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 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 men there was a non significant association between online dating and UAI (aOR = 1.62 95 % CI 0.96-2.72). Only among guys who indicated they were not aware of their HIV status (a small group in this study), UAI was more common with on-line than offline associates. Sluts nearest Albert Park South Australia.
The amount of sex partners in the preceding 6months of the index was likewise correlated 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 occurred 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 venture, and sex-related multiple drug use within venture.
In multivariate model 3 (Tables 4 and 5 ), additionally including variants 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 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 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 ). Sluts nearby Albert Park.
In univariate analysis, UAI was significantly more prone 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 associated 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 association of online dating using three distinct reference categories, 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 men no association was evident between UAI and internet ventures (OR = 1.07 95 % CI 0.71-1.62). Among HIV-unaware men, UAI was more common in online when compared with offline partnerships, though not statistically significant (OR = 1.65 95 % CI 0.79-3.44).
Sluts near me SA. Features of online 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 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 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 understood 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 internet partners (50.9% vs. 41.3%; P 0.001). Sex-associated material use, alcohol use, and group sex were less often reported with internet partners.
In order to examine 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 adapted additionally for venture sexual risk behavior (i.e., sex-associated 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 location was contained 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 separately for HIV-negative, HIV positive, and HIV-unaware guys. 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 miss potentially important associations. As a fairly big number of statistical tests were done and reported, this strategy does lead to an increased danger of one or more false positive associations. Investigations were done utilizing the statistical programme STATA, version 13 (STATA Intercooled, College Station, TX, USA). Sluts near Albert Park.
Sluts nearby Albert Park. 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. of male sex partners in preceding 6months), and some were presumed to be on the causal pathway between the primary exposure of interest and result (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).
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 features of participants, partners, and partnership sexual behaviour by on-line or offline venture, and calculated 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 analyze the association between dating location (online versus offline) and UAI. Odds ratio tests were used to evaluate the importance of a variable in a model.
In order to explore potential 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. South Australia sluts. Sexual behavior with each partner was dichotomised as: (1) no anal intercourse or simply protected anal intercourse, and (2) unprotected anal intercourse. To ascertain 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 related, 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 know whether you're HIV infected?', with five response alternatives: (1) I am certainly not HIV-contaminated; (2) I believe that I'm not HIV-contaminated; (3) I do not understand; (4) I think I may be HIV-infected; (5) I know for sure that I am HIV-contaminated. We categorised this into HIV-negative (1,2), unknown (3), and HIV-positive (4,5) status. Albert Park, SA Sluts. The survey enquired about the HIV status of each sex partner with the question: 'Do you know whether this partner is HIV-infected?' with similar answer choices as above. 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 during their trip to the STI outpatient clinic while waiting for preliminary test results after their consultation using a nurse or doctor. Sluts nearby Albert Park South Australia. 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 behaviour with those partners. A thorough description of the study design and also the questionnaire 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 site) was obtained for every partner, and categorised into on-line (websites), and offline (physical sites) dating places. To simplify the terminology of differentiating 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 understand written Dutch or English. Individuals could participate more than once, if following visits to the clinic 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 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 men who reported sexual contact with at least one casual partner dated online as well one casual partner dated offline. Sluts near me Albert Park Australia.
With increased acquaintance in sexual partnerships, for example by concordant ethnicity, age, lifestyle, HIV status, and increasing sex frequency, the chances for UAI increase as well 14 - 16 We compared the incidence of UAI in online acquired casual partnerships to that in offline obtained casual partnerships among MSM who reported both on-line and offline casual partners in the preceding six months. Sluts near me Albert Park South Australia. 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 described through better understanding of partner characteristics, including HIV status.
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