Arch Sex Behav DOI 10.1007/s10508-014-0432-x

ORIGINAL PAPER

Use of the Internet to Meet Sexual Partners, Sexual Risk Behavior, and Mental Health in Transgender Adults Eric G. Benotsch • Rick S. Zimmerman • Laurie Cathers • Ted Heck Shawn McNulty • Juan Pierce • Paul B. Perrin • Daniel J. Snipes



Received: 4 November 2013 / Revised: 25 October 2014 / Accepted: 31 October 2014 Ó Springer Science+Business Media New York 2014

Abstract The purpose of this study was to examine the use of the internet to meet sexual partners among transgender individuals and examine correlatesof this use,including sexualrisk behavior, discrimination experiences, and mental health. A sample of 166 transgender adults (112 male-to-female transgender women and 54 female-to-male transgender men) were recruited in community venues and anonymously completed measures assessing these variables. Most participants (64.5 %) were HIV-negative, 25.2 % were HIV-positive, and 10.3 % did notknowtheirHIVstatus.Overall,33.7 %ofparticipantsreported having met a sexual partner over the internet, which did not differ significantly between transgender women and men. Among these individuals, transgender women reported significantly more

E. G. Benotsch (&)  P. B. Perrin  D. J. Snipes Department of Psychology, Virginia Commonwealth University, PO Box 842018, Richmond, VA 23284, USA e-mail: [email protected] E. G. Benotsch  L. Cathers Institute for Drug and Alcohol Studies, Virginia Commonwealth University, Richmond, VA, USA E. G. Benotsch  L. Cathers Institute for Women’s Health, Virginia Commonwealth University, Richmond, VA, USA R. S. Zimmerman College of Nursing, University of Missouri–St. Louis, St. Louis, MO, USA T. Heck Virginia Department of Health, Richmond, VA, USA S. McNulty Fan Free Clinic, Richmond, VA, USA J. Pierce Minority Health Consortium, Richmond, VA, USA

lifetime internet sexual partners (median = 3) than transgender men (median = 1). Use of the internet to meet sexual partners was associated with lower self-esteem but not with depression, anxiety, somatic distress or discrimination experiences. Among transgender women, use of the internet to meet sexual partners was associated with each of the 11 sexual risk behaviors examined, including having multiple partners, sex under the influence of drugs, number of unprotected anal or vaginal sex acts, and history of commercial sex work. The use of the internet to meet partners was not associated with sexual risk behavior among transgender men (0/11 variables assessed). Although the internet is a common mode of meeting sexual partners among some transgender adults, it may also be a potential venue for prevention interventions targeting transgender individuals at particularly high risk for HIV acquisition. Keywords Transgender  Internet  Sexual behavior  HIV  Commercial sex work

Introduction Transgender individuals are those who have gender identities, behaviors, or expressions different from their biological sex at birth (Feinberg, 1992). Transgender women are born males but with female identification or expression, and transgender men are born females with male identification or expression (Kockott & Fahrner, 1998). Transgender persons in the United States face a host of psychosocial problems, including high rates of discrimination, economic disenfranchisement, transgender-related violence, and lack of access to sensitive and appropriate health care (Bockting, Miner, Swinburne Romine, Hamilton, & Coleman, 2013; Bradford, Reisner, Honnold, & Xavier, 2013; De Santis, 2009; Dispenza, Watson, Chung, & Brack, 2012). Given these adverse experiences, rates of mental

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health problems, substance use, and suicide attempts are high in this population (Benotsch et al., 2013; De Santis, 2009; Haas et al., 2011; Testa et al., 2012). Transgender individuals are also disproportionately affected by HIV and other sexually-transmitted infections.Research has documented relatively high rates of HIV transmission risk behaviors (e.g., unprotected sex, multiple partners, commercial sex work) in both transgender men and transgender women (Chen, McFarland, Thompson, & Raymond, 2011; Herbst et al., 2008; Reisner, Perkovich, & Mimiaga, 2010; Rowniak, Chesla, Dawson Rose, & Holzemer, 2011). A recent review of the literature estimated the HIV prevalence of transgender women at almost 28 % (Herbst et al., 2008). Less is known about the HIV prevalence of transgender men, with a few small studies reporting prevalence rates ranging from 0 to 10 % (Herbst et al., 2008; Stephens, Bernstein, & Philip, 2011). Sexuality and the Internet The internet is increasingly used by adults in the United States to find romantic or sexual partners. More than one in ten of all Americans, and 38 % of individuals who are single and seeking a partner, report using the internet or mobile applications to find romantic or sexual partners (Smith & Duggan,2013).Members of sexual minority groups may be more likely to use the internet to seek partners relative to the general population (Rosenfeld & Thomas, 2012). For example, in a meta-analysis of 15 studies that recruited participants offline, 40 % of men who have sex with men (MSM) indicated they had used the internet to seek sexual partners (Liau, Millett, & Marks, 2006). Considerable prior research has documented that people who seek sexual partners over the internet show a pattern of substantially higher sexual risk behaviors. Meeting partners online is associated with more total sexual partners, more unprotected sex acts,and more sexually-transmitted infections. Most of this research has been conducted with MSM (e.g., Benotsch, Kalichman, & Cage, 2002; Dragowski, Halkitis, Moeller, & Siconolfi, 2013; Grov et al., 2007; Horvath, Bowen, & Williams, 2006; Ko et al., 2012; Lenward & Berrang-Ford, 2014; Liau, Millett, & Marks, 2006; Rosenbaum, Daunt, & Jiang, 2013; Rosser et al., 2009) with a smaller number of studies conducted with heterosexual adolescents and adults (e.g., Bolding,Davis,Hart,Sherr,&Elford,2006; Buhi etal.,2013;McFarlane, Bull, & Rietmeijer, 2002; Whiteley et al., 2012). Surprisinglylittleresearchhasexaminedtheuseoftheinternettofindsexual partners in transgender persons; however, a few studies have assessed small samples of transgender participants. Reisner et al. (2010) conducted a mixed-method study with a small sample (N = 17) of transgender men and the majority (62.5 %) reported meeting a sex partner online in the past 12 months. In a qualitative study of transgender men (N = 15), Sevelius (2009) noted that many participants used the internet to meet sexual

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partners, disclose their gender identity prior to meeting, and to negotiate sexual safety. Use of the Internet, Stigma, and Mental Health Some research has suggested that a motivation for using the internet to find sexual partners is the relative anonymity through which members of marginalized groupscan engage one another inasafecontext (Do¨ring,2009).Onlinecommunicationpermits more control over self-presentation and lower perceived risk of social rejection, relative to face-to-face communication (Albright, 2008; Caplan, 2007; Walther, 1996). The anonymous natureof internet interactionsmay alsoallow easier disclosure of personal details (e.g., transgender status), as well as an opportunity to get to know someone prior to a face-to-face meeting (Seal et al., 2014).Given thehigh rates of discrimination towards transgender adults (Bockting et al., 2013), the internet may be an appealing place for some members of this population to find partners. Some studies have found higher rates of psychological problems in individuals who use the internet to seek social interactions or meet romantic partners, including higher levels of social anxiety, depression, and loneliness, as well as lower self-esteem (Caplan, 2007; Kim, Kwon, & Lee, 2009; Klein, 2014; Morrison & Gore, 2010). Given that many transgender men and women face discrimination and consequently have relatively high rates of psychiatric symptoms, examination of mental health among transgender individuals who meet partners online is warranted. The Present Study The purpose of the present study was to examine the use of the internet to meet sexual partners and examine correlates of this use, including sexual risk behavior, discrimination experiences, and mental health symptoms. We hypothesized that transgender adults who used the internet to meet sexual partners would report more discrimination and mental health symptoms, lower selfesteem, and more sexual risk behaviors, compared to transgender adults who had not used the internet to meet sexual partners.

Method A brief survey was administered to transgender adults recruited from community venues in the mid-Atlantic region in 2011– 2012. Participants were recruited in person from transgender health clinics in Richmond, VA (48.3 %) and Washington DC (20.7 %), along with recruitment in bars (20.7 %), at a transgender community event (8.6 %), and commercial sex work areas (1.7 %). Overall, 88.7 % of individuals invited to participate agreed to do so. Participants completed the survey in a

Arch Sex Behav

private area within the community venue and were paid $10 cash for completing the study. All study procedures and materials were approved by the relevant institutional review boards. Participants A total of 174 individuals participated, but eight participants (4.6 %) did not respond to the questions assessing use of the internet to find sexual partners and thus were eliminated from the analyses. The166 participants includedin the analyseswere 112transgenderwomen(67.5 %)and54transgendermen(32.5 %). The mean age of participants was 31.8 years (SD = 11.5; range 18–65) and the average years of formal education was 12.8 years (SD = 2.2). The majority of the sample was African American (55.2 %),withthe remainderbeing White (32.5 %), Asian American (2.4 %), Latino/a (1.2 %), Native American (1.2 %), or other/ mixedracial orethnicheritage(7.5 %).Sixty-three percent of participants had annual incomes below $16,000, 23 % between $16,000 and $30,000, 8 % between $31,000 and $45,000, and 6 % above $45,000. Thirty percent of the sample reported beingunemployed.Mostparticipants(64.5 %)reportedtheywere HIV-negative, 25.2 % said they were HIV-positive, and 10.3 % did not know their HIV status. The majority of participants reported receiving hormone therapy in their lifetimes (83 %) and currently (74 %).

items included‘‘In the past year, did someone make fun of you because of your gender identity?’’ and ‘‘In the past year, were you physically assaulted or beaten up because of your gender identity?’’ Responses choices were yes/no. This measure was adapted from a prior measure developed for use with MSM (Bogart, Wagner, & Galvan, 2010) and was internally consistent in this sample (a = .70). Psychiatric Symptoms Participants completed the 18-item version of the Brief Symptom Inventory (Derogatis, 2001). The BSI-18 contains wellvalidated scales assessing symptoms of depression, anxiety, and somaticdistress.Allsubscaleshadadequateinternalconsistency in this sample (alphas ranging from .79 to .92). Norm information is available for this scale. Use of the Internet to Find Sexual Partners Consistent with prior research, participants were first asked if they had ever had sex with someone they first‘‘met’’over the internet (Benotsch et al., 2002; Dragowski et al., 2013; Ko et al., 2012). Participantswhoanswered‘‘yes’’wereaskedtoindicatehowmany sexual partners they had met over the internet in their lifetime. Sexual Practices

Measures

Participants completed a 6-item version of the Rosenberg SelfEsteem scale (Rosenberg, 1965). This is a well-validated instrumentthatshowsconsiderablestability,includinginsexualminority populations(Bauermeisteretal.,2010).Thismeasurehadadequate internal consistency in the present sample (a = .79).

Sexual behavior was assessed by asking participants to report the number of times they had engaged in anal and vaginal intercourse, as well as the number of times they had used or had not used condoms during intercourse in the past 3 months. Consistent with prior work, openresponseformats (i.e., participants were asked to report the number of acts rather than select a categorical response) were used for the sexual behavior measures to reduce response bias and to minimize measurement error. Participants also recorded the number of oral sex partners and vaginal or anal sex partners they had had in the past 3 months. In addition, participants indicated if they had ever exchanged sex for money, drugs, or a place to stay in their lifetime and in the past 3 months. Finally, participants indicated the number of times they had had sex in the past 3 months after having ‘‘too much’’ to drink and after using drugs. Measures similar to these have been found to be reliable in self-reported sexual behavior assessments and to yield aggregate indices of HIV risk comparable to those obtained by retrospective partner-by-partner sexual behavior assessments (Napper, Fisher, Reynolds, & Johnson,2010; Pinkerton,Benotsch,& Mikytuck, 2007; Shacham & Cottler, 2010).

Discrimination Experiences

Statistical Analyses

Participants answered six questions that assessed perceived discrimination due to gender identity in the past year. Example

All surveys were examined for inconsistencies and invalid responses. Missing data were omitted from analyses, resulting

Participants completed anonymous, self-administered surveys assessing demographic information, self-esteem, mental health, useoftheinternettofindsexualpartners,andsexualriskbehavior. Demographics Participants were asked their age, birth sex, current gender, race/ethnicity, education level, employment status, HIV status, and use of hormone therapy. Participants also indicated if they had experienced marginal housing in the past year (no permanent place to stay) or had been in jail in their lifetime. Self-Esteem

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in slightly different sample sizes for various statistical tests. Because distributions of sexual behavior were highly skewed, nonparametric analyses were used as recommended by Hollander and Wolfe (1999).

Table 1 Means, SDs, and multivariable logistic regression results examining associations between mental health, self-esteem, and discrimination, and use of the internet to meet sexual partners Individuals reporting use of the internet to find sexual partners (n = 56)

Results Overall, 33.7 % of participants (n = 56) reported having met a sexual partner over the internet. Among these individuals, the average number of partners they had met online was 7.5 (SD = 19.2,median = 2). Use oftheinternet to find a sexual partner did not differ significantly between transgender women (35.7 %) and transgender men (29.6 %), v2(1, N = 166)\1. However, among individuals who found partners online, transgender women reported significantly more lifetime internet partners (M = 9.9, SD = 22.5, median = 3) than transgender men (M = 1.8, SD = 1.3, median = 1), Mann–Whitney Z = 2.93, p\.01. Individuals who reported using the internet to find sexual partners did not differ from those who did not report this behavior in age, race, educational level, income, employment, housing status, history of incarceration, HIV status, or use of hormone therapy. UseoftheInternettoFindSexual PartnersandPsychosocial Factors Table 1 shows the means and SDs for the psychosocial variables and results of multivariable logistic regression analyses examining associations between psychosocial variables and use of the internet to meet sexual partners, adjusting for age, race, andtransgendergroup(menorwomen).Asseen inTable 1, participants who reported having met a partner online scored significantly lower on the self-esteem measure than participants who reported not meeting a partner online. Participants who reported having met a partner online did not differ from those who did not in depression, anxiety, somatic distress, or discrimination experiences. Overall, 25.9 % of participants scored in the clinical range on the BSI, but the percentages who scored in the clinical range did not differ between individuals who reported meetingapartneronline(27.3 %)andthosewhodidnot(25.2 %), v2(1, N = 162)\1. Use of the Internet to Find Sexual Partners and Sexual Risk Behavior As shown in Table 2, use of the internet to meet sexual partners was related to a variety of sexual risk behaviors, including having multiple partners, sex under the influence of drugs, and number of unprotected anal or vaginal sex acts for transgender women but not for transgender men. Transgender women who reported meeting sexual partners online were also more likely to report commercial sex work in their lifetime and recently.

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Variable a

AOR (95 % CI)

M (SD)

Individuals NOT reporting use of the internet to find sexual partners (n = 110) M (SD)

5.91 (6.39)

4.84 (6.32)

1.03 (0.97, 1.08)

a

BSI-anxiety

4.96 (5.52)

4.09 (5.40)

1.03 (0.97, 1.09)

BSI-somatic distressb

3.57 (4.39)

3.31 (4.67)

1.01 (0.94, 1.09)

Self-esteemc

17.52 (3.85)

19.02 (4.30)

0.92* (0.85, 0.99)

Discrimination experiencesd

2.12 (1.84)

1.98 (1.65)

1.04 (0.87, 1.26)

BSI-depression

Multivariable analyses adjust for age, race, and transgender group (transgender women or men) AOR adjusted odds ratio, CI confidence interval a

Range, 0–24

b

Range, 0–19

c

Range, 6–24

d

Range, 0–6

* p\.05

Because multiple factors can influence sexual behaviors, a sequential (hierarchical) logistic regression analysis was conducted to determine independent associations between using the internet to find sexual partners and risk after controlling for demographic variables and variables known to be associated with risk (e.g., use of substances in conjunction with sexual activity) (Martin, Benotsch, Cejka, & Luckman, 2014). This analysis was conducted with transgender women only because of the findings from the univariate analyses showing a relationship between use of the internet to meet partners and sexual risk behavior. The analysis predicted membership in one of two groups: those who reported multiple anal or vaginal sex partners in the past 3 months (n = 35) and those who did not report this behavior (n = 61). As shown in Table 3, demographic factors (age,race,history of commercial sex work) were entered on the first step and predicted having multiple sexual partners, relative to a constant onlymodel,v2(3,N = 96) = 10.20,p\.05.AsshowninTable 3, individuals with a history of commercial sex work were more likely to report multiple anal/vaginal sex partners in the past 3 months. Theuse ofsubstancesinconjunction withsexualactivity was entered on the second step and significantly improved the model, v2(2, N = 96) = 7.82, p\.05. As shown in Table 3, having sex after having ‘‘too much’’ to drink was associated with having multiple partners. The use of the internet to find

Arch Sex Behav Table 2 Use of the internet to find sexual partners and sexual risk behavior in transgender women and men Transgender women (N = 112)

Behavior

Individuals reporting use of the Internet to find sexual partners (n = 40) % reporting

Transgender men (N = 54) 2

Individuals NOT reporting v use of the Internet to find sexual partners (n = 72) % reporting

Individuals reporting use of the Internet to find sexual partners (n = 16) % reporting

Individuals NOT reporting v2 use of the Internet to find sexual partners (n = 38) % reporting

Multiple anal or vaginal 61.5 sex partners, past 3 months

26.5

12.78*** 25.0

11.8

1.34

Multiple oral partners, past 3 months

59.0

26.9

10.69**

25.0

14.3

\1

Any unprotected (no 56.4 condom used) anal or vaginal sex, past 3 months

33.8

5.18*

43.8

42.9

\1

Sex after having‘‘too much’’to drink, past 3 months

38.5

20.0

4.14*

31.3

36.1

\1

Sex after using drugs, past 3 months

36.8

14.1

6.89**

14.3

16.7

\1

0.0

6.26*

6.3

0.00

2.48

38.9

5.79*

6.3

7.9

\1

M (SD)

Za

M (SD)

M (SD)

Za

Total unprotected anal or 2.05 (2.80) vaginal sex acts, past 3 months

1.96 (6.68)

2.40*

5.88 (9.74)

1.29 (2.42)

0.90

Total number of anal or vaginal sex partners, past 3 months

2.13 (5.81)

3.36**

1.75 (2.32)

0.79 (1.01)

0.99

Sex after having‘‘too 1.90 (3.93) much’’to drink, number of times, past 3 months

1.08 (3.62)

2.03*

1.69 (3.63)

1.08 (2.22)

0.05

Sex after using drugs, 1.61 (2.93) number of times, past 3 months

1.28 (4.82)

2.49*

0.31 (0.87)

0.56 (1.81)

0.35

Exchanged sex for 7.7 money, drugs, or a place to stay, past 3 months Exchanged sex for 62.5 money, drugs, or a place to stay, lifetime M (SD)

a

7.31 (19.88)

Mann–Whitney test

* p\.05, ** p\.01, *** p\.001

sexual partners was entered on the final step and significantly increased the predictive utility of the model, v2(1, N = 96) = 6.72p\.05, indicatingthat use of the internet to find partners was associated with having multiple partners after controlling for demographic factors and substance use in conjunction with sexual activity.

Discussion As with other groups, our results showed that some transgender men and women used the internet to find sexual partners (Smith

& Duggan, 2013). The present findings with transgender women were consistent with prior research with MSM and heterosexual men and women documenting an association between using the internet to find sexual partners and sexual risk behavior (e.g., Benotsch et al., 2011; Buhi et al., 2013; Dragowski et al., 2013; Seal et al., 2014; Whitely et al., 2012). To our knowledge, this was the first study to examine this association in a moderate size sample of transgender adults. Transgender women who used the internet to meet partners reported higher rates of unprotected sex and were more likely to report multiple partners and to use substancesinconjunctionwithsexualactivity.Transgendermen andwomendidnotdifferintheirlikelihoodofreportingapartner

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Arch Sex Behav Table 3 Sequential logistic regression analysis predicting multiple anal or vaginal sex partners, past 3 months, transgender women Variable and step

OR

CI

1.

Age

0.98

(0.94, 1.02)

-.018

.020

ns

Racea

2.15

(0.59, 7.74)

.763

.654

ns

Lifetime commercial sex workb

2.78

(1.07, 7.24)

1.02

.488

\.05 \.05

2. 3. a b

B

SE

p

Sex after‘‘too much’’to drink, number of times, past 3 months

1.38

(1.02, 1.86)

.319

.154

Sex after using drugs, number of times, past 3 months

1.02

(0.92, 1.13)

.019

.053

ns

Internet use to meet sexual partners

3.69

(1.36, 10.06)

1.31

.511

\.05

Reference group = White Reference group = No reported lifetime CSW

firstmetonline,but,amongthosewhoreportedmeetingapartner online, transgender women reported more online partners than transgender men. A high proportion of the transgender women reported lifetime (47 %) or recent (25 %) commercial sex work (defined as trading sex for money, drugs, or a place to stay), and theuseoftheinternettomeet sexualpartnerswasassociatedwith this activity. Prior work suggests that the internet is increasingly used in commercial sex work (Cunningham & Kendall, 2011; Minichiello, Scott, & Callander, 2013) and it may be that some participants in this study had met commercial partners online. Previous research suggests that commercial sex work is a crucial factor for HIV acquisition among transgender women (Herbst et al., 2008), the group in the present sample most likely to report this activity. However, when commercial sex work was controlled for in the multivariable analysis, the association between meeting a sexual partneron the internet and sexual risk remained. For transgender men, our results did not show a significant association between use of the internet to find partners and risk behavior.AnexaminationofTable 2suggeststhat,insomeways, thetrendsweresimilartotransgenderwomen.Forexample,transgender men who met partners online reported more total partners and more unprotected anal or vaginal sex acts, but these were not statistically significant differences, possibly due to the limited power in this smaller sample (N = 54). In other ways, data from the transgender men in the study diverged from the data for transgender women. For example, for transgender men, there were no apparent trends between use of the internet to find partners and substance use in conjunction with sexual activity or engagement in commercial sex work. Discrimination, Self-Esteem, and Mental Health Symptoms The findings assessing associations between psychosocial variables and use of the internet to meet partners were mixed. Consistent with our hypotheses, individuals who reported meeting a partner online had lower self-esteem scores than those who did not report this behavior. However, there were only non-significant trends showing higher self-reported psychiatric symptoms and more discrimination experiences in participants that met

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partners online. The literature examining associations between using the internet to find partners and emotional distress is itself mixed, with some research supporting these associations and some not, suggesting that any relationships may not be especially robust. To our knowledge, prior studies have not investigated associations between internet use to meet partners and mental health in transgender adults. It may be that for this vulnerable population, the anonymity of the internet as well as the potential to benefit from online social support has benefits that buffer any relation between psychiatric symptoms and internet use (Do¨ring, 2009; Lee, Noh, & Koo, 2013; Mehra, Merkel, & Bishop, 2004). Future work should explore these associations in larger samples of transgender adults, as emotional distress and low self-esteem are factors implicated in HIV risk in this population (Brennan et al., 2012; Nuttbrock et al., 2013). Limitations and Conclusion The data for this study were collected from a convenience sample of transgender adults in community venues in the midAtlantic region; generalization to other regions and populations may not be warranted. The use of a cross-sectional study design limits drawing causal conclusions regarding the associations between internet use to meet sexual partners and risk behavior. In addition, the surveys relied on retrospective self-reports, potentially leading participants to over- or under-report risk behaviors. An additional limitation was that we asked about lifetime use of the internet to meet partners and the lifetime number of partners met. Research has suggested that sexual risk behavior is influenced by partner type and perceived partner characteristics (Newcomb, Ryan, Garofalo, & Mustanski, 2014). To provide a more fine-grained understanding of the use of the internet to meet partners in transgender men and women, future work should ask about more recent time frames and assess the specific behaviors that occurred with internet partners as well as the type of partners (e.g., casual, commercial) met online. In addition, prospective assessment of sexual risk behaviors may be more accurate than retrospective assessment (Gillmore, Leigh, Hope, &Morrison,2010).Amoredetailedassessmentofsexualbehavior through diary studies could provide more comprehensive

Arch Sex Behav

information about the relationship between internet use to find partners and sexual risk (Gillmore et al., 2010; Glick, Winer, & Golden, 2013). An additional limitation is that we did not assess if participants had undergone sexual reassignment surgery (SRS), as our community advisory board noted that SRS would be very rare in our relatively low-SES sample. Future work with broader samples of transgender adults should assess SRS, as it has an influence on sexual desire and activity (Wierckx et al., 2014). Finally, we asked participants if they had met partners online but did not ask about the type of website (e.g., dating site, chatroom).Futureresearchshouldinquireaboutwebsitetype,as that information may be useful for prevention efforts. Despite these limitations, this study provided additional information about patterns of internet use to meet sex partners in transgender men and women and was the first to document associations between internet use to find partners and HIV risk behavior in transgender women. The present study also reported initial evidence for the need to consider internet use when implementing interventions for this population. Transgender women are at elevated risk for HIV infection and the present findings suggest that the internet may be one venue associated with risk. It would also appear to be a potential venue for intervention with transgender individuals at particularly high risk for HIV acquisition. Internet-based HIV prevention programs have shown efficacy with other groups (Bowen, Williams, Daniel, & Clayton, 2008; Bull, Levine, Black, Schiege, & Santelli, 2012; Noar, Black, & Pierce, 2009; Ybarra et al., 2013) and are widely utilized by HIV prevention non-governmental organizations (Benotsch et al., 2006). Most of these efforts have focused on MSM or high-risk adolescents. Web-based resources exist for transgender individuals, but relatively few of the websitesdesignedforthispopulationtakeahealthorpreventionfocus (Horvath, Iantaffi, Grey, & Bockting, 2012). Online intervention programs are most likely to be successful when intervention components are tailored to a specific group, culturally appropriate, and show respect for the norms in the online venue (Allison et al., 2012; Noar et al., 2009). The internet may also have an important role in empowerment and providing social support, particularly for members of marginalized groups (Do¨ring, 2009; Lee et al., 2013; Mehra et al., 2004). Prior internet-based HIV interventions have utilized a variety of formats, including peer-to-peer networking, outreach, and video elements (Benotsch et al., 2006; Hirshfield et al., 2012; Schnall, Travers, Rojas, & Carballo-Die´guez, 2014). Online HIV prevention interventions have focused on a variety of target behaviors, including increased HIV testing (an important concern for the present sample—more than 1 in 10 indicated they did not know their HIV status), disclosure of HIV statustosexualpartners,andincreasedcondomuse(Schnalletal., 2014).Overall, findingsfrom thepresent study suggest theinternet could be an important tool for reaching high-risk transgender individuals.

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Use of the Internet to Meet Sexual Partners, Sexual Risk Behavior, and Mental Health in Transgender Adults.

The purpose of this study was to examine the use of the internet to meet sexual partners among transgender individuals and examine correlates of this ...
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