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Taken together, these results present an important, complex, and highly consistent picture of the relationship between HIV risk behavior of MISM and demographic characteristics. First, although most respondents across all demographic characteristics did not engage in UAIMP, almost one-third reported that they did. While others have reporting a similar finding, this is the first paper, to our knowledge to confirm this is true across almost all demographic characteristics of MISM.

Second, participants report almost twice the number of UAIMP met online than offline; although the proportion of partners with whom they engaged in UAI was actually less for online than offline. This association is robust across demographic characteristics confirming the need for HIV prevention to address sexual risk behavior with partners met on the Internet.

The Internet appears to facilitate efficiency in meeting men for sex and hence significantly increasing the likelihood of UAI male partners rather than increasing the rates of unsafe sex. Fourth, while risk of engaging in UAI appears elevated for most MISM with male partners met online, the multiple regression analyses identified several key demographic characteristics of men at higher risk. In addition to HIV-positive status, men with children were at 3. These men may have less opportunity to meet other men for sex, may experience greater isolation and stress, and may feel more need to seek sexual partners via the Internet given childrearing responsibilities.

On the other hand, the findings are consistent with national trends revealing that HIV disproportionately and increasingly affects African American communities Centers for Disease Control and Prevention Men in their thirties and low income earners appeared more likely to report UAIMP with men met online although the odd ratios for these relationships are less remarkable.

These results appear robust and internally consistent. Similarly, across demographics, the same key findings emerged. These results also are consistent with those previously reported in a smaller study of Latino MISM by our team Rosser et al. Limitations of the study include that the data are cross-sectional and hence we lack the ability to follow those at highest risk longitudinally although this is proposed in the next phase of this study.

It should also be noted that all recruitment was from a single gay website service provider and that the respondents represent a sample of men likely to respond to research surveys; hence generalization to MISM more broadly or to MISM at other sites cannot be assumed. Other limitations, common in sexual risk assessment studies, include the inability to independently confirm risk behavior, concerns about validity of responses in online research, and questions of representativeness in online convenience samples.

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The primary risk measure used, UAI male partners, does not take into account other strategies MISM may use to lower risk such as sero-sorting and sero-positioning; hence the risk estimates may be higher than actual risk. Finally, our analyses have been confined to the demographic and behavioral characteristics under study. It is interesting to speculate whether there are other variables such as internet use, prior exposure to HIV prevention, and psychosexual characteristics e.

We confirm that we are analyzing these data and propose reporting on the findings in a future publication. As our primary question here was to document risk behavior of MISM for informing HIV prevention behavioral epidemiology , not a comparison study of risk factors etiology , we concluded unstratified analyses were more appropriate to examine the research question.

Implications for primary HIV prevention include the prioritization of online HIV primary prevention interventions, recognizing the Internet is now the largest gay venue nationally and internationally and also a most efficient venue for meeting partners.

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HIV prevention needs to build understanding of online-mediated HIV risk between men by being grounded in a realistic, empirically-based understanding of virtual-mediated risk. The exception appears to be African American MISM where there appears greater risk in meeting partners offline rather than online. Aside from the characteristics identified in the regression, even in a large study, most demographic characteristics fail to distinguish MISM at risk from those not at risk.

With Internet-mediated liaisons defining MISM, and a similar level of risk common across most demographics, we concluded it makes the most sense to target online interventions towards all MISM, or possibly target those engaging in the most high risk behavior.

The exception may be men with many partners, HIV status and possibly MISM with children, where tailored intervention may prove highly effective. All research was carried out with the approval of the University of Minnesota Institutional Review Board, study number S Keith J. Joseph A. MN, USA. Gene P. John L. Read article at publisher's site DOI : Psychooncology , 28 12 , 11 Nov Cited by: 0 articles PMID: To arrive at the top five similar articles we use a word-weighted algorithm to compare words from the Title and Abstract of each citation.

Sex Transm Infect , 90 4 , 11 Feb Cited by: 48 articles PMID: J Med Internet Res , 17 12 :e, 09 Dec Souleymanov R , Huang YT. Glob Public Health , 11 , 04 May Cited by: 2 articles PMID: Coronavirus: Find the latest articles and preprints. Europe PMC requires Javascript to function effectively. Recent Activity. Recent history Saved searches.

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Rosser BR 1 ,. Oakes JM ,. Horvath KJ ,. Konstan JA ,. Danilenko GP ,. Peterson JL. Affiliations 1 author 1. Share this article Share with email Share with twitter Share with linkedin Share with facebook. Other predictors of increased online partner risk include being years old, having children, not living in the Northeast, and low income. Free full text. AIDS Behav. Author manuscript; available in PMC Jun PMID: Simon Rosser , J. Michael Oakes , Keith J. Horvath , Joseph A. Konstan , Gene P. Danilenko , and John L. Simon Rosser.

Michael Oakes. Author information Copyright and License information Disclaimer. Corresponding author. Copyright notice. See other articles in PMC that cite the published article. Go to:. Open in a separate window. Procedures Potential participants who clicked on the banner advertisement were sent to the MINTS II website, which was protected with appropriate encryption to ensure that transmission of information was secure.

Demographics Demographic questions were taken from the US Census Table 1 Distributions of total unprotected anal sex male partners in last 90 days by demographic characteristics of men who use the internet to seek sex with men MISM. Sexual Demographics Sexual orientation was assessed by adapting the 7-point Kinsey scale to measure behavior. Sexual Risk Measures For the primary dependent variable, two questions were asked concerning the participants online and offline sex-seeking behaviors.

Table 2 Bivariate comparison of mean and median unsafe sex partners met online and offline in last 90 days, by demographic characteristics. Table 3 Negative-binomial multiple regression models predicting number of unprotected anal intercourse male sexual partners UAIMP in total, met online and met offline, last 90 days.

Lower skilled 1.

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Latino 1. Small town 0. Midwest 1. Protestant 0. Moderate 0. Yes 2. Yes 1. Yes 0. Bisexual 1. Yes 3. Men who have men sex partners via the Internet: Prevalence, predictors and implications for HIV prevention. Archives of Sexual Behavior. Gonococcal isolate surveillance project. Resurgent bacterial sexually transmitted disease among men who have sex with men—King County, Washington, — Morbidity and Mortality Weekly Report.

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Greene WH. Econometric analysis. The second wave will drown us. American Journal of Public Health. Intentional unsafe sex barebacking among HIV-positive gay men who seek sexual partners on the Internet.

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AIDS Care. Barebacking among gay and bisexual men in New York city: Explanations for the emergence of intentional unsafe behavior. Virtual and physical venues as contexts for HIV risk among rural men who have sex with men. Extramural Health Psychology. A new meeting place: Chatting on the Internet, e-dating and sexual risk behaviour among Dutch men who have sex with men. Journal of the American Medical Association.

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