For HIV-unaware guys the impact of dating location on UAI did not change by adding partner characteristics, but it improved when adding lifestyle and drug use. It is hard to assess the actual risk for HIV for these guys: do they act as HIV-negative men that want to shield themselves from HIV infection, or as HIV positive guys trying to safeguard their HIV-negative partner from HIV infection? A study by Horvath et al. Sluts near Queensland. 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 participate in UAI with HIV negative partners 12 Formerly 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 wasn't connected 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 because of 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. Nonetheless it can also reflect lay 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 not as high risk MSM now also make use of the Web for dating.
A key 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 offline casual partners. Sluts closest to QLD. This prevented prejudice due to potential differences between guys only dating online and those only dating offline, a weakness of several previous studies. By recruiting participants at the largest STI outpatient clinic in the Netherlands we could include a lot of MSM, and prevent potential differences in men sampled through Internet or face to face interviewing, weaknesses in certain previous studies 3 , 11
Among HIV-positive guys, in univariate analysis UAI was reported significantly more frequently with online partners 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 nonsignificant; this suggests that differences in partnership variables between online and offline partnerships are accountable for the increased UAI in online established partnerships. This could be due to a mediating effect of more info on partners, (including perceived HIV status) on UAI, or to other factors. Among HIV-negative guys no effect of online dating on UAI was found, either in univariate or in some of the multivariate models. Among HIV-unaware men, online dating was connected with UAI but only critical 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 associated with a higher risk 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 guys there was a non-significant association between online dating and UAI (aOR = 1.62 95 % CI 0.96-2.72). Windsor Queensland sluts. Only among men who suggested they weren't informed of their HIV status (a small group in this study), UAI was more common with on-line than offline partners.
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). Other factors significantly associated with UAI were group sex within the partnership, and sex-connected multiple drug use within partnership.
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 separate effect of online dating location on UAI became somewhat more powerful (though not essential) for the HIV-positive men (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 effect of online dating on UAI became more powerful (and significant) for HIV-oblivious men (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 connected 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 classes, 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 ventures (OR = 1.07 95 % CI 0.71-1.62). Among HIV-unaware guys, UAI was more common in online compared 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 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 known (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 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-related material use, alcohol use, and group sex were less often reported with on-line partners.
To be able to analyze the potential mediating effect of more information on partners (including perceived HIV status) on UAI, we developed three variant models. In model 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 partnership characteristics (age difference, ethnic concordance, lifestyle concordance, and HIV concordance). In model 3, we adjusted also for venture sexual risk behavior (i.e., sex-related drug use and sex frequency) and partnership 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-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. Sluts in Windsor, QLD. 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 fairly big number of statistical evaluations were done and reported, this approach does lead to a higher danger of one or more false positive associations. Investigations were done using the statistical programme STATA, version 13 (STATA Intercooled, College Station, TX, USA).
Prior to the investigations 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. Windsor, Queensland Sluts. Sluts Near Me Annandale Queensland. of male sex partners in preceding 6months), and some were presumed to be on the causal pathway between the main exposure of interest and outcome (age difference between participant and partner; ethnic concordance; concordance in life styles; HIV concordance; venture type; sex frequency within partnership; group sex with partner; sex-associated substance use in venture).
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 venture, and calculated P values based on logistic regression with robust standard errors, accounting for related 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 examine the association between dating location (online versus offline) and UAI. Odds ratio tests were used to evaluate the value of a variable in a model.
As a way to explore 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 answer choices: (1) no, (2) maybe, (3) yes. Sexual conduct with each partner was dichotomised as: (1) no anal intercourse or only 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 subsequent subcultures/lifestyles: casual, formal, alternate, drag, leather, military, sports, fashionable, punk/skinhead, rubber/lycra, gothic, bear, jeans, skater, or, if not one of these features were applicable, other. Windsor QLD sluts. Concordant lifestyle was categorised as: (1) concordant; (2) discordant. Accidental partner type 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're HIV infected?', with five response options: (1) I 'm definitely not HIV-contaminated; (2) I believe that I'm not HIV-infected; (3) I don't know; (4) I believe I may be HIV-contaminated; (5) I know for sure that I am 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 every sex partner with the question: 'Do you understand whether this partner is HIV-contaminated?' with similar reply alternatives as previously. Perceived concordance in HIV status within partnerships was categorised as; (1) concordant; (2) discordant; (3) unknown. The last class represents all partnerships where the participant did not 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 visit to the STI outpatient clinic while waiting for preliminary evaluation results after their consultation with a nurse or physician. 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 conduct with those partners. A thorough description of the study design as well as the questionnaire is supplied elsewhere 15 , 18 Our primary determinant of interest, dating location (e.g., the name of a pub, park, club, or the name of a website) was obtained for every partner, and categorised into online (websites), and offline (physical sites) dating places. 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 could 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. Contained in this analysis were guys who reported sexual contact with at least one casual partner dated online as well one casual partner dated offline. Sluts Near Me St Kilda Queensland.
With increased familiarity in sexual partnerships, for example by concordant ethnicity, age, lifestyle, HIV status, and increasing sex frequency, the likelihood for UAI increase as well 14 - 16 We compared the incidence of UAI in online acquired casual partnerships to that in offline got casual partnerships among MSM who reported both online and offline casual partners in the preceding six months. Sluts closest to Queensland. We hypothesised that MSM who date sex partners both online and offline, report more UAI with the casual partners they date online, and that this effect is partly explained through better knowledge of partner features, including HIV status.