AMC, Academic Medical Center; aOR, adjusted odds ratio; CI, confidence interval; CINIMA, Center for Infection and Immunology Amsterdam; DAG, directed acyclic graph; HIV, human immunodeficiency virus; i.e., id est, it is, 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 when it comes to fast changing dating processes as well as sero-adaptive behaviours (such as viral sorting and pre exposure prophylaxis). With every new way of dating and preventive opportunities, the rules of battles will change. Our data are 8years old and internet-based dating has developed since then. Nevertheless these results are useful, as they demonstrate how web-based partner acquisition can result in more information on the sex partner, and this may influence on the frequency of UAI.
Relationship online may offer other opportunities for communicating on HIV status than dating in physical surroundings. Sex partner nearest Atwell WA. Easing more on-line HIV status disclosure during partner seeking makes serosorting easier. Yet, serosorting may raise the weight of other STI and WOn't prevent HIV infection entirely. Sex Partner nearby Atwell. Interventions to prevent HIV transmission should particularly be directed at HIV-negative and unaware MSM and arouse timely HIV testing (i.e., after risk occasions or when experiencing symptoms of seroconversion illness) as well as regular testing when sexually active.
Because conclusions on UAI seem to be partially based on sensed HIV concordance, precise knowledge of one's own and the partner's HIV status is important. In HIV negative guys and HIV status-unaware guys, decisions on UAI will not 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 phase during which people can transmit HIV but cannot be diagnosed with the commonly used HIV tests. Consequently serosorting cannot be regarded as a very effective method of avoiding HIV transmission 22 Besides interventions to trigger the uptake of HIV and STI testing in sexually active men, interventions to warn against UAI based on sensed HIV-negative concordant status are in order, irrespective of whether this concerns online or offline dating.
For HIV-oblivious guys the effect of dating location on UAI did not change by adding partner characteristics, but it improved when adding lifestyle and drug use. It's difficult to assess the real risk for HIV for these men: do they behave as HIV-negative guys who want to protect 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 guys who were never tested for HIV, profiled themselves online as being HIV-negative, which might be problematic if they are HIV-positive and participate in UAI with HIV negative partners 12 Formerly Matser et al. reported that 1.7% of the unaware and sensed HIV-negative MSM were tested HIV positive. The study population included the MSM reported in this study 15
Online dating was not connected with UAI among HIV negative guys, a finding in agreement with some previous studies, mainly among young men 21 , but in contrast with other studies 1 - 5 This may be due to the fact that most earlier studies compared sexual behavior of two groups of MSM rather than comparing two sexual behavior patterns within one group of men. Nonetheless it may 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 not as high risk MSM now additionally make use of the Net for dating. Sex Partner near Atwell Western Australia Australia.
A vital 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 also offline casual partners. Atwell, Western Australia Sex Partner. Sex Partner Near Me Bicton Western Australia. This avoided prejudice caused by potential differences between men just dating online and those simply dating offline, a weakness of numerous previous studies. Sex partner near me Atwell Australia. By recruiting participants at the greatest STI outpatient clinic in the Netherlands we could contain a great number of MSM, and avoid 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 on-line partners than with offline associates. When adjusting for partner characteristics, the effect of online/offline dating on UAI among HIV-positive MSM became somewhat smaller and became non significant; this suggests that differences in partnership factors between online and offline partnerships are responsible for the increased UAI in online established ventures. This may be because of a mediating effect of more information on partners, (including perceived HIV status) on UAI, or to other factors. 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 associated with UAI but only important when adding partner and venture 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 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 nonsignificant association between online dating and UAI (aOR = 1.62 95 % CI 0.96-2.72). Just among guys who suggested they weren't informed of their HIV status (a little 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 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). Sex Partner near Atwell. 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 just one sex act). Other variables 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 ), additionally including variants concerning sexual behavior in the partnership (sex-associated multiple drug use, sex frequency and partner type), the independent effect of online dating place on UAI became somewhat stronger (though not critical) 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 result of online dating on UAI became stronger (and critical) for HIV-oblivious guys (aOR = 2.55 95 % CI 1.11-5.86) (Table 5 ).
In univariate analysis, UAI was significantly more inclined to occur in online 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 different reference categories, one for each HIV status. Among HIV positive men, UAI was more common in online when compared with offline ventures (OR = 1.61 95 % CI 1.03-2.50). Among HIV-negative guys no association was apparent between UAI and on-line ventures (OR = 1.07 95 % CI 0.71-1.62). Among HIV-oblivious 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).
Features of on-line 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 often reported as understood (61.4% vs. 49.4%; P 0.001), and in online partnerships, perceived HIV concordance was higher (49.0% vs. 39.8%; P 0.001). Participants reported that their on-line 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 online partners (50.9% vs. 41.3%; P 0.001). Sex-associated material use, alcohol use, and group sex were less often reported with on-line partners. Sex Partner Near Me Canning Vale Western Australia.
To be able to examine the possible mediating effect of more information on partners (including perceived HIV status) on UAI, we developed three variant 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 partnership features (age difference, ethnic concordance, lifestyle concordance, and HIV concordance). In model 3, we adjusted also for partnership sexual risk behaviour (i.e., sex-related 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 included in all three models by making a new six-class variable. For clarity, the effects of online/offline dating on UAI are also presented individually for HIV-negative, HIV-positive, and HIV-unaware men. 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 significant organizations. As a rather large number of statistical evaluations were done and reported, this approach 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).
Before the investigations 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; on-line 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 outcome (age difference between participant and partner; ethnic concordance; concordance in life styles; HIV concordance; partnership sort; 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 venture, and calculated 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 examine the association between dating place (online versus offline) and UAI. Sex partner near Atwell, Western Australia. Likelihood ratio tests were used to measure the significance of a variable in a model.
To be able to investigate possible disclosure of HIV status we additionally asked the participant whether the casual sex partner knew the HIV status of the participant, with the answer options: (1) no, (2) perhaps, (3) yes. Sexual behaviour with each partner was dichotomised as: (1) no anal intercourse or merely 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, substitute, drag, leather, military, sports, trendy, punk/skinhead, rubber/lycra, gothic, bear, jeans, skater, or, if none of these characteristics were related, other. Concordant lifestyle was categorised as: (1) concordant; (2) discordant. Chance partner type 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 'm 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 'm HIV-contaminated. We categorised this into HIV-negative (1,2), unknown (3), and HIV-positive (4,5) status. The questionnaire enquired about the HIV status of each sex partner with the question: 'Do you know whether this partner is HIV-infected?' with similar response options as above. Perceived concordance in HIV status within ventures was categorised as; (1) concordant; (2) discordant; (3) unknown. The last group 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 test results after their consultation using a nurse or doctor. 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 as well as the questionnaire is provided elsewhere 15 , 18 Our chief determinant of interest, dating location (e.g., the name of a pub, park, club, or the name of a site) was obtained for every partner, and categorised into on-line (websites), and offline (physical sites) dating locations. To simplify the terminology of distinguishing 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 might understand written Dutch or English. Individuals could participate more than once, if subsequent visits to the practice were related to a potential new STI episode. Sex Partner near Atwell Western Australia. 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. Sex partner nearest Atwell. Included in this evaluation were guys who reported sexual contact with at least one casual partner dated online as well one casual partner dated offline.