To be able to analyze the potential mediating effect of more info on partners (including perceived HIV status) on UAI, we developed three multivariable models. In model 1, we adapted the organization between online/offline dating location and UAI for characteristics of the participant: age, ethnicity, number of sex partners in the preceding 6months, and self-perceived HIV status. In model 2 we added the partnership characteristics (age difference, ethnic concordance, lifestyle concordance, and HIV concordance). In version 3, we adjusted additionally for partnership sexual risk behavior (i.e., sex-associated drug use and sex frequency) and venture type (i.e., casual or anonymous). As we assumed a differential effect of dating location for HIV-positive, HIV negative and HIV status unknown MSM, an interaction between HIV status of the participant and dating place was contained in all three models by making a new six-category variable. For clarity, the effects of online/offline dating on UAI are also presented individually for HIV negative, HIV positive, and HIV-oblivious guys. Cheap prostitutes nearest Wagner, Alberta. We performed a sensitivity analysis restricted to partnerships in which only one sexual contact occurred. Statistical significance was defined as P 0.05. No adjustments for multiple comparisons were made, in order not to miss potentially important organizations. As a fairly large number of statistical evaluations were done and reported, this strategy does lead to an increased risk of one or more false-positive organizations. Evaluations were done utilizing the statistical programme STATA, version 13 (STATA Intercooled, College Station, TX, USA).
Characteristics of online and offline partners and ventures are shown in Table 2 The median age of the partners was 34years (IQR 28-40). Compared to offline partners, more on-line partners were Dutch (61.3% vs. 54.0%; P 0.001) and were defined as a known partner (77.7% vs. 54.4%; P 0.001). The HIV status of on-line partners was more frequently reported as understood (61.4% vs. 49.4%; P 0.001), and in online partnerships, perceived HIV concordance was higher (49.0% vs. 39.8%; P 0.001). Participants reported that their online partners more frequently understood the HIV status of the participant than offline partners (38.8% vs. 27.2%; P 0.001). Participants more often reported multiple sexual contacts with online partners (50.9% vs. Cheap prostitutes closest to Wagner. 41.3%; P 0.001). Sex-related material use, alcohol use, and group sex were less frequently reported with internet partners.
In univariate analysis, UAI was significantly more inclined to happen in online than in offline partnerships (OR = 1.36 95 % CI 1.03-1.81) (Table 4 ). The self-perceived HIV status of the participant was firmly associated with UAI (OR = 11.70 95 % CI 7.40-18.45). The result of dating location on UAI differed by HIV status, as can be seen best in Table 5 Table 5 shows the association of online dating using three distinct reference groups, one for each HIV status. Cheap Prostitutes nearby Alberta. Among HIV positive men, UAI was more common in online when compared with offline partnerships (OR = 1.61 95 % CI 1.03-2.50). Among HIV-negative men no association was evident between UAI and online ventures (OR = 1.07 95 % CI 0.71-1.62). Among HIV-unaware guys, UAI was more common in online compared to offline ventures, though not statistically significant (OR = 1.65 95 % CI 0.79-3.44).
In multivariate model 3 (Tables 4 and 5 ), also including variants concerning sexual behaviour in the partnership (sex-related multiple drug use, sex frequency and partner type), the independent effect of online dating place on UAI became somewhat more powerful (though not critical) for the HIV positive guys (aOR = 1.62 95 % CI; 0.96-2.72), but remained similar for HIV negative guys (aOR = 0.94 95 % CI 0.59-1.48). The effect of online dating on UAI became stronger (and critical) for HIV-unaware men (aOR = 2.55 95 % CI 1.11-5.86) (Table 5 ).
The amount of sex partners in the preceding 6months of the index was also correlated with UAI (OR = 6.79 95 % CI 2.86-16.13 for those with 50 or more recent sex partners compared to those with fewer than 5 recent sex partners). UAI was significantly more likely if more sex acts had happened in the partnership (OR = 16.29 95 % CI 7.07-37.52 for >10 sex acts within the venture compared to just one sex act). Other factors significantly associated with UAI were group sex within the venture, and sex-related multiple drug use within partnership.
In this large study among MSM attending the STI clinic in Amsterdam, we found no signs that online dating was independently related to a higher danger of UAI than offline dating. Cheap Prostitutes nearest Wagner. For HIV-negative guys this lack of assocation was clear (aOR = 0.94 95 % CI 0.59-1.48); among HIV positive guys there was a non significant association between online dating and UAI (aOR = 1.62 95 % CI 0.96-2.72). Cheap Prostitutes in Wagner. Simply among men who suggested they were not informed of their HIV status (a small group in this study), UAI was more common with on-line than offline associates.
Among HIV positive guys, in univariate analysis UAI was reported significantly more often with online partners than with offline associates. When adjusting for associate features, the effect of online/offline dating on UAI among HIV-positive MSM became somewhat smaller and became non significant; this suggests that differences in partnership variables between online and also offline partnerships are responsible for the increased UAI in online established ventures. This may be due to a mediating effect of more info on partners, (including perceived HIV status) on UAI, or to other variables. Among HIV negative guys no effect of online dating on UAI was observed, either in univariate or in any of the multivariate models. Among HIV-oblivious men, online dating was connected with UAI but just critical when adding partner and venture variables to the model.
A vital strength of this study was that it explored the connection between online dating and UAI among MSM who had recent sexual contact with both online and offline casual partners. This avoided bias due to potential differences between men just dating online and those only dating offline, a weakness of several previous studies. By recruiting participants at the biggest STI outpatient clinic in the Netherlands we could include a lot of MSM, and avoid potential differences in men sampled through Internet or face-to-face interviewing, weaknesses in certain previous studies 3 , 11
Online dating was not correlated with UAI among HIV negative guys, a finding in agreement with some previous studies, mainly among young men 21 , but in contrast with other studies 1 - 5 This may be due to the fact that most earlier studies compared sexual behavior of two groups of MSM rather than comparing two sexual behaviour patterns within one group of guys. Nevertheless it can also reflect secular changes; perhaps in the beginning of online dating a more high-risk group of guys used the Internet, and over time online dating normalized and less high risk MSM now also utilize the Internet for dating.
For HIV-oblivious guys the impact of dating place on UAI didn't change by adding partner features, but it increased when adding lifestyle and drug use. It is difficult to evaluate the actual risk for HIV for these guys: do they act as HIV-negative guys that are trying to protect themselves from HIV infection, or as HIV-positive guys attempting to shield their HIV-negative partner from HIV infection? A study by Horvath et al. reported that 72% of men who were never tested for HIV, profiled themselves online as being HIV negative, which might be debatable if they're HIV positive and engage in UAI with HIV negative partners 12 Previously Matser et al. reported that 1.7% of the unaware and perceived HIV-negative MSM were tested HIV positive. The study population included the MSM reported in this study 15
Because determinations on UAI appear to be partially based on perceived HIV concordance, accurate knowledge of one's own and the partner's HIV status is important. In HIV negative guys and HIV status-unaware men, conclusions on UAI will not only be based on perceived HIV status of the partner but also on one's own negative status. HIV serosorting is challenged by the frequency of HIV testing and also the HIV window period during which people can transmit HIV but cannot be diagnosed with the commonly used HIV tests. Hence serosorting cannot be regarded as a very powerful way of preventing HIV transmission 22 Besides interventions to trigger the uptake of HIV and STI testing in sexually active men, interventions to warn against UAI based on sensed HIV-negative concordant status are in order, irrespective of whether this concerns online or offline dating. Cheap Prostitutes near Wagner, Alberta.
Dating online may offer other opportunities for communicating on HIV status than dating in physical environments. Easing more online HIV status disclosure during partner seeking makes serosorting simpler. Nonetheless, serosorting may increase the burden of other STI and will not prevent HIV infection completely. Interventions to prevent HIV transmission should especially be directed at HIV negative and unaware MSM and spark timely HIV testing (i.e., after risk occasions or when experiencing symptoms of seroconversion illness) as well as regular testing when sexually active.
New research should remain up to date in regards to fast changing dating approaches as well as sero-adaptive behaviours (like viral sorting and pre exposure prophylaxis). With each new way of dating and preventive opportunities, the rules of battles will be different. Our data are 8years old and net-based dating has developed since then. Cheap Prostitutes Near Me Wabasca Alberta. Cheap Prostitutes Near Me Wainwright Alberta. However these results are useful, as they show how net-based partner acquisition can lead to more information on the sex partner, and this might impact on the frequency of UAI.
AMC, Academic Medical Center; aOR, adjusted odds ratio; CI, confidence interval; CINIMA, Center for Infection and Immunology Amsterdam; DAG, directed acyclic graph; HIV, human immuno-deficiency virus; i.e., id est, it's, for example; IQR, interquartile range; MEC, Medical Ethics Committee; MSM, men who have sex with men; OR, odds ratio; RIVM, National Institute of Public Health and the Environment, Centre for Infectious Disease Control; STI, sexually transmitted infection; UAI, unprotected anal intercourse; UMCU, University Medical Center Utrecht
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