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 is, 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 accelerated altering dating approaches and sero-adaptive behaviours (like viral sorting and pre exposure prophylaxis). With each new way of dating and preventive opportunities, the rules of battles will vary. Our data are 8years old and net-based dating has developed since then. Yet these results are useful, as they show how web-based partner acquisition can lead to more information on the sex partner, and this may affect on the frequency of UAI.
Dating online may offer other opportunities for communicating on HIV status than dating in physical surroundings. Sex Partner near me Gladstone NSW. Facilitating more online HIV status disclosure during partner seeking makes serosorting easier. However, serosorting may increase the weight of other STI and will not prevent HIV disease entirely. Sex Partner in Gladstone. Interventions to prevent HIV transmission should notably be directed at HIV-negative and unaware MSM and stimulate timely HIV testing (i.e., after risk events or when experiencing symptoms of seroconversion illness) as well as regular testing when sexually active.
Because conclusions on UAI seem 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 men and HIV status-oblivious guys, judgements 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 the HIV window period during which people can transmit HIV but cannot be diagnosed with the commonly used HIV tests. Consequently serosorting can't be regarded as an extremely powerful way of avoiding HIV transmission 22 Besides interventions to stimulate the uptake of HIV and STI testing in sexually active men, interventions to caution against UAI based on sensed HIV negative concordant status are in order, irrespective of whether this concerns online or offline dating.
For HIV-unaware guys the impact of dating location on UAI did not change by adding partner features, but it increased when adding lifestyle and drug use. It is hard to assess the real risk for HIV for these men: do they act as HIV negative guys that are attempting to protect themselves from HIV infection, or as HIV positive guys attempting to guard 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 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 analyzed HIV positive. The study population comprised the MSM reported in this study 15
Online dating was not correlated 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 due to the reality that most earlier studies compared sexual behaviour of two groups of MSM rather than comparing two sexual behavior patterns within one group of men. Yet it can 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 less high-risk MSM now also make use of the Internet for dating. Sex partner closest to Gladstone New South Wales Australia.
An integral strength of the 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. Gladstone New South Wales Sex Partner. Sex Partner Near Me Emu Plains New South Wales. This avoided prejudice caused by potential differences between guys only dating online and those just dating offline, a weakness of numerous previous studies. Sex partner closest to Gladstone, Australia. By recruiting participants at the greatest STI outpatient clinic in the Netherlands we could comprise a lot of MSM, and prevent potential differences in guys tried through Internet or face-to-face interviewing, weaknesses in some previous studies 3 , 11
Among HIV positive men, in univariate analysis UAI was reported significantly more frequently with on-line associates than with offline associates. When correcting for partner 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 responsible for the increased UAI in online established ventures. This could be because of a mediating effect of more info on associates, (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 guys, online dating was associated with UAI but just critical when adding associate and venture 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 danger of UAI than offline dating. For HIV negative guys this dearth of assocation was clear (aOR = 0.94 95 % CI 0.59-1.48); among HIV-positive men there was a non significant association between online dating and UAI (aOR = 1.62 95 % CI 0.96-2.72). Only among men who indicated they were not aware of their HIV status (a little group in this study), UAI was more common with online than offline associates.
The number of sex partners in the preceding 6months of the index was also 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 Gladstone. 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 venture compared to just 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 ), additionally including variants concerning sexual behavior in the partnership (sex-associated multiple drug use, sex frequency and partner kind), the separate effect of online dating location 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 result of online dating on UAI became more powerful (and critical) for HIV-oblivious 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 ventures (OR = 1.36 95 % CI 1.03-1.81) (Table 4 ). The self-perceived HIV status of the participant was firmly correlated with UAI (OR = 11.70 95 % CI 7.40-18.45). The effect 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 different reference groups, one for each HIV status. Among HIV-positive men, UAI was more common in online in comparison to offline partnerships (OR = 1.61 95 % CI 1.03-2.50). Among HIV-negative guys no association was apparent between UAI and on-line ventures (OR = 1.07 95 % CI 0.71-1.62). Among HIV-unaware men, UAI was more common in online when compared with offline ventures, though not statistically significant (OR = 1.65 95 % CI 0.79-3.44).
Features of on-line 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 online partners was more often reported as understood (61.4% vs. 49.4%; P 0.001), and in on-line ventures, perceived HIV concordance was higher (49.0% vs. 39.8%; P 0.001). Participants reported that their on-line partners more frequently understood the HIV status of the participant than offline partners (38.8% vs. 27.2%; P 0.001). Participants more frequently reported multiple sexual contacts with internet partners (50.9% vs. 41.3%; P 0.001). Sex-associated material use, alcohol use, and group sex were less often reported with online partners. Sex Partner Near Me Austral New South Wales.
To be able to analyze the potential mediating effect of more information on partners (including perceived HIV status) on UAI, we developed three multivariable models. In model 1, we adjusted the organization between online/offline dating location and UAI for features 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 features (age difference, ethnic concordance, lifestyle concordance, and HIV concordance). In model 3, we adjusted additionally for venture sexual risk behavior (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 location was included in all three models by making a fresh 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 men. We performed a sensitivity analysis limited 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 organizations. As a rather large number of statistical tests were done and reported, this approach does lead to an increased danger of one or more false positive organizations. Analyses were done using the statistical programme STATA, version 13 (STATA Intercooled, College Station, TX, USA).
Before 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; online partner acquisition), others were considered as confounders (participants' age, participants' ethnicity, and no. of male sex partners in preceding 6months), and some were assumed to be on the causal pathway between the primary 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-related substance use in partnership).
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 venture sexual behavior by on-line or offline venture, and computed P values predicated 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 analyze the association between dating location (online versus offline) and UAI. Sex partner nearest Gladstone, New South Wales. Likelihood ratio tests were used to assess the significance of a variable in a model.
As a way to investigate potential disclosure of HIV status we additionally asked the participant whether the casual sex partner knew the HIV status of the participant, together with the reply options: (1) no, (2) possibly, (3) yes. Sexual behaviour with each partner was dichotomised as: (1) no anal intercourse or just shielded anal intercourse, and (2) unprotected anal intercourse. To discover 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, substitute, drag, leather, military, sports, trendy, punk/skinhead, rubber/lycra, gothic, bear, jeans, skater, or, if not one of these features were related, 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 know whether you're HIV infected?', with five response alternatives: (1) I 'm definitely not HIV-contaminated; (2) I think that I'm not HIV-contaminated; (3) I don't understand; (4) I think I may be HIV-infected; (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 understand whether this partner is HIV-contaminated?' with similar response choices as above. Perceived concordance in HIV status within ventures was categorised as; (1) concordant; (2) discordant; (3) unknown. The final category 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 throughout their trip to the STI outpatient clinic while waiting for preliminary evaluation results after their consultation with a nurse or doctor. The survey elicited information on socio-demographics and HIV status of the participant, the three most recent partners in the preceding six months, and information on sexual conduct with those partners. A thorough description of the study design as well as the survey is provided elsewhere 15 , 18 Our chief determinant of interest, dating place (e.g., the name of a pub, park, club, or the name of a site) was obtained for every partner, and categorised into online (websites), and offline (physical sites) dating places. To simplify the terminology 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 could comprehend written Dutch or English. People could participate more than once, if subsequent visits to the practice were related to a potential new STI episode. Sex partner near me Gladstone New South Wales. Participants were routinely 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. Sex partner closest to Gladstone. Included in this investigation were guys who reported sexual contact with at least one casual partner dated online as well one casual partner dated offline.