(2016) who assessed attitudes toward condom use in SEM
among heterosexual and non-heterosexual men. The autho rsdi d
not specifically inquire about the types of behaviors that partic-
ipants viewed, thus precluding any analyses into whether their
attitudes predicted viewing. The current study, however, did assess
behavioral content viewed and observed significant associations
with preferences for condom use in SEM (also serving as a validity
check).
Previous research with GBMSM has shown significant asso-
ciations between viewing condomless anal sex in gay male SEM
andengaginginmorecondomless anal sex encounters (Nelson
et al., 2014b;Rosseretal.,2013;Schrimshawetal.,2016a; Stein
et al., 2012). The current study found that a substantial number of
heterosexual and bisexual men reported viewing condomless
vaginaland anal sexin SEM.Thus, it ispossible thatviewing such
high-riskbehaviors in SEMmay beassociated notonly withmore
condomless anal sex with male partners (among bisexual men),
but also with more condomless encounters with female partners
amongheterosexualand bisexual men. Furtherresearch isneeded
to examine these potential associations, particularly with regard
to female partners, as this is an understudied area. Likewise, we
alsofound that gaymen reportviewing condomless vaginalsex in
SEM. Additional research should examine whether this viewing
contributes at all to risky sexual encounters with male partners. If
any of these associations are confirmed in subsequent studies, it
would suggest that SEM-based risk reduction messaging (as an
HIV/STI prevention intervention) must not only target gay male
media but heterosexual and bisexual media as well.
Further research is also needed to better understand the
mechanisms underlying diverse SEM viewing patterns. For
example, some heterosexual-identified men may experience
sexual arousal from the homosociality or patterns of male
bonding (including BDSM) inherent to gay male SEM. For
gay-identified men who watch bisexual sex scenes, perhaps
their interest (gaze) lies not with the female actor(s), but with
the one or more male actors engaging in sexual activity.
Moreover, some men are perhaps aroused by the domination
(implied or otherwise) incorporated into bisexual and other
group sex scenes and may fantasize that they are the person
being dominated. Of course we recognize that viewing pat-
terns may change over time and are likely associated with
more than just sexual identity, including attractions to one or
more gender types, SEM content-related sexual arousal, and
prior sexual experiences. Also embedded in this discussion is
the idea that sexual identity is not always reflective of one’s
attractions or experiences (Baldwin et al., 2015). Indeed, the
current study found evidence of sexual identity discrepancy
in behavioral content viewed. This suggests, as we have noted
above, that SEM-based risk reduction messages have the
potential to reach a broad audience.
Limitations
Severalstudy limitations shouldbe noted.First,thedataarecross-
sectional in nature precluding any causal conclusions about
condom use preferences in SEM and behavioral content viewed
(i.e., does exposure influence viewing preferences, do prefer-
ences influence what viewers search for and watch, or is it
reciprocal and mutually reinforcing). Further, the study relied
on self-report retrospective data collected from an online non-
probability sample. Thus, there are potential concerns about
recall biasas well as participant selection and external validity.
To minimize issues with recall, the survey utilized a 6-month
timeframe to assess recent SEM use. Additionally, the survey
did not include items to assess the types of behavioral content
participants searched for in SEM, but ratherwhat they actually
viewed. As such, it remains unclear whether men intended to
watch those behaviors that they reported viewing. Nevertheless,
there was evidence of validity within the findings as preferences
for viewing condom use in SEM (a likely marker for content
searching)were significantly associatedwith behavioralcontent
viewed—specifically condom use or nonuse during scenes fea-
turing vaginal and anal sex—during the past 6 months. Lastly,
we noted several differences between participants who com-
pleted the survey and those who onlyprovided a partial survey.
Thus, the findings may not necessarily generalize to those
participants who did not complete the survey.
Conclusions
The results from this study have extended prior SEM research
bycomparing the frequency ofuse, viewing contexts,behavioral
content viewed, and viewer preferences for condom use during
vaginal and anal sex scenes by sexual identity among an ethni-
cally diverse sample of men in the U.S. Gay and bisexual men
reported significantly more frequent use of Internet SEM com-
pared to heterosexual men. Although most participants reported
viewing SEM at home on a computer, tablet, or smartphone,
significantly more gay men reported SEM use at a sex party or
commercial sex venue. Sexual identity predicted viewing of
high-risk (condomless anal and vaginal sex) and protective
behaviors (anal and vaginal sex with a condom). Nevertheless,
there was evidence of identity discrepant SEM viewing as
heterosexual-identified men reported viewing male same-sex
behavior and gay-identified men reported viewing heterosexual
behavior. Significant associations were also observed between
behavioral content viewed and preferences for condom use in
SEM. Findings suggest the importance of assessing SEM use
across media types (e.g., SEM that targets heterosexual, bisex-
ual, and gay audiences) and contexts and have implications for
future SEM research and prevention strategies to address con-
cerns about the potential influence of SEM on sexual behavior.
Arch Sex Behav
123
Compliance with Ethical Standards
Conflict of interest This research was supported by a grant from the
Foundation for the Scientific Study of Sexuality to Martin J. Downing,
Jr., Ph.D. (no award number provided). The authors declare that they
have no other conflicts of interest.
Human Participants All procedures performed in studies involving
human participants were in accordance with the ethical standards of the
institutional and/or national research committee and with the 1964
Helsinki Declaration and its later amendments or comparable ethical
standards.
Informed Consent Informed consent was obtained from all individual
participants included in the study.
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