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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). 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 only one sex act). Lesbian Dating in Campbellfield, Victoria. Other factors significantly associated with UAI were group sex within the partnership, and sex-related multiple drug use within venture.

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 place 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 more powerful (and significant) for HIV-unaware guys (aOR = 2.55 95 % CI 1.11-5.86) (Table 5 ).

In univariate analysis, UAI was significantly more inclined to occur 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 impact 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 different reference categories, one for each HIV status. 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 apparent between UAI and internet ventures (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).

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Features of on-line and offline partners and partnerships are revealed 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 often knew 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 online partners (50.9% vs. 41.3%; P 0.001). Sex-related substance use, alcohol use, and group sex were less often reported with internet partners.

In order to analyze the potential mediating effect of more information on partners (including perceived HIV status) on UAI, we developed three variant models. In version 1, we adapted the association 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 venture characteristics (age difference, ethnic concordance, lifestyle concordance, and HIV concordance). In model 3, we adjusted also for partnership sexual risk behavior (i.e., sex-related drug use and sex frequency) and partnership 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 fresh 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 men. 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 lose potentially significant organizations. As a fairly large number of statistical evaluations were done and reported, this approach does lead to an elevated danger of one or more false-positive associations. Investigations were done using 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. Lesbian dating near Campbellfield, Victoria. In this model some variables 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 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-associated material use in venture).

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We compared characteristics of participants by self-reported HIV status (using 2-evaluations for dichotomous and categorical variables and using rank sum test for continuous variables). We compared characteristics of participants, partners, and partnership sexual behaviour by online or offline partnership, and computed P values based on logistic regression with robust standard errors, accounting for linked data. Continuous variables (i.e., age, amount 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 place (online versus offline) and UAI. Likelihood ratio tests were used to evaluate the importance of a variable in a model.

In order to investigate potential disclosure of HIV status we additionally asked the participant whether the casual sex partner understood the HIV status of the participant, with the reply options: (1) no, (2) possibly, (3) yes. Sexual conduct with each partner was dichotomised as: (1) no anal intercourse or merely shielded anal intercourse, and (2) unprotected anal intercourse. To determine the subculture, we asked whether the participant characterised himself or his partners as belonging to at least one of the subsequent subcultures/lifestyles: casual, formal, alternative, 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. Chance partner sort was categorised by the participants into (1) known traceable and (2) anonymous partners.

HIV status of the participant was got by asking the question 'Do you understand whether you are HIV infected?', with five response alternatives: (1) I 'm certainly not HIV-infected; (2) I think that I'm not HIV-infected; (3) I don't understand; (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 questionnaire enquired about the HIV status of every sex partner together with the question: 'Do you understand whether this partner is HIV-infected?' with similar answer options as previously. Lesbian dating near Campbellfield Victoria Australia. Perceived concordance in HIV status within partnerships was categorised as; (1) concordant; (2) discordant; (3) unknown. The last group represents all partnerships where the participant didn't know 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.

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Participants completed a standardised anonymous questionnaire throughout their visit to the STI outpatient clinic while waiting for preliminary evaluation results after their consultation with 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 information on sexual conduct with those partners. A comprehensive description of the study design and also the survey is provided elsewhere 15 , 18 Our main determinant of interest, dating location (e.g., the name of a bar, park, club, or the name of a web site) was obtained for every partner, and categorised into on-line (websites), and offline (physical sites) dating locations. To simplify the terminology of distinguishing the partners per dating location, 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 might comprehend written Dutch or English. Individuals could participate more than once, if following visits to the practice were related to a potential new STI episode. Participants were routinely 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. Included in this evaluation were guys who reported sexual contact with at least one casual partner dated online as well one casual partner dated offline.

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. 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 partly explained through better understanding of partner characteristics, including HIV status.

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A meta-analysis in 2006 found limited evidence that getting a sex partner online raises the risk of unprotected anal intercourse (UAI) 3 Many previous studies compared men with internet partners to guys with offline partners. However, men favoring online dating might differ in a variety of unmeasured respects from guys favoring offline dating, resulting in incomparable behavioural profiles. A more recent meta-analysis included several studies analyzing MSM with both online and offline acquired sex partners and found evidence for an association between UAI and online partners, which may suggest a mediating effect of more information on partners, (including perceived HIV status) on UAI 13 Lesbian Dating near me Campbellfield VIC.

Men who have sex with men (MSM) frequently utilize the Web to locate sex partners. Several studies have revealed that MSM are prone to engage in unprotected anal intercourse with sex partners they meet through the Internet (on-line) than with partners they meet at social places (offline) 1 - 3 This implies that men who get partners online may be at a higher risk for sexually transmitted infections (STI) and HIV 4 - 6 Although higher rates of UAI are reported with on-line partners, the danger of HIV transmission also depends on accurate knowledge of one's own and the sex partners' HIV status 7 - 10

Five hundred seventy-seven men (351 HIV negative, 153 HIV-positive, and 73 HIV-unaware) reported UAI in 26% of 878 on-line, and 23% of 903 offline casual partnerships. The crude OR of online dating for UAI was 1.36 (95 % CI 1.03-1.81). HIV positive men were more likely to report UAI than HIV negative men (49% vs. 28% of ventures). Corrected for demographic characteristics, online dating had no important effect on UAI among HIV-negative and HIV status-oblivious guys, but HIV-positive men were more likely to have UAI with online partners (aOR = 1.65 95 % CI 1.05-2.57). After correction for partner and partnership features the effect of online/offline dating on UAI among HIV positive MSM was reduced and no longer significant.

Believe it or not, I didn't come out of this experiment feeling terrible about myself---just smarter about the way gay men (or perhaps men in general) area way too much emphasis on silly characteristics like beards and ballcaps (hint: that is why you are all still cranky and single). And really, I really don't believe having long hair itself is the big hang up; it's what my hair implies. Having long hair (especially for a black man) means you are likely a bitchy spectacular queen that nobody wants to date. Lesbian Dating nearest Campbellfield VIC. Even if the assumption isn't that extreme, the inherent fear is you spent too much time on your look and that is not masculine." That is frustrating, obviously, since stereotypical masculinity takes just as much work---we just do not think of it that way. I recall chatting with this scruffy, fairly muscular man with tattoos and chest hair and an Instagram full of masc pics; after we got to talking, he revealed his obsession with Beyonc and said yasss!" every other paragraph. But no matter---his graphic is butch, so his dating life is constantly full.

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