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AMC, Academic Medical Center; aOR, adjusted odds ratio; CI, confidence interval; CINIMA, Center for Infection and Immunology Amsterdam; DAG, directed acyclic graph; HIV, human immunodeficiency 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

New research should stay up-to-date when it comes to fast shifting dating processes and sero-adaptive behaviours (such as viral sorting and pre exposure prophylaxis). With each new way of dating and preventive chances, the rules of battles will change. Our data are 8years old and net-based dating has developed since then. Yet these results are useful, as they demonstrate how net-based partner acquisition can result in more information on the sex partner, and this may affect on the frequency of UAI.

Relationship online may offer other chances for communication on HIV status than dating in physical surroundings. Sex partner nearby Wellers Hill, QLD. Easing more on-line HIV status disclosure during partner seeking makes serosorting simpler. However, serosorting may increase the load of other STI and will not prevent HIV disease completely. Sex Partner near me Wellers Hill. Interventions to prevent HIV transmission should particularly be directed at HIV-negative and unaware MSM and stimulate timely HIV testing (i.e., after danger events or when experiencing symptoms of seroconversion illness) as well as regular testing when sexually active.

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Because conclusions on UAI seem to be partly based on perceived HIV concordance, accurate knowledge of one's own and the partner's HIV status is essential. In HIV-negative guys and HIV status-oblivious guys, decisions on UAI WOn't 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 individuals can transmit HIV but cannot be diagnosed with the commonly used HIV tests. So serosorting can't be regarded as a very effective 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 perceived HIV-negative concordant status are in order, irrespective of whether this concerns online or offline dating.

For HIV-unaware men the effect of dating location on UAI did not change by adding partner features, but it improved when adding lifestyle and drug use. It is difficult to assess the real risk for HIV for these guys: do they behave as HIV-negative men that are trying 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. reported that 72% of guys who were never tested for HIV, profiled themselves online as being HIV-negative, which might be problematic if they're HIV-positive and participate in UAI with HIV-negative partners 12 Formerly Matser et al. reported that 1.7% of the oblivious and perceived HIV-negative MSM were tested HIV-positive. The study population included the MSM reported in this study 15

Online dating wasn't correlated with UAI among HIV-negative guys, a finding in agreement with some previous studies, largely 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 behaviour of two groups of MSM rather than comparing two sexual behavior patterns within one group of guys. Nevertheless it could also reflect secular changes; possibly 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 today additionally use the Web for dating. Sex Partner near me Wellers Hill Queensland, Australia.

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A key 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 also offline casual partners. Wellers Hill Queensland Sex Partner. Sex Partner Near Me Browns Plains Queensland. This prevented bias caused by potential differences between men only dating online and those just dating offline, a weakness of numerous previous studies. Sex Partner closest to Wellers Hill, Australia. By recruiting participants at the greatest STI outpatient clinic in the Netherlands we could comprise a great number of MSM, and prevent potential differences in guys tried through Internet or face-to-face interviewing, weaknesses in certain previous studies 3 , 11

Among HIV-positive men, in univariate analysis UAI was reported significantly more often with on-line partners than with offline associates. When correcting for associate features, the effect of online/offline dating on UAI among HIV positive MSM became somewhat smaller and became nonsignificant; this indicates that differences in partnership factors between online and also offline partnerships are in charge of the increased UAI in online established partnerships. This could be because of a mediating effect of more information on partners, (including perceived HIV status) on UAI, or to other variables. Among HIV-negative men no effect of online dating on UAI was discovered, either in univariate or in some of the multivariate models. Among HIV-unaware guys, online dating was correlated with UAI but only essential when adding partner and partnership variables to the model.

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 risk of UAI than offline dating. For HIV negative men this dearth of assocation was clear (aOR = 0.94 95 % CI 0.59-1.48); among HIV positive guys there was a nonsignificant association between online dating and UAI (aOR = 1.62 95 % CI 0.96-2.72). Simply among men who indicated they were not informed of their HIV status (a small group in this study), UAI was more common with online than offline associates.

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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). Sex Partner in Wellers Hill. UAI was significantly more likely if more sex acts had happened in the venture (OR = 16.29 95 % CI 7.07-37.52 for >10 sex acts within the venture compared to only one sex act). Other factors significantly associated with UAI were group sex within the partnership, and sex-related multiple drug use within partnership.

In multivariate model 3 (Tables 4 and 5 ), also including variables concerning sexual behavior in the venture (sex-associated multiple drug use, sex frequency and partner kind), the separate effect of online dating location on UAI became somewhat stronger (though not essential) for the HIV-positive men (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 more powerful (and essential) for HIV-unaware men (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 ventures (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 place on UAI differed by HIV status, as can be seen best in Table 5 Table 5 shows the organization of online dating using three distinct reference groups, one for each HIV status. Among HIV positive guys, UAI was more common in online compared to 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-oblivious guys, UAI was more common in online when compared with offline partnerships, though not statistically significant (OR = 1.65 95 % CI 0.79-3.44).

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Characteristics of online and offline partners and ventures are revealed in Table 2 The median age of the partners was 34years (IQR 28-40). Compared to offline partners, more online 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 online partners was more often reported as understood (61.4% vs. 49.4%; P 0.001), and in online ventures, perceived HIV concordance was higher (49.0% vs. 39.8%; P 0.001). Participants reported that their on-line partners more frequently knew 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. Sex Partner Near Me Moranbah Queensland.

To be able to examine the possible mediating effect of more information on partners (including perceived HIV status) on UAI, we developed three multivariable models. In model 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 venture features (age difference, ethnic concordance, lifestyle concordance, and HIV concordance). In version 3, we adapted also for partnership sexual risk behaviour (i.e., sex-related drug use and sex frequency) and venture type (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 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-unaware men. We performed a sensitivity analysis restricted 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 lose potentially significant associations. As a rather big number of statistical evaluations were done and reported, this strategy does lead to a heightened danger of one or more false-positive organizations. Investigations were done utilizing the statistical programme STATA, version 13 (STATA Intercooled, College Station, TX, USA).

Prior to the analyses 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. of male sex partners in preceding 6months), and some were supposed to be on the causal pathway between the principal exposure of interest and outcome (age difference between participant and partner; ethnic concordance; concordance in life styles; HIV concordance; venture type; sex frequency within venture; group sex with partner; sex-associated substance use in partnership).

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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 features of participants, partners, and partnership sexual conduct by online or offline venture, and computed P values based on logistic regression with robust standard errors, accounting for related 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. Sex partner nearest Wellers Hill Queensland. Odds ratio tests were used to gauge the significance of a variable in a model.

In order to investigate possible disclosure of HIV status we additionally asked the participant whether the casual sex partner understood the HIV status of the participant, together with the reply choices: (1) no, (2) perhaps, (3) yes. Sexual behavior with each partner was dichotomised as: (1) no anal intercourse or simply protected anal intercourse, and (2) unprotected anal intercourse. To determine the subculture, we asked whether the participant characterised himself or his partners as belonging to one or more of the following subcultures/lifestyles: casual, formal, alternate, drag, leather, military, sports, fashionable, punk/skinhead, rubber/lycra, gothic, bear, jeans, skater, or, if not one of these characteristics were appropriate, other. Concordant lifestyle was categorised as: (1) concordant; (2) discordant. Casual partner type 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 are HIV infected?', with five response options: (1) I 'm certainly not HIV-infected; (2) I believe that I am not HIV-contaminated; (3) I do not know; (4) I believe I may be HIV-infected; (5) I know for sure that I 'm HIV-infected. We categorised this into HIV negative (1,2), unknown (3), and HIV positive (4,5) status. The questionnaire enquired about the HIV status of each sex partner with the question: 'Do you understand whether this partner is HIV-contaminated?' with similar reply options as above. Perceived concordance in HIV status within ventures was categorised as; (1) concordant; (2) discordant; (3) unknown. The last 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 trip to the STI outpatient clinic while waiting for preliminary test results after their consultation with a nurse or physician. The survey 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 behavior with those partners. A detailed description of the study design and also the survey is provided elsewhere 15 , 18 Our chief determinant of interest, dating location (e.g., the name of a pub, park, club, or the name of a web site) was obtained for every partner, and categorised into online (websites), and offline (physical sites) dating locations. To simplify the language of differentiating the partners per dating place, we refer to them as online 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 could comprehend written Dutch or English. People could participate more than once, if subsequent visits to the practice were related to a possible new STI episode. Sex partner near Wellers Hill, Queensland. Participants were regularly screened for STI/HIV according to the standard procedures of the STI outpatient clinic 15 , 17 The study was approved by the medical ethics committee of the Academic Medical Center of Amsterdam (MEC 07/181), and written informed consent was obtained from each participant. Sex partner near me Wellers Hill. 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.