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For HIV-oblivious men the effect of dating place on UAI did not change by adding partner characteristics, but it improved when adding lifestyle and drug use. It's difficult to evaluate the real risk for HIV for these guys: do they behave as HIV negative men that want to protect themselves from HIV infection, or as HIV-positive guys attempting to safeguard their HIV-negative partner from HIV infection? A study by Horvath et al. Free sex dating nearest New South Wales. reported that 72% of guys who were never tested for HIV, profiled themselves online as being HIV negative, which might be debatable if they are HIV positive and participate in UAI with HIV-negative partners 12 Previously Matser et al. reported that 1.7% of the oblivious and perceived HIV negative MSM were examined HIV-positive. The study population included the MSM reported in this study 15

Online dating was not connected with UAI among HIV negative guys, a finding in agreement with some previous studies, mostly among young men 21 , but in comparison with other studies 1 - 5 This may be because of the reality that most earlier studies compared sexual behavior of two groups of MSM rather than comparing two sexual behaviour patterns within one group of guys. Yet it might also represent lay changes; maybe in the beginning of online dating a more high risk group of men used the Internet, and over time online dating normalized and not as high risk MSM today also use the Web for dating.

An integral strength of this study was that it explored the relationship between online dating and UAI among MSM who had recent sexual contact with both online and also offline casual partners. Free sex dating closest to NSW. This averted bias caused by potential differences between men just dating online and those only dating offline, a weakness of numerous previous studies. By recruiting participants at the biggest STI outpatient clinic in the Netherlands we could comprise a lot of MSM, and avoid potential differences in guys sampled through Internet or face to face interviewing, weaknesses in certain previous studies 3 , 11

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Among HIV-positive guys, in univariate analysis UAI was reported significantly more often with online associates 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 indicates that differences in partnership variables between online and offline partnerships are liable for the increased UAI in online established partnerships. This may be due to a mediating effect of more information on associates, (including perceived HIV status) on UAI, or to other factors. Among HIV negative guys no effect of online dating on UAI was discovered, either in univariate or in the multivariate models. Among HIV-oblivious guys, online dating was associated with UAI but only critical when adding associate and partnership variables to the model.

In this large study among MSM attending the STI clinic in Amsterdam, we found no evidence that online dating was independently related to a higher risk of UAI than offline dating. For HIV negative men 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). Ultimo New South Wales free sex dating. Only among guys who indicated they weren't aware of their HIV status (a little group in this study), UAI was more common with online than offline partners.

The amount of sex partners in the preceding 6months of the index was likewise connected 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 occurred in the partnership (OR = 16.29 95 % CI 7.07-37.52 for >10 sex acts within the partnership compared to only one sex act). Other variables significantly associated with UAI were group sex within the partnership, and sex-connected multiple drug use within partnership.

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In multivariate model 3 (Tables 4 and 5 ), additionally including variables concerning sexual behaviour in the venture (sex-associated multiple drug use, sex frequency and partner kind), the independent effect of online dating location on UAI became somewhat stronger (though not significant) for the HIV positive guys (aOR = 1.62 95 % CI; 0.96-2.72), but remained similar for HIV-negative men (aOR = 0.94 95 % CI 0.59-1.48). The result of online dating on UAI became stronger (and critical) for HIV-unaware guys (aOR = 2.55 95 % CI 1.11-5.86) (Table 5 ).

In univariate analysis, UAI was significantly more inclined to happen in on-line 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 impact of dating place on UAI differed by HIV status, as can be seen best in Table 5 Table 5 shows the association of online dating using three different reference groups, one for each HIV status. Among HIV positive guys, 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 apparent between UAI and online partnerships (OR = 1.07 95 % CI 0.71-1.62). Among HIV-oblivious guys, UAI was more common in online in comparison to offline partnerships, though not statistically significant (OR = 1.65 95 % CI 0.79-3.44).

Characteristics of on-line and offline partners and partnerships 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 on-line 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. 41.3%; P 0.001). Sex-associated substance use, alcohol use, and group sex were less often reported with on-line partners.

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To be able to analyze the possible mediating effect of more info on partners (including perceived HIV status) on UAI, we developed three variant models. In version 1, we adjusted the association between online/offline dating place 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 adapted also for partnership sexual risk behavior (i.e., sex-associated drug use and sex frequency) and venture sort (i.e., casual or anonymous). As we assumed a differential effect of dating place for HIV-positive, HIV-negative and HIV status unknown MSM, an interaction between HIV status of the participant and dating place was included in all three models by making a brand new six-class variable. For clarity, the effects of online/offline dating on UAI are also presented individually for HIV negative, HIV positive, and HIV-oblivious guys. Free Sex Dating in Ultimo NSW. We performed a sensitivity analysis confined to partnerships in which just 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 significant associations. As a fairly big number of statistical tests were done and reported, this strategy does lead to an elevated danger of one or more false positive associations. Investigations were done utilizing the statistical programme STATA, version 13 (STATA Intercooled, College Station, TX, USA).

Before the evaluations we developed a directed acyclic graph (DAG) representing a causal model of UAI. In this model some variants were putative causes (self-reported HIV status; on-line partner acquisition), others were considered as confounders (participants' age, participants' ethnicity, and no. Ultimo, New South Wales Free Sex Dating. Free Sex Dating Near Me Mascot New South Wales. of male sex partners in preceding 6months), and some were presumed to be on the causal pathway between the primary exposure of interest and results (age difference between participant and partner; ethnic concordance; concordance in life styles; HIV concordance; partnership sort; sex frequency within venture; group sex with partner; sex-related substance use in venture).

We compared characteristics of participants by self-reported HIV status (using 2-tests for dichotomous and categorical variables and using rank sum test for continuous variables). We compared characteristics of participants, partners, and venture sexual behaviour by online or offline venture, and computed P values based on logistic regression with robust standard errors, accounting for correlated data. Continuous variables (i.e., age, number of sex partners) are reported as medians with an interquartile range (IQR), and were categorised for inclusion in multivariate models. Random effects logistic regression models were used to examine the association between dating location (online versus offline) and UAI. Likelihood ratio tests were used to gauge the value of a variable in a model.

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As a way to investigate possible disclosure of HIV status we also asked the participant whether the casual sex partner knew the HIV status of the participant, with the reply alternatives: (1) no, (2) perhaps, (3) yes. Sexual behaviour with each partner was dichotomised as: (1) no anal intercourse or simply protected anal intercourse, and (2) unprotected anal intercourse. To ascertain the subculture, we asked whether the participant characterised himself or his partners as belonging to at least one of the following subcultures/lifestyles: casual, formal, alternative, drag, leather, military, sports, fashionable, punk/skinhead, rubber/lycra, gothic, bear, jeans, skater, or, if not one of these features were applicable, other. Ultimo, NSW Free Sex Dating. Concordant lifestyle was categorised as: (1) concordant; (2) discordant. Accidental partner kind was categorised by the participants into (1) known traceable and (2) anonymous partners.

HIV status of the participant was obtained by asking the question 'Do you understand whether you're HIV infected?', with five answer choices: (1) I 'm certainly not HIV-infected; (2) I think that I'm not HIV-infected; (3) I don't know; (4) I think I may be HIV-contaminated; (5) I know for sure that I 'm HIV-contaminated. We categorised this into HIV-negative (1,2), unknown (3), and HIV positive (4,5) status. The survey enquired about the HIV status of each sex partner together with the question: 'Do you know whether this partner is HIV-infected?' with similar answer options as above. Perceived concordance in HIV status within ventures was categorised as; (1) concordant; (2) discordant; (3) unknown. The final group represents all partnerships where the participant didn't understand his own status, or the status of his partner, or both. In this study the HIV status of the participant is self-reported and self-perceived. The HIV status of the sexual partner is as perceived by the participant.

Participants completed a standardised anonymous questionnaire during their visit to the STI outpatient clinic while waiting for preliminary test results after their consultation using a nurse or doctor. The questionnaire elicited information on socio-demographics and HIV status of the participant, the three most recent partners in the preceding six months, and data on sexual behaviour with those partners. A thorough description of the study design and the survey is provided elsewhere 15 , 18 Our chief determinant of interest, dating place (e.g., the name of a bar, park, club, or the name of a site) was obtained for every partner, and categorised into on-line (websites), and offline (physical sites) dating locations. To simplify the language of recognizing the partners per dating place, we refer to them as on-line or offline partners.

We used data from a cross sectional study focusing on spread of STI via sexual networks 15 Between July 2008 and August 2009 MSM were recruited from the STI outpatient clinic of the Public Health Service of Amsterdam, the Netherlands. Men were eligible for participation if they reported sexual contact with men during the six months preceding the STI consultation, they were at least 18years old, and may comprehend written Dutch or English. Individuals could participate more than once, if subsequent visits to the clinic were related to a potential new STI episode. Participants were regularly screened for STI/HIV according to the standard procedures of the STI outpatient clinic 15 , 17 The study was accepted by the medical ethics committee of the Academic Medical Center of Amsterdam (MEC 07/181), and written informed consent was obtained from each participant. Included in this investigation were men who reported sexual contact with at least one casual partner dated online as well one casual partner dated offline. Free Sex Dating Near Me Cheltenham New South Wales.

With increased familiarity in sexual partnerships, for example by concordant ethnicity, age, lifestyle, HIV status, and raising sex frequency, the likelihood for UAI increase as well 14 - 16 We compared the occurrence of UAI in online got casual partnerships to that in offline acquired casual partnerships among MSM who reported both online and offline casual partners in the preceding six months. Free Sex Dating near me New South Wales. We hypothesised that MSM who date sex partners both online and offline, report more UAI with the casual partners they date on the internet, and that this effect is partially clarified through better knowledge of partner features, including HIV status.