Arch Sex Behav (2015) 44:509–519 DOI 10.1007/s10508-014-0463-3

ORIGINAL PAPER

Meeting Sex Partners Through the Internet, Risky Sexual Behavior, and HIV Testing Among Sexually Transmitted Infections Clinic Patients Monique J. Brown • River Pugsley • Steven A. Cohen

Received: 16 August 2013 / Revised: 1 March 2014 / Accepted: 18 April 2014 / Published online: 8 January 2015  Springer Science+Business Media New York 2015

Abstract The Internet has now become a popular venue to meet sex partners. People who use the Internet to meet sex partners may be at a higher risk for contracting HIV and STIs. This study examined the association between meeting sex partners from the Internet, and HIV testing, STI history, and risky sexual behavior. Data were obtained from the Virginia Department of Health STD Surveillance Network. Logistic regression models were used to obtain crude and adjusted odds ratios, and 95 % confidence intervals for the associations between meeting sex partners through the Internet andevertestedforHIV,HIV testinginthepast 12 months, STI history, and risky sexual behavior. Logistic regression was also used to determine if gender and men who have sex with men interaction terms significantly improved the model. Women who met a sex partner from the Internet were more likely to have had an HIV test in the past 12 months than women who did not meet a partner in this way. On the other hand, men who met a sex partner through the Internet were more likely to have ever had an HIV test than other men, but this was only seen for heterosexual men. All populations who met a sex partner from the Internet were more likely to take part in risky sexual behavior. HIV prevention strategies should emphasize annual testing for all populations.

M. J. Brown (&)
R. Pugsley
S. A. Cohen Department of Family Medicine and Population Health, Virginia Commonwealth University School of Medicine, 830 East Main St., 8th Floor, Richmond, VA 23219, USA e-mail: [email protected] R. Pugsley Office of Epidemiology, Division of Disease Prevention, Virginia Department of Health, Richmond, VA, USA

Keywords Internet
HIV testing
STI
Risky behavior
Surveillance

Introduction TheInternethasnowbecomeapopularvenuetomeetsexpartners (Whiteley et al., 2012). Its growing popularity can be attributed to its increasing ease of access, relative inexpensiveness, anonymity and acceptability (Cooper, 1998; King, 1999). Studies have reported varying prevalence estimates of Internet use to find sex partners. Among a sample of HIV-infected patients seeking medical care in a San Francisco county hospital and universitybased clinic, 29 % reported using the Internet to find sex partners (Clark, Marquez, Hare, John, & Klausner, 2012). Among clients at a public health HIV counseling and testing site, 16 % reported seeking sex partners on the Internet (McFarlane, Bull, & Rietmeijer, 2000). Among men who have sex with men (MSM) diagnosed with syphilis, 18, 22 and 26 % reported using the Internet to meet sex partners in 2001, 2002, and 2003 respectively (Taylor et al., 2004). In one of the few studies examining using the Internet to seek sex partners in both heterosexual and gay populations, among heterosexual men and women, one in 20 women and one in 10 men had used the Internet to look for sexual partners in the previous 12 months compared to nearly half of gay men (Bolding, Davis, Hart, Sherr,& Elford, 2006). Amonga sample of homeless youth in Los Angeles, California, participants who reported having sex with an online partner may be at a higher risk for contracting HIV and STIs compared to those who did not have sex with an online partner (Young & Rice, 2011). This difference in risk is possibly due to a greater frequency of risky sexual behavior between populations having sex with partners met online and those who do not. For example, participants who reported having sex with an online partner were more likely to exchange sex for money, drugs, accommodation, or food

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compared to participants who did not report having sex with an online partner (Young & Rice, 2011). Internet Use and Sexual Risk Behavior Previous studies have shown that individuals who use the Internet to seek sex partners were more likely to report unprotected sex (Benotsch, Kalichman, & Cage, 2002; Clark et al., 2012; Garofalo, Herrick, Mustanski, & Donenberg, 2007; Liau, Millett, & Marks, 2006), higher rates of drug use in the past 12 months (Benotsch et al., 2002; Clark et al., 2012), more sexual partners (Benotsch et al., 2002; Horvath, Rosser, & Remafedi, 2008; Mustanski, 2007; Ogilvie et al., 2008), and failure to discuss sexual histories (Mustanski, 2007) compared to individuals who do not use the Internet to seek sex partners. Meeting sex partners online has also been found to be associated with HIV/STI risk behavior among African American adolescents (Whiteley et al., 2012). Among gay and bisexual men recruited from the New York City men-seeking-men section of Craigslist.org, those who were HIV negative reported that the highest rates of unprotected sex were with men they met online (Grov, Agyemang, Ventuneac, & Breslow, 2013). One in four men stated that they did not discuss HIV status with partners whom they had met online as they were not comfortable with the topic (Grov et al., 2013). Among heterosexual and gay populations attending a LondonHIV testing clinic, rates of high-risk sexual behavior were higher among those who used the Internet to find sex partners compared to those who did not (Bolding et al., 2006). Nevertheless, the relationship between Internet use to find sexual partners and risky sexual behavior is more complex. For example, although having an online partner was associated with unprotected sex in the past year among a sample of MSM from New York City recruited offline, no significant association remained after controlling for multiple partnerships (Jenness et al., 2010). Slightly higher levels of other risky behaviors were found within offline partnerships. Partners who met offline were more likely to engage in substance abuse with the participant and be HIV-serodiscordant. These findings suggest that meeting partners online may not be an independent predictor of behavioral risks but could be a marker for risks occurring independent of using the Internet (Jenness et al., 2010). However, among MSM who were recruited through a variety of Internet sites, Mustanski (2007) found that unprotected sexual intercoursewas less likely to occurwithpartnerswhometonlinecomparedtopartnerswhomet by other means. One possible reason for this finding was that lack of trust and familiarity with online partners could have served as motivating factors for condom use (Grov et al., 2013). Sexual encounters with an Internet partner were not associated with increased risk of chlamydia or gonorrhea infection among an STI clinic population in Denver, Colorado (Al-Tayyib, McFarlane, Kachur, & Rietmeijer, 2009). It is possible that the association seen between Internet use to seek sexual partners and risky sexual behaviors is not due to Internet-seeking resulting in these

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behaviors, but that individuals who practice risky sexual behaviors use the Internet to seek sex partners. Among MSM, data have suggested that it is the men who engage in high-risk sex with other men who use the Internet, and not that meeting partners online predicts high-risk sex (Mustanski, 2007). Similarly, Bolding et al. (2006) found that heterosexual men and women who were highrisk tended to use the Internet to engage in sexual risky behavior more so than the use of the Internet leading to high-risk behavior. Other factors such as sensation-seeking or compulsive sexual behavior may be associated with using the Internet to seek sex partners and sexual risk behavior. Among African American adolescents, sexual sensation seeking was associated with meeting sex partners online (Whiteley et al., 2012). Sexual sensation seeking was also associated with unprotected sex among middleeastern MSM who used the Internet to seek sex (Matarelli, 2013) andamongadolescentsreceivingsubstanceusetreatmentservices at two outpatient facilities in South Florida (Oshri et al., 2013). Among HIV-positive outpatients recruited from two participating hospitals in upstate New York and New Jersey, impulsivity was associated with an increased number of sexual partners (Wulfert, Safren, Brown, & Wan, 1999). More specifically, sexual impulsivity defined as ‘‘having trouble being safe when you’re really turned on’’, was associated with unprotected sexual intercourse among a multistage probability sample of gay and bisexual men in San Francisco (Hays et al., 1997). Coleman et al. (2010) showed that compulsive sexual behavior was associated with unprotected sex among MSM who used the Internet to seek sexual partners, whether partners met on the Internet or offline. HIV/STI Testing Onlyasmallbodyofevidencehasexaminedtheassociationbetween using the Internet to seek sex partners and HIV/STI testing. For example, homeless youth who do not use online social networks were less likely to have had STI testing compared to those who did (Young & Rice, 2011), which can also be due to the lack of trust and familiarity with online partners (Grov et al., 2013). However, among Australian MSM, compared to men who tested for HIV over 12 months ago, untested men tended to be younger, less educated, less likely to have unprotected sexual intercourse, more likely to expect HIV negative disclosure and spent more time using social networking websites. Nevertheless, compared to men who tested for HIV over 12 months ago, men who tested for HIV in the prior year where younger and more likely to expect HIV negative disclosure (Holt et al., 2012). Confounders PotentialconfoundersoftheassociationbetweenusingtheInternet to seek sexual partners and HIV testing and STI history may include race/ethnicity (McFarlane, Kachur, Bull, & Rietmeijer, 2004), age (McFarlane et al., 2004), employment status, education, number of sex partners (McFarlane et al., 2004), sexual

Arch Sex Behav (2015) 44:509–519

orientation (Bolding et al., 2006), having one-time sex partners (Mustanski,2007),givingand/orreceivingdrugsormoneyforsex, and condom use (Elford, Bolding, & Sherr, 2001; McFarlane et al., 2004; Mustanski, 2007). One study found that heterosexual women and men who looked for sex online were less likely to be employed compared to those who did not define themselves as heterosexual (Bolding et al., 2006). Women who have reported having sex with someone they first met on the Internet were more likely to be older, White, have had a higher number of sexual partners, frequently use condoms, and have been tested for STIs, compared to women who never had a sex partner who they first met online (McFarlane et al., 2004). Heterosexual men and women have been found to be less likely to have looked for a sexualpartnerthroughtheInternetcomparedtogaymen(Bolding et al., 2006). Seeking sex on the Internet was associated with recent STIs and high-risk sexual behavior among HIV positive and negative MSM populations (Elford et al., 2001). Retrospective data have also showed that a history of seeking sex partners online was associated with a greater number of sexual partners in the past 12 months, one-time sex partners and having sex without condoms (Mustanski, 2007). Aim of the Present Study The use of the Internet to seek sex partners and risk for HIV transmission is not well understood (Davis, Hart, Bolding, Sherr, & Elford, 2006). Additionally, studies examining associations between using the Internet to meet sex partners and risky behavior among non-MSM populations are scant. The majority of studies examining the association between use of the Internet to seek sex partners and risky sexual behavior focus on MSM due to their initial greater use of online social networks (Whiteley et al., 2012). Nevertheless, there has been a substantial increase in access to technology (Whiteley et al., 2012) to all populations locally, nationally, and globally, and more people are continually using the Internet for dating and as a resource to obtain sexual partners. Women also use the Internet to seek sex partners (McFarlane et al., 2004), and their behaviorsshouldalsobestudied.Researchhasshownthat useofthe Internet is associated with risky sexual behavior (Benotsch et al., 2002; Clark et al., 2012; Garofalo et al., 2007; Horvath et al., 2008; Liauetal.,2006;Mustanski,2007;Ogilvieetal.,2008),possiblydue to high-risk individuals, who have had multiple sex partners and unprotected sex, using the Internet to meet sexual partners (White, Mimiaga, Reisner, & Mayer, 2013). However, there is a lack of research on whether use of the Internet to seek sex partners may influence HIV testing. It is important to examine the association betweenuseoftheInternettoseeksexpartnersandHIVtesting,STI history and risky behavior among MSM and other populations controlling for potential confounders. We will be able to determine if populations who seek sex partners via the Internet should be targeted for HIV screening and prevention strategies. Toourknowledge,nostudyhasexaminedtheassociationbetween meeting sex partnersfrom theInternet andHIV testingamong anSTI

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clinic population. There is also a dearth of literature examining the relationship between using the Internet to seek sex partners, and HIV testing, STI history and risky sexual behavior among non-MSM populations. This study examines the association between meeting sex partners from the Internet, HIV testing, STI history, and risky sexual behavior among men and among women, and helps to determine which populations should be targeted for HIV and STI screening.

Method Participants Datawereobtainedfrom theVirginiaDepartment ofHealth (VDH) STD Surveillance Network (SSuN) Clinic database. The Centers for Disease Control and Prevention (CDC) established SSuN, which is a sentinel surveillance system comprising local enhanced STI surveillance systems that follow common protocols at 12 sites in geographically disparate areas across the U.S. (Centers for Disease Control and Prevention, 2012). The main purpose of this system is to improve the capacity of STI programs in detecting, monitoring, and responding to trends in STIs (Rietmeijer et al., 2009). SSuN has twomain components: STIclinic surveillance and Neisseria gonorrhoeae (NG) population surveillance (Virginia Department of Health, Office of Epidemiology Division of Disease Prevention,2011).TheSTIclinicsurveillance,onwhichthestudyis based, involves collecting data on patients attending public STI clinics in the Richmond metro area in Virginia (the city of Richmond and the surrounding counties of Henrico and Chesterfield). From January 2009 to September 2012, the period on which the current study is based, three STI clinics in Richmond City, Henrico County and Chesterfield County participated in the VDH STD SSuN Clinic data collection. The majority of STI clinic patients were non-Hispanic Black (78 %), and were between 20 and 34 years old (32 % age 20–24 and 41 % age 25–34). Thirty-five percent of patients were unemployed at the time of their visit, 15 % had less than a high school education and 27 % were full-time or part-time students (Virginia Department of Health, Office of Epidemiology Division of Disease Prevention, 2011). Questionnaires were completed for 74.2 % of patients who visited the clinic from January 2009 to September 2012. Participants were eligible for this study if they were age 18 or older at the time of their visit. The resultant sample size was 35,957 patients. Procedure The SSuN questionnaire was distributed to each patient by clinical staff during the normal patient registration process at each participating STI clinic (i.e., during check-in). All questionnaires were paper-based, and patients filled out the forms on their own while waiting to be seen by a clinician. The data collected by the

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questionnaires included information on patient demographics and high-risk behaviors. Patients were asked to complete the questionnaire, but completion of the questionnaire was not mandatory to receive service. The questionnaires were not anonymous, but were confidential patient medical and risk histories, which were used by clinicians during the patient’s visit. One copy was kept in each patient’s medical file, while the second copy was sent to the central VDH office for data entry and analysis. Patient interview data were also integrated with information on STI diagnoses and treatment from other STI and HIV/AIDS surveillance data systems at the central office. More detailed information onSSuNprotocolsisavailableelsewhere(VirginiaDepartmentof Health, Office of Epidemiology Division of Disease Prevention, 2011). The Virginia Commonwealth University Institutional Review Board deemed the current study exempt as de-identified, secondary data were used. Measures Operational Definition of Internet Use to Seek Sex Partners Internet use to seek sex partners was defined as answering yes to the question‘‘Have you met sex partners through the Internet in the past 12 months?’’which elicited a binary response (yes vs. no). Operational Definitions of HIV Testing and STI History Lifetime HIV testing was defined as answering yes to the question‘‘Have you ever been tested forHIV?’’which elicited a binary response (yes vs. no). The CDC recommends, for patients in all health-care settings, that persons at high risk for HIV infection should be screened for HIV at least annually (Branson et al., 2006). HIV testing in the past 12 months was determined by using the question ‘‘When were you last tested for HIV’’ and among those who gave a month and year of last test date, we determined if the month of being tested for HIV was within the 12 months prior to their clinic visit date. We also included those participants who were tested for HIV at their current visit?’’We excluded participants for whom the date of last HIV test was unknown. STI history, which was self-reported, was defined as answering yes to ‘‘Have you ever been diagnosed with gonorrhea?’’ or ‘‘Have you ever been diagnosed with chlamydia?’’ or ‘‘Have you ever been diagnosed with syphilis?’’ Potential Confounders Confounders of the association between use of the Internet to find sex partners and HIV testing that were considered included: race/ ethnicity (McFarlane et al., 2004), age (McFarlane et al., 2004), employment status, education, number of sex partners (McFarlane et al., 2004), sexual orientation (Bolding et al., 2006), having one-time sex partners (Mustanski, 2007), giving and/or receiving drugs or money for sex, and condom use (Elford et al., 2001;

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McFarlane et al., 2004; Mustanski, 2007). Sexual orientation was determined by the question ‘‘Do you consider yourself gay (homosexual),straight(heterosexual),orbisexual?’’Confounders of the association between use of the Internet to find sex partners and STI history included the other aforementioned confounders. Moderators Basedonpreviousresearch,wetestedforaninteractionwithmeeting sex partners from the Internet and gender, sexual orientation, anonymous sex partners in the past 12 months and commercial sex in the past 12 months for the HIV testing and the STI history models. As previously stated, heterosexual men and women have been found to belesslikelycomparedtogaymentohavelookedforasexualpartner through the Internet (Bolding et al., 2006). Among populations with history of an STI, rates of anonymous sex in the past 12 months and commercial sex in the past 12 months varied depending on population(women,MSM,andmenwhohavesexwithwomen)(Newman et al., 2012). Interaction was determined by the significance of the p value and the magnitude of the estimate of the interaction terms. Statistical Analysis Contingencytablesanddescriptivestatisticswereusedtodetermine the distribution of socidemographic and sexual history characteristics among the total sample population, among participants who reported having had a sexual partner from the Internet in the past 12 months compared to those who did not, and among participants who reported ever having an HIV test compared to those who did not. p values were used to determine statistically significant differences. All p values were based on v2 statistics or scores from the Wilcoxon Rank Sum or Kruskal–Wallis test, where appropriate. Potential confounders considered were either associated with meeting sex partners from the Internet, and HIV testing or STI history. A variable was considered to be a potential confounder based on the literature review done a priori. Each potential confounder was placed in each model with having a sex partner from the Internet in the past 12 months and HIV testing and STI history as separate outcomes. The confounder that changed the effect of meeting sex partners from the Internet in the past 12 months the most was then retained for the next iteration. Variables were considered confounders if the odds ratios had a 10 % change or more. All potential confounders were determined to confound the associations. Multivariable logistic regression models were used to obtain adjusted odds ratios and 95 % confidence intervals for the associations between using the Internet to seek sex partners and ever tested for HIV, HIV testing in the past 12 months, STI history, number of sex partners in the past 3 months, anonymous sex partners, commercial sex, and condom use at last sex. Results were stratified by gender and MSM status based on literature review a priori and testing for interaction. MSM status was defined by identifying as male, and gay or bisexual or

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reporting having sex with males in the past 3 months vs. identifying as male and heterosexual. The log likelihood ratio test was used to determine if interaction terms significantly improved the model. Robustness analyses were performed to exclude participants whose test date within the past 12 months was at the time of their clinic visit. We excluded these participants to determine if those participants who had an HIV test during the past 12 months at another time other than the current visit at these clinics would show different results for the association between using the Internet to seek sexual partners, HIV testing, and STI history. SAS version 9.3 (SAS Institute, Cary, NC) was used for all statistical analyses.

513 Table 1 Descriptive characteristics of VDH SSuN sample population, January 2009 to September 2012 Characteristics*

% (N) N = 35,957

Sex Female

52.8 (18,973)

Male

47.2 (16,944)

Race Black, non-Hispanic Hispanic White, non-Hispanic Other, non-Hispanic

77.5 (24,102) 8.2 (2,548) 12.8 (3,975) 1.5 (478)

Age

Results In the total sample, the majority were women (52.8 %), Black (77.5 %) and unemployed (55.1 %) (Table 1). One in eight participants was identified to be MSM. Approximately 8 in 10 participants reported ever being tested for HIV and 63.7 % reported having had an HIV test in the past 12 months. Approximately 7 % reported meeting sex partners through the Internet. Forty-four percent of all participants reported having had a history of STIs (chlamydia, gonorrhea, or syphilis) and the majority of participants (62.6 %) reported no condom use during last sex. Table 2 shows the distribution of sociodemographic and sexual history characteristics among participants who reported meeting sex partners through the Internet in the past 12 months vs. not and among participants who reported ever having an HIV test vs. not. A higher percent of men reported meeting sexual partners through the Internet compared to women (11.4 % vs. 3.4 %). Of participantswhowereemployed,7.6 %reportedmeetingsexualpartners through the Internet in the past 12 months compared to 6.8 % of participants who were unemployed. Approximately one in five participants who reported having three or more sex partners in the past 3 months reported meeting sex partners through the Internet compared to 2.8 % of participants who reported one sex partner in the past 3 months. Thirty-eight percent of participants who selfidentified as gay and 42.2 % who were classified as MSM reported meeting sex partners using the Internet. There were no statistically significant differences in STI history among participants who reported meeting sex partners through the Internet and those who did not. However, statistically significant differences were found in reporting anonymous sex partners, exchanging sex for drugs or money, and condom use among participants who reported meeting sex partners through the Internet and those who did not. Seventeen percent of participants who reported having anonymous sex partners, 24.3 % who reported exchanging drugs or money for sex, and 8.4 % of participants who reported condom use reported meeting sex partners through the Internet. Table 3 shows the association between reporting meeting a sex partner through the Internet in the past 12 months and ever being tested for HIV, HIV testing in the past 12 months, STI history, and

18–24

28.2 (10,135)

25–34

43.8 (15,758)

35–44

15.0 (5,391)

45–54

9.1 (3,284)

55?

3.9 (1,389)

Employment Employed

44.9 (11,227)

Unemployed

55.1 (13,763)

Education \HS

14.6 (3,801)

HS

39.4 (10,226)

[HS

45.9 (11,932)

Number of sex partnersa 0

5.2 (1,293)

1

53.2 (13,279)

2

26.0 (6,496)

C3

15.7 (3,917)

Sexual orientation Heterosexual

89.4 (22,385)

Gay

4.8 (1,198)

Bisexual

5.9 (1,464)

MSM status MSM

12.5 (1,455)

Heterosexual men

87.5 (10,225)

Ever tested for HIV Yes

81.2 (21,041)

No

18.8 (4,879)

HIV testing in the past 12 months Yes No

63.7 (22,911) 36.3 (13,046)

Meeting sex partners through Internet Yes

7.2 (1,243)

No

92.8 (16.031)

STI history Yes

44.1 (10,418)

No

55.9 (13,195)

Anonymous sex partners Yes

13.0 (2,205)

No

87.0 (14,811)

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Table 1 continued Characteristics*

% (N) N = 35,957

The log likelihood ratio test showed that addition of the gender interaction and MSM interaction improved the model (p = .0284 and\.0001, respectively) (data not shown).

Commercial sex Yes

1.8 (312) 98.2 (16,662)

Discussion

Yes

37.4 (9,370)

No

62.6 (15,688)

Although many studies have examined meeting sex partners through the Internet among the MSM population (Benotsch et al., 2002; Davis et al., 2006; Elford et al., 2001; Garofalo et al., 2007; Grov et al., 2013; Holt et al., 2012; Horvath et al., 2008; Jenness et al., 2010; Klein, 2011; Liau et al., 2006; Ogilvie et al., 2008; Stall et al., 2003), few studies have examined the association between this exposure and STI history, especially among nonMSM populations (Bolding et al., 2006; Whiteley et al., 2012). To our knowledge, no study has examined the association between meeting sex partners through the Internet and HIV testing among women. Among this STI clinic population, approximately 7 % reported using the Internet to seek sex partners. This prevalence estimate is substantially lower when compared to other studies reporting estimates of 16–30 % (Clark et al., 2012; McFarlane et al., 2000; Taylor et al., 2004) The difference in estimates could be due to the difference in study populations. The current study is based on the STI clinic population in the Richmond metro area in Virginia while the referenced studies were based on an HIV counseling and testing site in Denver, Colorado (16 %), a San Francisco county hospital and university based clinic (29 %), and among syphilis cases reported to the Department of Health in Los Angeles County (30 %). Using data from surveillance compared to research activities tend to show varying proportions of prevalence estimates (Newman et al., 2012). Wefoundthat compared towomenwho didnotreport meeting asexpartnerfromtheInternet,womenwhometasexpartnerfrom the Internet were more likely to have had an HIV test in the past 12 months. This association was not found in men. Women may be more vigilant about sexual health screening (Brown, Weitzen, & Lapane, 2013) as a result of yearly checkups compared to men. Women who reported meeting sex partners through the Internet were more likely to report multiple sex partners in the past 3 months and having anonymous sex partners. Women who have had sex partners from the Internet might be more vigilant about annual HIV testing compared to women who do not have sex partners from the Internet due to awareness of their risky behaviors. Women who meet sex partners from the Internet may engage in more risky sexual behaviors, but may also engage in more protective behavior more frequently than women who have no sex partners from the Internet (McFarlane et al., 2004). Men who reported meeting a sex partner through the Internet were more likely to have ever had an HIV test compared to men who did not. However, this association was only seen only for heterosexual men and not for MSM. Men who reported seeking sex partners from the Internet may be more vigilant about ever getting an HIV test, but not about

No Condom useb

* Comparisons of distributions in each category are statistically significant using v2 tests for equal proportions (p\.0001) a

Number of sex partners in the past 3 months

b

Condom use during last sex

risky sexual behavior. Overall crude results show that those who reported meeting a sex partner from the Internet in the past 12 months were 50 % morelikely to report everhavingan HIV test and 23 % more likely to report having an HIV test in the past 12 months. However, adjusting for gender, race, age, employment, education, number of sex partners in the past 3 months, sexual orientation, STI history, anonymous sex partners, commercial sex and condom use at last sex attenuated the relationship sothattheconfidenceintervalsincludedunity.Amongwomenand men, those who met sex partners through the Internet were 80 % more likely to have had an HIV test in the past 12 months and 40 % more likely to ever have had an HIV test, respectively. Robustness analyses, excluding participants whose test date within the past 12 months was at the time of their clinic visit, showed no statistically significant results. Meeting sex partners through the Internet was associated with reporting three or more partners in the past 3 months (women: adjusted OR: 9.61; 95 % CI 2.85–32.4; men: adjusted OR: 5.31; 95 % CI 3.21–8.78), reporting having anonymous sex partners (women: adjusted OR: 2.96; 95 % CI 2.06– 4.25;men: adjusted OR: 3.25; 95 % CI2.64–3.99)andexchanging sex for drugs and/or money among men (adjusted OR: 2.42; 95 % CI 1.34–4.35). Table 4 shows the association between reporting meeting a sex partner through the Internet, and HIV testing, STI history and risky sexual behavior by MSM status. For heterosexual men, those who reported meeting a sex partner from the Internet in the past 12 months were 55 % more likely to report ever having an HIV test. Robustness analyses, excluding participants whose test date within the past 12 months was at the time of their clinic visit, showed no statistically significant results. Meeting sex partners through the Internet was associated with having three or more sex partners in the past 3 months (heterosexual men: adjusted OR: 4.83; 95 % CI 2.24–10.4; MSM: adjusted OR: 4.73; 95 % CI 2.49–8.99), and having anonymous sex partners (heterosexual men: adjustedOR: 3.25; 95 % CI2.52–4.20; MSM: adjustedOR: 3.16; 95 % CI 2.21–4.53). Meeting sex partners from the Internet was also associated with exchanging sex for drugs and/or money among heterosexual men (adjusted OR: 2.46; 95 % CI 1.29– 4.70) but not among MSM.

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515

Table 2 Distribution of sociodemographic and sexual history characteristics among participants who reported meeting sex partners through the internet in the past 12 months versus not and among participants reported ever having an HIV test versus not Met sex partner from the Internet in past 12 months % (N)

Did not have sex partner from the Internet in the past 12 months % (N)

p*

Ever had a HIV test % (N)

Have not had an HIV test % (N)

p*

11.4 (931)

88.6 (7,208)

\.0001

77.3 (9,228)

22.7 (2,714)

\.0001

3.4 (308)

96.6 (8,802)

84.5 (11,779)

15.5 (2,162)

Gender Male Female Race \.0001

Black, non-Hispanic

6.5 (861)

93.5 (12,410)

83.6 (17,016)

16.4 (3,355)

Hispanic

6.3 (78)

93.7 (1,156)

72.0 (1,308)

28.1 (510)

White, non-Hispanic

11.6 (281)

88.4 (2,142)

72.7 (2,415)

27.3 (907)

Other, non-Hispanic

6.7 (23)

93.2 (319)

70.4 (293)

29.6 (123)

\.0001

Age \.0001

18–24

5.7 (322)

94.3 (5,311)

25–34

8.0 (604)

92.0 (6,920)

30.6 (2,314)

69.4 (5,255)

15.1 (1,769)

84.9 (9,983)

35–44

7.7 (186)

92.3 (2,227)

9.4 (353)

90.6 (3,395)

45–54

8.5 (107)

91.5 (1,147)

14.1 (300)

85.9 (1,825)

55?

5.3 (24)

94.7 (426)

19.7 (143)

80.3 (583)

Employed

7.6 (695)

92.4 (8,397)

Unemployed

6.8 (485)

93.2 (6,692)

\.0001

Employment .0304

81.2 (10,930)

18.8 (2,532)

82.3 (8,986)

17.7 (1,929)

.0226

Education \HS

6.0 (135)

94.0 (2,112)

73.2 (2,657)

26.8 (974)

HS

5.3 (343)

94.7 (6,114)

\.0001

79.6 (7,906)

20.4 (2,031)

[HS

9.0 (746)

91.0 (7,506)

85.6 (10,052)

14.4 (1,687)

\.0001

Number of sex partnersa \.0001

0

5.4 (44)

94.7 (777)

76.3 (947)

23.7 (294)

1

2.8 (252)

97.2 (8,820)

81.4 (10,562)

18.6 (2,417)

7.9 (342)

92.1 (3,979)

82.1 (5,241)

17.9 (1,140)

21.3 (565)

78.7 (2,089)

82.3 (3,153)

17.7 (677) 19.2 (4,200)

2 C3

\.0001

Sexual orientation Heterosexual

95.3 (14,235)

80.8 (17,688)

Gay

38.1 (351)

4.7 (696)

61.9 (570)

90.5 (1,070)

9.5 (112)

Bisexual

16.9 (183)

83.1 (899)

86.2 (1,251)

13.8 (201)

42.2 (469)

57.8 (643)

89.8 (1,280)

10.2 (146)

75.5 (7,507)

24.5 (2,441)

\.0001

\.0001

MSM status MSM Heterosexual men

\.0001

6.6 (458)

93.5 (6,537)

Yes

6.6 (537)

93.4 (7,636)

No

7.3 (604)

92.7 (7,647)

.0588

Yes

17.3 (377)

82.7 (1,801)

\.0001

No

4.0 (589)

96.0 (14,163)

\.0001

STI history 92.1 (9,423)

7.9 (812)

73.9 (9,564)

26.1 (3,385)

\.0001

Anonymous sex partners 83.1 (1,791)

16.9 (365)

82.3 (11,940)

17.7 (2,565)

88.7 (267)

11.3 (34)

82.3 (13,440)

17.7 (2,888)

82.4 (7,569)

17.6 (1,618)

80.8 (12,393)

19.2 (2,940)

.3908

Commercial sex Yes

24.3 (58)

No

75.7 (181)

5.5 (913)

94.5 (15,587)

Yes

8.4 (573)

91.6 (6,223)

No

6.2 (631)

93.8 (9,486)

\.0001

.0039

Condom useb \.0001

.0023

2

* All p values are based on v statistics except for age and number of sexual partners in the past 3 months, which were based on Wilcoxon scores/Kruskal–Wallis test a

Number of sex partners in 3 months

b

Condom use at last sex

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Arch Sex Behav (2015) 44:509–519

Table 3 Association between reporting meeting a sex partner from the internet in the past 12 months and ever being tested for HIV, HIV testing in the past 12 months and STI history overall, and by sex Outcome

Ever tested for HIVa

Overall

Females

Males

Crude OR (95 % Adjusted OR CI) (95 % CI)

Crude OR (95 % Adjusted OR CI) (95 % CI)

Crude OR (95 % Adjusted OR CI) (95 % CI)

1.50 (1.26–1.78) 1.23 (0.96–1.57)

1.02 (0.74–1.41) 0.91 (0.57–1.44)

2.03 (1.66–2.50) 1.40 (1.04–1.88)

HIV testing in past 12 monthsa 1.23 (1.07–1.41) 1.19 (0.99–1.44)

1.30 (0.99–1.73) 1.80 (1.19–2.72)

1.24 (1.06–1.46) 1.00 (0.70–1.19)

HIV testing in past 12 monthsa 1.06 (0.89–1.25) 1.01 (0.81–1.26) (SA)b

0.93 (0.66–1.32) 1.12 (0.72–1.75)

1.21 (0.99–1.47) 0.88 (0.67–1.14)

STI historyc

0.98 (0.77–1.24) 1.08 (0.78–1.49)

0.98 (0.85–1.13) 1.05 (0.86–1.15)

0.89 (0.79–1.01) 1.02 (0.87–1.19)

Number of sex partnersd 1

0.50 (0.36–0.70) 0.81 (0.53–1.24)

0.97 (0.39–2.42) 1.36 (0.40–4.59)

0.55 (0.38–0.78) 0.86 (0.53–1.37)

2

1.52 (1.10–2.10) 1.85 (1.22–2.82)

3.86 (1.56–9.53) 5.18 (1.58–17.0)

1.24 (0.87–1.76) 1.53 (0.95–2.49)

C3

4.78 (3.48–6.56) 5.41 (3.51–8.33)

11.7 (4.75–28.9) 9.61 (2.85–32.4)

3.45 (2.44–4.88) 5.31 (3.21–8.78)

Anonymous sex partners

5.03 (4.38–5.78) 3.40 (2.86–4.05)

4.67 (3.45–6.30) 2.96 (2.06–4.25)

4.05 (3.45–4.74) 3.25 (2.64–3.99)

Commercial sex Condom usee

5.47 (4.04–7.41) 1.58 (1.00–2.50) 1.38 (1.23–1.56) 1.02 (0.87–1.19)

9.31 (5.80–14.9) 1.26 (0.56–2.85) 0.88 (0.69–1.12) 0.85 (0.62–1.17)

4.47 (2.96–3.75) 2.42 (1.34–4.35) 1.42 (1.23–1.63) 0.89 (0.73–1.08)

a

Adjusted estimates controlled for gender, race, age, employment, education, number of sex partners in the past 3 months, sexual orientation, STI history, anonymous sex partners, commercial sex and condom use at last sex

b

Sensitivity analyses - excluded participants whose test date within the past 12 months was at the time of their clinic visit

c

Adjusted estimates controlled for gender, race, age, employment, education, number of sex partners in the past 3 months, sexual orientation, anonymous sex partners, commercial sex and condom use at last sex

d

Number of sex partners in the past 3 months

e

Condom use at last sex

Table 4 Association between reporting meeting a sex partner from the internet in the past 12 months and HIV testing, STI history, and risky sexual behavior by MSM status Outcome

Heterosexual men Crude OR (95 % CI) a

MSM Adjusted OR (95 % CI)

Crude OR (95 % CI)

Adjusted OR (95 % CI)

Ever tested for HIV

1.53 (1.18–1.98)

1.55 (1.09–2.21)

1.26 (0.82–1.95)

1.22 (0.68–2.20)

HIV testing in past 12 monthsa

1.29 (1.08–1.56)

0.96 (0.72–1.26)

1.09 (0.82–1.46)

1.15 (0.78–1.70)

HIV testing in past 12 monthsa (RA)b STI historyc

0.83 (0.66–1.03) 1.03 (0.85–1.26)

0.96 (0.72–1.26) 1.12 (0.87–1.43)

0.97 (0.67–1.39) 0.97 (0.76–1.25)

1.21 (0.75–1.96) 0.98 (0.71–1.37)

1

0.72 (0.41–1.28)

1.06 (0.49–2.31)

0.68 (0.40–1.15)

0.82 (0.43–1.58)

2

1.50 (0.85–2.64)

1.74 (0.78–3.90)

1.67 (1.00–2.85)

1.41 (0.74–2.68)

C3

Number of sex partnersd

4.29 (2.47–7.46)

4.83 (2.24–10.4)

5.28 (3.12–8.93)

4.73 (2.49–8.99)

Anonymous sex partners

3.82 (3.07–4.76)

3.25 (2.52–4.20)

4.02 (3.00–5.39)

3.16 (2.21–4.53)

Commercial sex

4.91 (2.93–8.24)

2.46 (1.29–4.70)

6.52 (2.15–19.8)

3.27 (0.58–18.3)

Condom usee

0.93 (0.76–1.13)

0.81 (0.64–1.04)

1.18 (0.92–1.51)

1.04 (0.75–1.44)

a

Adjusted estimates controlled for gender, race, age, employment, education, number of sex partners in the past 3 months, sexual orientation, STI history, anonymous sex partners, commercial sex and condom use at last sex

b

Robustness analyses—excluded participants whose test date within the past 12 months was at the time of their clinic visit

c

Adjusted estimates controlled for gender, race, age, employment, education, number of sex partners in the past 3 months, sexual orientation, anonymous sex partners, commercial sex and condom use at last sex

d

Number of sex partners in the past 3 months

e

Condom use at last sex

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Arch Sex Behav (2015) 44:509–519

yearly HIV testing, compared to men who do not meet sex partners from the Internet. Compared to men who did not report meeting sex partners from the Internet, those who did were more likely to report risky sexual behavior such as multiple sex partners in the past 3 months, and having anonymous sex partners. This association was seen for heterosexual men and MSM. However the association between meeting sex partners on the Internet and exchanging sex for money and/or drugs was seen for heterosexuals but not for MSM. This lack of association among MSM could have been due to small cell sizes, which produced very wide confidence intervals. Men seeking sex partners from the Internet may take part in more protective behaviors (McFarlane et al., 2004) by getting an HIV test but may feel satisfied with ever getting testing and may not see the need for more frequent or annual testing. However, this population is also more likely to take part in risky behaviors (Benotsch et al., 2002; Garofalo et al., 2007; Horvath et al., 2008). In the current study, among the heterosexual male and MSM populations, there was no statistically significant association seen between meeting sex partners from the Internet and HIV testing in the past 12 months. Therefore, men who are using the Internet to seek sex partners are engaging in more sexual risk behavior, but are not getting frequent HIV tests like they should. Since high-risk men are more likely to seek sex partners from the Internet (Bolding et al., 2006), yearly HIV testing should be encouraged, especially for this population. The findings that meeting sex partners on the Internet was not associatedwith frequentHIV testingamongmenandlifetime HIV testing among women but was associated with risky sexual behavior among both groups suggest that HIV prevention strategies, specifically those with a focus on HIV testing, should target people who use the Internet to meet sex partners. However, while strategies focused on frequent HIV testing should not ignore women as targets, our research suggests that men will benefit greatly from these prevention efforts. HIV prevention efforts should also emphasize annual testing among male populations who use the Internet to seek sex partners, not only among MSM but their heterosexual peers. We found no statistically significant associations between reporting sex partners from the Internet and STI history. Even though the current study suggests that persons seeking sex partnersfrom theInternetmaytakepartinmoreriskysexual behavior, thisfindingsuggeststhatsexualhealthoutcomessuchashistoryof STIs might be similar among persons seeking sex partners from the Internet and those who do not. This result confirms previous findings of a lack of association between meeting a sex partner online and current or past STIs (Buhi et al., 2013) but conflicts with Elford et al. (2001), who found that seeking sex on the Internet was associated with recent STI. The estimates of the association may also have been biased towards the null if there had been misclassification of STI history with respect to meeting sex partners from the Internet.

517

The findings of this study should be considered with limitations in mind. First, the study is limited to STI clinics in the Richmond metro area in Virginia, and results might not be representative of other populations. Sentinel surveillance in STI clinics is usually based on populations with certain demographics and risk characteristics (Rietmeijer et al., 2009). For example, STI clinic patients tend to be younger and of a lower socio-economic class. It is also possible that many STI clinic patients may not have easy accesstotheInternet.STIclinicpatientsmayalsobemorelikelyto have had an HIV test and STI history compared to the general population. Therefore, these tendencies could have resulted in underestimates of the ‘‘true’’ associations. Second, social desirability bias could have contributed to the underreporting of meeting sex partners through the Internet, and/or STI history. Next, the study was cross-sectional so the temporal sequence of meeting sex partners through the Internet and HIV testing and STI history was unclear. It is also possible that men who self-identified as heterosexual could actually be MSM. However, we defined MSM as men who self-identified as being gay or bisexual or men who reported having sex with men in the past 3 months in order to better capture the MSM population. Additionally, STI clinic attendees who chose to take part in the survey might have been different from those who did not take part. We were unable to determine the differences and similarities between responders and non-responders. The VDH SSuN does not collect data on actual non-responders. If non-responders were different, this could have resulted in biased measures of association. Also, the measure of usingthe Internet toseek sex partnersdid not differentiate between meeting someone on a dating website or meeting someone through websites mostly soliciting anonymous sexual encounters. Determining this difference could have been helpful in determining the differences and/or similarities in varying degrees of using the Internet to seek sex partners, HIV testing, STI history, and risky sexual behavior. Despite these limitations, the study had several important strengths. This is one of the few studies to examine meeting sex partners on the Internet, and HIV testing, STI history and risky sexual behavior among non-MSM populations. The study also used data from the Virginia SSuN database, which was implemented to collect data on risky sexual behaviors from public STI clinics. As a result, we were able to consider sexual history characteristics such as number of sex partners and anonymous sex partners of the participants as confounders—variables that are generallynotcapturedinnational surveys(Rietmeijeretal.,2009). Conclusion The results showed that women who met a sex partner from the Internet were more likely to have had an HIV test in the past 12 months than women who did not meet a sex partner in this way. On the other hand, men who met a sex partner through the Internet were more likely to have ever had an HIV test than other men, but this was only seen for heterosexual

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men and not for MSM. All groups who reported meeting sex partners from the Internet were more likely to take part in risky sexual behavior. The results suggest that HIV testing should be targeted to men and women who meet sex partners on the Internet. Men who meet sexual partners on the Internet may benefit greatly from prevention efforts focused on frequent HIV testing. Acknowledgments Portions of the data used for this analysis were collected with support from CDC Grant number 5H25PS001282, the STD Surveillance Network (SSuN), to the Virginia Department of Health, Division of Disease Prevention.

References Al-Tayyib, A. A., McFarlane, M., Kachur, R., & Rietmeijer, C. A. (2009). Finding sex partners on the Internet: What is the risk for sexually transmitted infections? Sexually Transmitted Infections, 85, 216–220. Benotsch, E. G., Kalichman, S., & Cage, M. (2002). Men who have met sex partners via the Internet: Prevalence, predictors, and implications for HIV prevention. Archives of Sexual Behavior, 31, 177–183. Bolding, G., Davis, M., Hart, G., Sherr, L., & Elford, J. (2006). Heterosexual men and women who seek sex through the Internet. International Journal of STD and AIDS, 17, 530–534. Branson, B. M., Handsfield, H. H., Lampe, M. A., Janssen, R. S., Taylor, A. W., … Clark, J. E. (2006). Revised recommendations for HIV testing of adults, adolescents, and pregnant women in health-care settings. Morbidity and Mortality Weekly Report, 55, 1–17. Brown, M. J., Weitzen, S., & Lapane, K. L. (2013). Association between intimate partner violence and preventive screening among women. Journal of Women’s Health, 22, 947–952. Buhi, E. R., Klinkenberger, N., McFarlane, M., Kachur, R., Daley, E. M., Baldwin, J., … Rietmeijer C. (2013). Evaluating the Internet as a sexually transmitted disease risk environment for teens: Findings from the communication, health, and teens study. Sexually Transmitted Diseases, 40, 528–533. Centers for Disease Control and Prevention. (2012). Sexually Transmitted Disease Surveillance, 2011. Atlanta, GA: U.S. Department of Health and Human Services. Clark, T., Marquez, C., Hare, C. B., John, M. D., & Klausner, J. D. (2012). Methamphetamine use, transmission risk behavior and Internet use among HIV-infected patients in medical care, San Francisco, 2008. AIDS and Behavior, 16, 396–403. Coleman, E., Horvath, K. J., Miner, M., Ross, M. W., Oakes, M., & Rosser, B. (2010). Compulsive sexual behavior and risk for unsafe sex among Internet using men who have sex with men. Archives of Sexual Behavior, 39, 1045–1053. Cooper, A. (1998). Sexuality and the Internet: Surfing into the new millennium. Cyberpsychology & Behavior, 1, 187–193. Davis, M., Hart, G., Bolding, G., Sherr, L., & Elford, J. (2006). Sex and the Internet: Gay men, risk reduction and serostatus. Culture, Health & Sexuality, 8, 161–174. Elford, J., Bolding, G., & Sherr, L. (2001). Seeking sex on the Internet and sexual risk behavior among gay men using London gyms. AIDS, 15, 1409–1415. Garofalo, R., Herrick, A., Mustanski, B. S., & Donenberg, G. R. (2007). Tip of the iceberg: Young men who have sex with men, the Internet, and HIV risk. American Journal of Public Health, 97, 1113–1117. Grov, C., Agyemang, L., Ventuneac, A., & Breslow, A. S. (2013). Navigating condom use and HIV status disclosure with partners met online: A qualitative pilot study with gay and bisexual men from Craigslist.org. AIDS Education and Prevention, 25, 72–85.

123

Arch Sex Behav (2015) 44:509–519 Hays, R. B., Paul, J., Ekstrand, M., Kegeles, S. M., Stall, R., & Coates, T. J. (1997). Actual versus perceived HIV status, sexual behaviors and predictors of unprotected sex among young gay and bisexual men who identify as HIV-negative, HIV-positive and untested. AIDS, 11, 1495– 1502. Holt, M., Rawstorne, P., Wilkinson, J., Worth, H., Bittman, M., & Kippax, S. (2012). HIV testing, gay community involvement and Internet use: Social and behavioral correlates of HIV testing among Australian men who have sex with men. AIDS and Behavior, 16, 13–22. Horvath, K. J., Rosser, B. R., & Remafedi, G. (2008). Sexual risk taking among young Internet-using men who have sex with men. American Journal of Public Health, 98, 1059–1067. Jenness, S. M., Neaigus, A., Hagan, H., Wendel, T., Gelpi-Acosta, C., & Murrill, C. S. (2010). Reconsidering the Internet as an HIV/STD risk for men who have sex with men. AIDS and Behavior, 14, 1353–1361. King, S. A. (1999). Internet gambling and pornography: Illustrative examples of the psychological consequences of communication anarchy. Cyberpsychology & Behavior, 2, 175–193. Klein,H.(2011).UsingasyndemicstheoryapproachtostudyHIVrisktaking in a population of men who use the Internet to find partners for unprotected sex. American Journal of Men’s Health, 5, 466–476. Liau, A., Millett, G., & Marks, G. (2006). Meta-analytic examination of online sex-seeking and sexual risk behavior among men who have sex with men. Sexually Transmitted Diseases, 33, 576–584. Matarelli, S. A. (2013). Sexual sensation seeking and Internet sexseeking of Middle-Eastern men who have sex with men. Archives of Sexual Behavior, 42, 1285–1297. McFarlane, M., Bull, S. S., & Rietmeijer, C. A. (2000). The Internet as a newly emerging risk environment for sexually transmitted diseases. Journal of the American Medical Association, 284, 443–446. McFarlane, M., Kachur, R., Bull, S., & Rietmeijer, C. (2004). Women, the Internet, and sexually transmitted infections. Journal of Women’s Health, 13, 689–694. Mustanski, B. S. (2007). Are sexual partners met online associated with HIV/STI risk behaviours? Retrospective and daily diary data in conflict. AIDS Care, 19, 822–827. Newman, L. M., Dowell, D., Bernstein, K., Donnelly, J., Martins, S., Stenger, M., …Weinstock, H. (2012). A tale of two gonorrhea epidemics: Results from the STD surveillance network. Public Health Reports, 127, 282–292 Ogilvie, G. S., Taylor, D. L., Trussler, T., Marchand, R., Gilbert, M., Moniruzzaman, A., & Rekart, M. L. (2008). Seeking sexual partners on the Internet: A marker for risky sexual behaviour in men who have sex with men. Canadian Journal of Public Health, 99, 185–188. Oshri, A., Tubman, J. G., Morgan-Lopez, A. A., Saavedra, L. M., & Csizmadia, A. (2013). Sexual sensation seeking, co-occurring sex and alcohol use,andsexual riskbehavioramongadolescentsintreatment for substance use problems. American Journal on Addictions, 22, 197–205. Rietmeijer, C.A., Donnelly, J., Bernstein K. T., Bissette, J. M., Martins, S., Pathela, P., … Newman, L. M. (2009). Here comes the SSuN: Early experiences with the STD Surveillance Network. Public Health Reports, 124, 72–77 Stall, R., Mills, T. C., Williamson, J., Hart, T., Greenwood, G., Paul, J., … Catania, J. A. (2003). Association of co-occurring psychosocial health problems and increased vulnerability to HIV/AIDS among urban men who have sex with men. American Journal of Public Health, 93, 939–942 Taylor, M., Aynalem, G., Smith, L., Bemis, C., Kenney, K., & Kerndt, P. (2004). Correlates of Internet use to meet sex partners among men who have sex with men diagnosed with early syphilis in Los Angeles County. Sexually Transmitted Diseases, 31, 552–556. Virginia Department of Health, Office of Epidemiology Division of Disease Prevention. (2011). STD Surveillance Network Report. White, J. M., Mimiaga, M. J., Reisner, S. L., & Mayer, K. H. (2013). HIV sexual risk behavior among black men who meet other men on the Internet for sex. Journal of Urban Health, 90, 464–481.

Arch Sex Behav (2015) 44:509–519 Whiteley, L. B., Brown, L. K., Swenson, R. R., Valois, R. F., Vanable, P. A., Carey, M. P., … Romer, D. (2012). African American adolescents meeting sex partners online: Closing the digital research divide in STI/ HIV prevention. Journal of Primary Prevention, 33, 13–18 Wulfert, E., Safren, S. A., Brown, I., & Wan, C. K. (1999). Cognitive, behavioral, and personality correlates of HIV-positive persons’

519 unsafe sexual behavior. Journal of Applied Social Psychology, 29, 223–244. Young, S. D., & Rice, E. (2011). Online social networking technologies, HIV knowledge, and sexual risk and testing behaviors among homeless youth. AIDS and Behavior, 15, 253–260.

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