An integral strength of this study was that it explored the relation between online dating and UAI among MSM who had recent sexual contact with both online and offline casual partners. Sluts nearby Macleod VIC. This averted bias caused by potential differences between guys only dating online and those only dating offline, a weakness of numerous previous studies. By recruiting participants at the largest STI outpatient clinic in the Netherlands we could comprise a high number of MSM, and avoid potential differences in men tried through Internet or face to face interviewing, weaknesses in some previous studies 3 , 11
Among HIV-positive guys, in univariate analysis UAI was reported significantly more frequently with on-line partners than with offline partners. 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 also offline partnerships are accountable for the increased UAI in online established ventures. This may be because of a mediating effect of more info on partners, (including perceived HIV status) on UAI, or to other variables. Among HIV negative men no effect of online dating on UAI was detected, either in univariate or in any of the multivariate models. Among HIV-oblivious guys, online dating was correlated 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 evidence that online dating was independently associated with a higher danger 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 men there was a nonsignificant association between online dating and UAI (aOR = 1.62 95 % CI 0.96-2.72). Only among men who indicated they weren't informed of their HIV status (a little group in this study), UAI was more common with on-line than offline associates.
The number of sex partners in the preceding 6months of the index was also associated 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). Macleod sluts. 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 partnership compared to just one sex act). Macleod, VIC sluts. Other variables significantly associated with UAI were group sex within the venture, and sex-related multiple drug use within venture.
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 place on UAI became somewhat more powerful (though not critical) 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 result of online dating on UAI became stronger (and significant) for HIV-unaware guys (aOR = 2.55 95 % CI 1.11-5.86) (Table 5 ).
In univariate analysis, UAI was significantly more likely 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 distinct reference groups, one for each HIV status. Among HIV-positive guys, UAI was more common in online in comparison to offline ventures (OR = 1.61 95 % CI 1.03-2.50). Among HIV negative guys no association was apparent between UAI and internet partnerships (OR = 1.07 95 % CI 0.71-1.62). Among HIV-oblivious 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 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 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 online partners more often 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 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 possible mediating effect of more information on partners (including perceived HIV status) on UAI, we developed three multivariable models. In version 1, we adapted the association 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 venture features (age difference, ethnic concordance, lifestyle concordance, and HIV concordance). In model 3, we adapted also for partnership sexual risk behavior (i.e., sex-associated drug use and sex frequency) and partnership kind (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 location was contained 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 separately for HIV negative, HIV-positive, and HIV-oblivious men. We performed a sensitivity analysis restricted to partnerships in which only one sexual contact occurred. Statistical significance was defined as P 0.05. Macleod Victoria, Australia Sluts. No adjustments for multiple comparisons were made, in order not to miss potentially important organizations. As a rather large number of statistical tests were done and reported, this strategy does lead to an elevated danger of one or more false positive organizations. 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 variables 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 principal exposure of interest and result (age difference between participant and partner; ethnic concordance; concordance in life styles; HIV concordance; venture sort; sex frequency within venture; group sex with partner; sex-related material use in partnership).
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). Sluts Near Me Cremorne Victoria. We compared characteristics of participants, partners, and partnership sexual behaviour by on-line or offline partnership, 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 place (online versus offline) and UAI. Likelihood ratio tests were used to assess the importance of a variable in a model.
In order to explore possible disclosure of HIV status we also asked the participant whether the casual sex partner knew the HIV status of the participant, with the response options: (1) no, (2) maybe, (3) yes. Sexual behaviour with each partner was dichotomised as: (1) no anal intercourse or just shielded anal intercourse, and (2) unprotected anal intercourse. Sluts Near Me Boronia Victoria. To ascertain 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, substitute, drag, leather, military, sports, fashionable, punk/skinhead, rubber/lycra, gothic, bear, jeans, skater, or, if not one of these features 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 obtained by asking the question 'Do you understand whether you are HIV infected?', with five response options: (1) I am certainly not HIV-contaminated; (2) I think that I'm not HIV-infected; (3) I don't understand; (4) I think I may be HIV-infected; (5) I know for sure that I 'm HIV-infected. Macleod, VIC, Australia Sluts. 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 all the question: 'Do you know whether this partner is HIV-infected?' with similar answer choices as previously. Perceived concordance in HIV status within partnerships 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 survey throughout their visit to the STI outpatient clinic while waiting for preliminary test 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. Sluts near me Macleod, VIC Australia. A thorough description of the study design and the survey is supplied elsewhere 15 , 18 Our chief determinant of interest, dating place (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 language of distinguishing 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 may understand written Dutch or English. Individuals could participate more than once, if subsequent visits to the practice were related to a possible 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 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 investigation were men 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 incidence of UAI in online acquired casual partnerships to that in offline got casual partnerships among MSM who reported both on-line 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 online, and that this effect is partially described through better understanding of partner characteristics, including HIV status.
A meta-analysis in 2006 found limited evidence that acquiring a sex partner online raises the risk of unprotected anal intercourse (UAI) 3 Many previous studies compared guys with online partners to men with offline partners. Nonetheless, men favoring online dating might differ in a variety of unmeasured respects from guys preferring offline dating, resulting in incomparable behavioural profiles. A more recent meta-analysis included several studies analyzing MSM with both online and also offline acquired sex partners and found evidence for an association between UAI and online partners, which would indicate a mediating effect of more information on partners, (including perceived HIV status) on UAI 13
Men who have sex with men (MSM) often make use of the Web to discover sex partners. Sluts nearest Victoria. Several studies have revealed that MSM are more prone to participate in unprotected anal intercourse with sex partners they meet through the Internet (online) than with partners they meet at social venues (offline) 1 - 3 This implies that men who acquire 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 risk of HIV transmission also depends on exact knowledge of one's own and the sex partners' HIV status 7 - 10