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 guys this lack 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). Only among men who indicated they were not aware of their HIV status (a small group in this study), UAI was more common with online than offline associates. Sluts near Red Hill, New South Wales.
The number of sex partners in the preceding 6months of the index was also 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 partnership compared to just 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 ), 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 location on UAI became somewhat more powerful (though not significant) 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 important) for HIV-unaware men (aOR = 2.55 95 % CI 1.11-5.86) (Table 5 ). Sluts in Red Hill.
In univariate analysis, UAI was significantly more prone to happen in on-line than in offline partnerships (OR = 1.36 95 % CI 1.03-1.81) (Table 4 ). The self-perceived HIV status of the participant was strongly 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 organization of online dating using three distinct reference types, one for each HIV status. Among HIV-positive men, 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 on-line 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).
Sluts nearest NSW. Characteristics of online and offline partners and partnerships 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 frequently 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 online partners more often 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 internet partners (50.9% vs. 41.3%; P 0.001). Sex-related material use, alcohol use, and group sex were less frequently reported with online partners.
In order to analyze the potential mediating effect of more info on partners (including perceived HIV status) on UAI, we developed three multivariable models. In model 1, we adjusted the organization between online/offline dating place 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 version 3, we adapted also for partnership sexual risk behaviour (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 place was included in all three models by making a 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 restricted to partnerships in which only 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 rather big number of statistical tests were done and reported, this strategy does lead to an elevated risk of one or more false-positive associations. Evaluations were done using the statistical programme STATA, version 13 (STATA Intercooled, College Station, TX, USA). Sluts near Red Hill.
Sluts in Red Hill. 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 primary 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 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 features of participants, partners, and partnership sexual behaviour by on-line or offline venture, and computed P values predicated 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 examine the association between dating location (online versus offline) and UAI. Likelihood ratio tests were used to measure the value of a variable in a model.
To be able to explore 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 alternatives: (1) no, (2) possibly, (3) yes. New South Wales sluts. Sexual behavior with each partner was dichotomised as: (1) no anal intercourse or merely protected anal intercourse, and (2) unprotected anal intercourse. To determine 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, alternative, drag, leather, military, sports, trendy, punk/skinhead, rubber/lycra, gothic, bear, jeans, skater, or, if none of these features were applicable, 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 got by asking the question 'Do you know whether you're HIV infected?', with five response choices: (1) I 'm definitely not HIV-infected; (2) I believe that I'm not HIV-infected; (3) I do not know; (4) I believe 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. Red Hill NSW sluts. The survey enquired about the HIV status of every sex partner with all the question: 'Do you understand whether this partner is HIV-infected?' with similar response alternatives as above. 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 did not 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.
Participants completed a standardised anonymous questionnaire during their visit to the STI outpatient clinic while waiting for preliminary evaluation results after their consultation using a nurse or doctor. Sluts closest to Red Hill New South Wales. 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 detailed description of the study design and the survey is provided 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 online (websites), and offline (physical sites) dating places. To simplify the language of differentiating 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 could comprehend written Dutch or English. Individuals could participate more than once, if following visits to the clinic were related to a possible 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 evaluation were guys who reported sexual contact with at least one casual partner dated online as well one casual partner dated offline. Sluts nearest Red Hill Australia.
With increased acquaintance in sexual partnerships, for example by concordant ethnicity, age, lifestyle, HIV status, and raising sex frequency, the chances for UAI increase as well 14 - 16 We compared the incidence of UAI in online got casual partnerships to that in offline obtained casual partnerships among MSM who reported both online and offline casual partners in the preceding six months. Sluts near Red Hill New South Wales. 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 described through better understanding of partner features, including HIV status.
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