IN RECENT YEARS, THE Internet has become increasingly popular as a means for meeting sex partners and setting up liaisons. Partners can be met through chat rooms, discussion forums, instant messaging systems, websites soliciting sex, and personal advertisements. Men who have sex with men (MSM) may find this form of sex-seeking appealing because it offers anonymity, privacy, safety, minimal cost, and easy access at any time.1
The Internet has been implicated in several outbreaks of sexually transmitted infections (STI) among MSM. A syphilis outbreak in San Francisco was traced back to a chat room used predominantly by MSM,2–4 and another outbreak in Calgary was also traced to men seeking sex partners on the Internet.5 Case studies have linked online sex-seeking to the transmission of the human immunodeficiency virus (HIV) as well.6 Some of these events occurred around the time epidemiologic studies of MSM in North America and Europe observed increases in the prevalence of sexual risk behaviors.7–16
It is important to determine whether MSM's online sex-seeking is contributing to unsafe sexual practices and transmission of STIs. If many men look for sex partners online, and if many of those men are also engaging in high-risk behaviors, then Internet sex-seeking may indeed be contributing to the spread of STIs beyond that which occurs when MSM meet sex partners at venues such as bars, clubs, parties, or community events.
In the past 5 years, several studies have been published on online sex-seeking and sexual practices among MSM. These studies varied considerably in the manner in which they were performed (e.g., sampling, recruitment venues, behavioral measurement), the types of stratifications that were made (e.g., HIV status of participants), and the findings they obtained. To achieve an integrative understanding of this literature, it is necessary to consider the findings as a whole, giving attention to methodological characteristics of the studies. Accordingly, we conducted a systematic review of published findings and used meta-analysis techniques to quantitatively combine results so that valid conclusions can be drawn about the following questions:
* What percentage of MSM have used the Internet to look for sex partners?
* What percentage of MSM have actually had sex with partners found online?
* Is the prevalence of sexual risk behavior higher among MSM who use the Internet to look for sex partners than MSM who do not?
Literature Search and Study Selection
The public's use of the Internet gained momentum in the mid-1990s. The start date for our literature search was 1988 (through July 2005) so as not to miss any early studies. Electronic databases including MEDLINE, AIDSLINE (through December 2000), PsycInfo, EMBASE, CINAHL, and SOCIOFILE were searched to identify relevant English-language articles, abstracts, book chapters, and doctoral dissertations. The first-level search used the following keywords: Internet, online, electronic, websites, chatrooms, and cybersex, and generated 83,926 documents. A second-level search (i.e., search within) of these documents used the following demographic terms: MSM, men who have sex with men, gay men, bisexual, and homosexual men, and reduced the number of documents to 311. Of these, 20 published articles met inclusion criteria (see below). Two additional articles were identified through hand searches of relevant journals or through checking reference lists of articles included in the meta-analysis, bringing the total to 22.
Studies were included if they met the following criteria:
1. The study recruited MSM or gay men (including bisexual men if they were part of the sample) and did not pool analyses with non-MSM populations.
2. The article provided data on 1 or more of the following: percentage of MSM's use of the Internet to seek sex partners or percentage that actually had sex with partners found online, sexual behavior stratified by MSM who used or did not use the Internet to find sex partners, or sexual behavior stratified by whether study participants were recruited into studies through the Internet (e.g., chat rooms, gay-related websites) or at offline venues (e.g., gay bars, bookstores, gyms, newsletters, gay pride events).
Information on the following variables was abstracted: author(s), setting of data collection, study recruitment method (online versus offline), sample size, location of study, method of data collection (self-administered versus interviewer-administered questionnaire), sexual behavior measured, participants' HIV status if provided, and findings relevant to the questions posed for this review.
The data abstraction was guided by the following rules:
1. Generally, 1 finding per study was selected so as not to violate the assumption of independence of data in the meta-analysis. However, a study could contribute 2 or more findings if it had independent groups of participants (e.g., HIV-positive, HIV-negative, HIV-unknown MSM) and data for each group.
2. Only 1 sexual behavior outcome per sample (or group) was used. If findings on multiple behaviors were reported, we selected the one with the highest risk of contracting or transmitting HIV (e.g., anal rather than oral sex). Prevalence of unprotected anal intercourse (UAI) was selected as the primary outcome variable because nearly all studies provided data on this behavior.
3. If data were available for 2 or more partners, we selected the partner with the highest risk of contracting or transmitting HIV (e.g., serodiscordant rather than seroconcordant partners). Because STIs (e.g., syphilis, gonorrhea) and HIV superinfection (among HIV-positive persons) can be transmitted in HIV-seroconcordant partnerships, relevant findings from those partnerships are described and examined in a sensitivity analysis.
4. Most studies reported univariate findings or unadjusted descriptive data. If both univariate and multivariate results were reported, we used the univariate results because the multivariate models differed across studies, making it difficult to interpret the findings.
5. If 2 or more publications reported sexual behavior data from the same database, we used the findings from the most recently published paper.
Analytic Approach and Calculation of Effect Size (ES)
To examine the percentage of MSM who had used the Internet to look for sex partners, a weighted mean percentage and 95% confidence interval (CI) were calculated from available findings. Weights were determined by sample size. Calculations were conducted separately for studies that recruited MSM through the Internet and for studies that recruited MSM offline. To examine differences in sexual behavior by participants' HIV status, comparisons (HIV-positive versus HIV-negative/unknown) were conducted using procedures described below for calculating an ES.
A meta-analysis was conducted of differences in the prevalence of sexual risk behavior of MSM who had sought sex partners online versus those who had not. An additional meta-analysis examined sexual behavior differences by method of study recruitment (online versus offline). ESs were estimated with odds ratios (ORs) because the studies compared 2 groups of MSM on a dichotomous behavioral variable. An OR greater than 1 indicates an increased likelihood of risky sex among MSM who sought sex partners on the Internet (versus not) and among those who were recruited online (versus offline).
Standard meta-analytic methods were used.17,18 A random-effects model for aggregating individual ESs was used because it provides a conservative estimate of the variance and generates more accurate inferences about a population of studies beyond those included in the review.19 We first obtained the log OR (lnOR) and calculated its corresponding weight (i.e., inverse variance) for each independent sample. In estimating the overall ES, we multiplied each lnOR by its weight, summed the weighted lnOR across samples, and then divided by the sum of the weights. For purpose of presenting the results, the aggregated lnOR was converted back to OR by exponential function, and a 95% CI was derived.
Sensitivity analyses examined the effect of outliers by comparing the aggregated ES with estimates obtained after iterations using k − 1 findings (k = number of independent findings). In other words, we removed a finding and calculated the aggregated ES. We then replaced that finding, removed another, and repeated the process. We also examined the extent to which the aggregated ES changed when different types of partnerships (e.g., HIV-seroconcordant instead of HIV-serodiscordant) were used in the meta-analysis.
What Percentage of MSM Have Used the Internet to Look for Sex Partners?
There were 29 findings from 14 studies on the percentage of MSM who had looked for sex partners through the Internet (Table 1). 20–33 The percentages ranged from 23.3% to 98.5%. This wide variation can be accounted for largely by methodological differences in how study participants were recruited. In studies that recruited and surveyed participants online (k = 13), the range was 63.8% to 98.5% (weighted mean = 84.7%; 95% CI, 81.4%–88.0%), and in studies that recruited and surveyed offline (k = 15), the range was 23.3% to 57.3% (weighted mean = 40.2%; 95% CI, 35.2%–45.2%). The prevalence was much higher in MSM recruited entirely online because many of those studies recruited men in chat rooms used to find sex partners. A sensitivity analysis indicated that each of these 2 weighted means was affected less than ±2% with any single finding removed.
A meta-analysis was conducted of 3 findings (all from the United Kingdom; none were available from U.S. studies) on the prevalence of Internet sex-seeking stratified by participants' HIV status.22,23,25 Among MSM recruited online, HIV-positive MSM were significantly more likely than HIV-negative/unknown MSM to have sought sex partners through the Internet (OR = 2.95; 95% CI, 2.06–4.23; k = 3). The weighted mean percentage for HIV-positive MSM was 93.5% (95% CI, 91.8%–95.2%), and for HIV-negative/unknown MSM it was 82.0% (95% CI, 79.2%–84.7%). The findings were similar, albeit nonsignificant, when HIV-positive participants and their study counterparts were recruited offline (OR = 1.52; 95% CI, 0.86–2.67; k = 3). The respective weighted mean percentages were 49.6% (95% CI, 44.9%–54.3%) and 41.2% (95% CI, 36.8%–45.6%).
What Percentage of MSM Have Actually Had Sex With Partners Found Online?
There were 8 findings from 8 studies on the percentage of MSM who reported that they actually had sex with partners found online (Table 1). 20,21,26,27,34–37 The findings varied considerably (range from 22.4% to 93.5%), due mainly to differences in recruitment methods. For studies that recruited participants online, the range was 78.3% to 93.5% (weighted mean = 81.6%; 95% CI, 76.3%–86.9%; k = 5), and for studies that recruited offline, the range was 22.4% to 33.0% (weighted mean = 30.3%; 95% CI, 26.3%–34.3%; k = 3). The weighted means changed less than ±3% with any single finding removed. The findings could not be examined by HIV status of participants, because none of the studies provided data stratified by that variable.
Is the Prevalence of Sexual Risk Behavior Higher Among MSM Who Use the Internet to Look for Sex Partners Than MSM Who Do Not?
A total of 11 findings from 8 studies provided data relevant to this question. 25,27–29,32,36,38,39 Participants were recruited at offline venues (in all studies except 139) and stratified by self-report of Internet sex-seeking (yes versus no). The meta-analysis indicated that high-risk sexual behavior with any partners was significantly more likely among MSM who sought partners online than those who did not (OR = 1.68; 95% CI, 1.18–2.40; k = 11) (Table 2). Two of the 8 studies25,28 provided data separately for HIV-positive and HIV-negative MSM participants and found that, for each serostatus group, the prevalence of UAI with HIV-serodiscordant or status-unknown male partners was higher among men who used (versus did not use) the Internet for sex-seeking. These same 2 studies also provided data on UAI with HIV-seroconcordant male partners in the past 3 months (data not shown in Table 2). For HIV-positive MSM participants, the prevalence of HIV-seroconcordant UAI in those studies was significantly higher among those who sought sex through the Internet than among those who did not (32%–38% versus 4%–8%, P <0.01 in both studies25,28). For HIV-negative MSM, however, the prevalence of UAI with HIV-seroconcordant male partners was lower in the online than offline group (12.7% versus 23.5%, P <0.05).28 When the findings with HIV-seroconcordant partners were used in the meta-analysis instead of the findings with HIV-serodiscordant partners, the aggregated OR remained virtually the same (OR = 1.66; 95% CI, 1.16–2.37; k = 11).
Almost all of the studies measured anal intercourse without a condom. Two studies, however, measured receptive anal intercourse with or without a condom.29,32 When we omitted those 2 studies from the meta-analysis, the aggregated OR (k = 9) increased slightly to 1.71. One other study measured use of a condom during last sexual encounter.27 When that study was omitted, the aggregated OR (k = 10) increased to 1.81. The overall OR remained significant (P <0.05) when any single finding was removed.
A few studies collected data on self-reported STIs, but those findings were not included in the meta-analysis because of the qualitatively different nature of the outcome variable and the limited number of findings. One study found that the prevalence of any STI in the prior 12 months was higher among MSM who used the Internet to find sex partners compared with their counterparts (28.8% versus 18.8%, P <0.05).30 In a study that pooled MSM (majority of sample) with heterosexual men and women, lifetime prevalence of STI was higher in the Internet than non-Internet group (29.3% versus 20.4%, P <0.05).27 Another study, however, did not find that Internet groups differed in lifetime prevalence of STIs among MSM (51.2% versus 53.8%).31
A final set of studies examined sexual behavior by method of recruiting MSM into studies. If MSM recruited into studies through online websites (compared with recruitment at offline venues) are more likely to seek sex partners through the Internet, then it is informative to compare the sexual behavior of MSM recruited online versus offline. Three studies provided 7 independent findings on the prevalence of online sex-seeking stratified by method of study recruitment.23–25 Each of the 7 comparisons was highly significant (P <0.01), indicating that online sex-seeking was more prevalent among participants recruited online (mostly from chat rooms) than offline (aggregated OR = 9.37; 95% CI, 5.30–16.57; k = 7). Further, a meta-analysis of 10 independent findings from 6 studies indicated that UAI was significantly more likely among MSM participants recruited online than offline (OR = 1.57; 95% CI, 1.25–1.98; k = 10) (Table 3).23–26,40,41 In the 2 studies that stratified participants by HIV status, the findings were generally consistent for HIV-positive, HIV-negative, and HIV-unknown MSM.23,25 The overall OR remained significant (P <0.05) when any single finding was omitted.
The first question concerned the percentage of MSM who use the Internet to search for sex partners. The findings from studies that recruited participants through Internet chat rooms greatly overestimate the percentage of MSM who look for partners online because those chat rooms are typically used to find partners. A more accurate estimate may come from the 9 studies that recruited MSM offline (e.g., gay pride events, gay gyms, health departments, STI clinics). The aggregated findings of those studies suggest that approximately 40% of MSM have sought sex partners through the Internet. The prevalence of online sex-seeking was somewhat higher among HIV-positive than HIV-negative/unknown MSM in the United Kingdom. Data stratified by participants' HIV status were not available from U.S. studies. About the second question, among MSM participants recruited offline, the percentage who actually had sex with a person met through the Internet (30%) was only somewhat lower than the percentage who looked for sex partners online (40%). The studies used a wide variety of recruitment venues; some recruited at STI clinics and sex resorts (presumably higher-risk MSM); others recruited at gay pride events and gyms (presumably a more general sample of MSM). Thus, the samples included a full range of MSM (from higher to lower risk), which increases the external validity of the aggregated results. Nevertheless, caution must be used in generalizing the prevalence estimates to the general MSM population.
As for the third question, UAI was more prevalent among MSM who used the Internet to look for sex partners than MSM who did not. This group difference was observed for UAI with HIV-serodiscordant/unknown partners as well as HIV-seroconcordant partners among HIV-positive study participants.25,28 A similar group difference was observed for UAI with HIV-serodiscordant/unknown partners among HIV-negative participants,25,28 but the prevalence of HIV-seroconcordant UAI was lower among HIV-negative participants who used (versus did not use) the Internet to search for partners.28 The findings from these 2 studies do not indicate that serosorting tendencies (i.e., UAI between men of the same serostatus) are more prevalent among MSM who look for partners online versus MSM who do not. Other comparisons from these studies also suggest that serosorting was not occurring. Among HIV-positive MSM who looked for partners online, the prevalence of UAI with HIV-seroconcordant partners (32–38%) was only slightly higher than the prevalence of UAI with HIV-serodiscordant partners (27–34%).25,28 Among HIV-negative MSM who looked for partners online, the prevalence of UAI was higher with HIV-serodiscordant (23%) than HIV-seroconcordant partners (13%).28
Two hypotheses may account for the association of Internet sex-seeking and increased likelihood of unsafe sex. One suggests that men prone to engage in risky sex may be more likely than men who practice safer sex to use the Internet to meet sex partners (self-selection hypothesis). That is, high-risk men may be more prone to gravitate to the Internet as a main or as an additional venue to meet partners. This explanation, by itself, however, misses the dynamic process of Internet sex-seeking, which may accentuate risk behavior and transmission of STIs beyond that which occurs when partners are sought in other settings (accentuation hypothesis). The Internet is an environment that expands access to sex partners, thus potentially increasing the prevalence of sexual activity and the likelihood of unsafe sex. Further, the Internet may be creating a “network” of high-risk men that facilitates transmission of STIs among Internet sex-seekers, who may spread infection to other partners met at offline venues such as bars, clubs, and parties.
It is likely that both self-selection and accentuation are occurring, but it is difficult to specify their relative contribution or demonstrate their respective roles from the studies in the meta-analysis. The accentuation hypothesis can be addressed more clearly by examining behavior with partners met online and behavior with partners met offline. Limited data are available on this issue. Two studies that recruited MSM online found that they reported more online than offline sex partners in the prior 12 months (M = 10.0 versus M = 5.534; M = 9.0 versus M = 8.120), but condom use during last anal or vaginal intercourse was somewhat more prevalent with online than offline partners (70.7% versus 57%).20 Another study25 found that HIV-positive MSM who used the Internet to look for sex partners were about equally likely to engage in UAI with HIV-serodiscordant/unknown partners found online as with HIV-serodiscordant/unknown partners found offline. However, among these HIV-positive MSM, HIV-seroconcordant UAI was more prevalent with partners found online than offline.25 These findings as a whole do not provide compelling evidence that the Internet is accentuating sexual risk behavior about HIV transmission, although it is too early to draw any firm conclusions. The evidence will be more compelling if future studies find that online-recruited MSM not only have more online than offline partners but are also more likely to engage in risky sex (e.g., HIV-serodiscordant UAI) with partners met online than offline. It would also be informative to have longitudinal data on behavior before and after a person begins to use the Internet to look for sex partners. This would provide a direct test of the accentuation hypothesis and would help rule out confounding variables that affect between-group comparisons.
Many of the primary studies in our meta-analysis have methodological limitations that restrict generalization of the findings. First, none of the U.S. studies of sexual behavior of Internet users reported findings stratified by participants' HIV status. Analysis of sexual behavior according to the serostatus of study participants and the serostatus of sex partners is important because it provides data on serosorting tendencies.42 Second, all of the U.S. studies were conducted with samples composed mostly of white MSM. A wider sampling frame is needed that includes meaningful numbers of Latino and black MSM who account for a highly disproportionate number of new HIV infections among men in the U.S.43 Further, more attention must be given to the issue of gay identification and its association with online sex-seeking. The Internet may be especially appealing to non–gay-identified MSM and those who desire anonymity, but little is known about their Internet practices and sexual behaviors with online partners.44
As this review makes evident, a considerable percentage of MSM use the Internet to look for sex partners, and those who do have a riskier sexual behavior profile than their counterparts. The extent to which the Internet may increase risk behavior beyond that which occurs when men meet partners at offline venues remains unclear. It is important to conduct more sophisticated studies of its possible role in accentuating risk behavior and transmission of STIs.
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