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And yet, just this week, a brand new evaluation from Michigan State University found that online dating results in fewer committed relationships than offline dating does --- that it doesn't work, in other words. That, in the words of its own author, contradicts a load of studies which have come before it. In reality, this latest proclamation on the state of modern love joins a 2010 study that found more couples meet online than at schools, bars or parties. Free sex dating closest to Athabasca. And a 2012 study that found dating site algorithms aren't powerful. And a 2013 paper that indicated Internet access is boosting marriage rates. Plus a whole host of doubtful statistics, surveys and case studies from dating giants like eHarmony and , who assert --- insist, even!! --- that online dating works."

AMC, Academic Medical Center; aOR, adjusted odds ratio; CI, confidence interval; CINIMA, Center for Infection and Immunology Amsterdam; DAG, directed acyclic graph; HIV, human immuno-deficiency virus; i.e., id est, it's, for example; IQR, interquartile range; MEC, Medical Ethics Committee; MSM, men who have sex with men; OR, odds ratio; RIVM, National Institute of Public Health and the Environment, Centre for Infectious Disease Control; STI, sexually transmitted infection; UAI, unprotected anal intercourse; UMCU, University Medical Center Utrecht

New research should remain up-to-date as it pertains to rapid shifting dating methods as well as sero-adaptive behaviours (like viral sorting and pre exposure prophylaxis). With each new way of dating and preventative opportunities, the rules of engagements will change. Our data are 8years old and web-based dating has developed since then. However these results are useful, as they show how internet-based partner acquisition can lead to more info on the sex partner, and this may influence on the frequency of UAI.

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Dating online may offer other chances for communication on HIV status than dating in physical surroundings. Facilitating more online HIV status disclosure during partner seeking makes serosorting easier. Yet, serosorting may increase the burden of other STI and WOn't prevent HIV disease entirely. Interventions to prevent HIV transmission should notably be directed at HIV-negative and unaware MSM and stimulate timely HIV testing (i.e., after risk events or when experiencing symptoms of seroconversion illness) as well as routine testing when sexually active.

Because determinations on UAI seem to be partially based on sensed HIV concordance, accurate knowledge of one's own and the partner's HIV status is essential. In HIV-negative guys and HIV status-unaware men, conclusions on UAI WOn't only be based on perceived HIV status of the partner but also on one's own negative status. HIV serosorting is challenged by the frequency of HIV testing and also the HIV window period during which individuals can transmit HIV but cannot be diagnosed with the commonly used HIV tests. Hence serosorting cannot be regarded as an extremely successful way of avoiding HIV transmission 22 Besides interventions to stimulate the uptake of HIV and STI testing in sexually active men, interventions to caution against UAI based on perceived HIV negative concordant status are in order, irrespective of whether this concerns online or offline dating.

For HIV-oblivious men the impact of dating place on UAI did not change by adding partner features, but it improved when adding lifestyle and drug use. It's difficult to evaluate the real risk for HIV for these men: do they behave as HIV negative guys who are trying to shield themselves from HIV infection, or as HIV-positive guys trying to guard their HIV-negative partner from HIV infection? A study by Horvath et al. reported that 72% of men who were never tested for HIV, profiled themselves online as being HIV negative, which might be debatable if they are HIV positive and engage in UAI with HIV negative partners 12 Formerly Matser et al. reported that 1.7% of the oblivious and sensed HIV negative MSM were tested HIV-positive. The study population included the MSM reported in this study 15

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Online dating wasn't associated with UAI among HIV-negative guys, a finding in agreement with some previous studies, mostly 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. Athabasca, Alberta free sex dating. Nonetheless it could also reflect lay changes; perhaps in the beginning of online dating a more high risk group of men used the Internet, and over time online dating normalized and less high-risk MSM now additionally use the Net for dating.

Free sex dating near me Athabasca Alberta. A vital strength of the study was that it investigated the relation between online dating and UAI among MSM who had recent sexual contact with both online and also offline casual partners. This avoided bias caused by potential differences between men just dating online and those just dating offline, a weakness of numerous previous studies. Free sex dating in Athabasca Alberta, Canada. By recruiting participants at the biggest STI outpatient clinic in the Netherlands we could comprise a high number of MSM, and prevent potential differences in guys sampled 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 often with online partners than with offline associates. Free sex dating nearest Athabasca Alberta. When correcting for associate characteristics, the effect of online/offline dating on UAI among HIV-positive MSM became somewhat smaller and became non-significant; this implies that differences in partnership variables between online and offline partnerships are accountable for the increased UAI in online established ventures. This could be due to a mediating effect of more information on associates, (including perceived HIV status) on UAI, or to other variables. Among HIV negative men no effect of online dating on UAI was observed, either in univariate or in the multivariate models. Among HIV-oblivious guys, online dating was correlated with UAI but only critical when adding associate and partnership variables to the model.

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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 risk 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 guys there was a nonsignificant association between online dating and UAI (aOR = 1.62 95 % CI 0.96-2.72). Simply among men who indicated they were not informed of their HIV status (a small 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 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 happened in the venture (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 venture (sex-related multiple drug use, sex frequency and partner kind), the independent effect of online dating place on UAI became somewhat stronger (though not essential) 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 effect of online dating on UAI became more powerful (and important) for HIV-unaware guys (aOR = 2.55 95 % CI 1.11-5.86) (Table 5 ).

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In univariate analysis, UAI was significantly more likely to happen in online than in offline ventures (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 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 different reference types, one for each HIV status. Among HIV positive guys, UAI was more common in online compared to offline partnerships (OR = 1.61 95 % CI 1.03-2.50). Among HIV-negative men no association was apparent between UAI and on-line 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).

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). Free Sex Dating nearest Athabasca. 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 often reported as understood (61.4% vs. 49.4%; P 0.001), and in on-line partnerships, 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 frequently 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 internet partners.

In order to examine the possible mediating effect of more information on partners (including perceived HIV status) on UAI, we developed three multivariable models. In model 1, we adjusted the association between online/offline dating place 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 version 3, we adapted also for partnership sexual risk behavior (i.e., sex-related drug use and sex frequency) and venture type (i.e., casual or anonymous). Athabasca Free Sex Dating. 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-class variable. Free sex dating nearest Alberta. 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 limited 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 organizations. As a fairly big number of statistical tests were done and reported, this approach does lead to an increased danger of one or more false-positive organizations. 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. 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 assumed to be on the causal pathway between the principal exposure of interest and results (age difference between participant and partner; ethnic concordance; concordance in life styles; HIV concordance; partnership type; sex frequency within partnership; group sex with partner; sex-related substance 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). We compared features of participants, partners, and venture sexual behavior by on-line or offline partnership, and computed P values predicated 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 place (online versus offline) and UAI. Odds ratio tests were used to measure the significance of a variable in a model.

As a way to explore possible disclosure of HIV status we additionally asked the participant whether the casual sex partner understood the HIV status of the participant, together with the response choices: (1) no, (2) possibly, (3) yes. Free Sex Dating near Alberta. Sexual behaviour with each partner was dichotomised as: (1) no anal intercourse or just 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 at least one of the following 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. Casual partner kind 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 answer choices: (1) I 'm certainly not HIV-contaminated; (2) I think that I am not HIV-contaminated; (3) I don't understand; (4) I think I may be HIV-infected; (5) I know for sure that I 'm HIV-contaminated. Free Sex Dating closest to Athabasca Canada. We categorised this into HIV negative (1,2), unknown (3), and HIV-positive (4,5) status. The survey enquired about the HIV status of every sex partner with all 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 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.

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