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Slip Opinions: This contains clickable hypertext links to read, search, and copy the full text of N. Supreme Court and N. The also has links to court s in the contiguous states, plus links to read, search, and copy the full text of both U. Supreme Court decisions and the U. We have tried to include every precedent-setting case from January 1, to present. We also included selected slip opinions from and


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Dating apps are a novel means of delivering HIV prevention messages. We analyzed testing behaviors of YBSMM, comparing typical testing frequency between app users and non-users using odds ratios. Overall, testing rates were high. App users were more likely than non-users to test at least every 12 months. App-using YBSMM exhibit high compliance with testing guidelines, which may indicate future successful uptake of biomedical preventions, such as Pre-Exposure Prophylaxis. HIV incidence is also highest among young persons, with incidence rates of 14, perindividuals age in N. Despite the lack of firm correlations between risk behaviors and sex-seeking via apps, there is benefit to frequent HIV testing among young Black SMM YBSMM who use apps, and mHealth interventions therefore often target this population.

Hightow-Weidman et al.

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A more complete understanding of testing behaviors is needed to inform the development of tailored prevention interventions for maximum efficacy Oster et al. Routine HIV testing is essential to the diagnosis and early initiation of antiretroviral therapy Workowski, But studies of risk-taking with sex partners met on the Internet and via apps report mixed. For example, a review by Francisco Luz Nunes Queiroz et al found several studies identified high frequency of condomless anal sex CAS with partners met via apps Francisco Luz Nunes Queiroz, et al.

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The same review also found several studies that showed frequent partner changing among app-using MSM. Other studies show the opposite; SMM who use apps to find sex partners are more likely to use condoms than those SMM who find sex partners in other venues Rice E et al. We based this hypothesis on the data that show app users to be more likely to use sexual health resources Macapagal et al. YBSMM who had a mobile device with Internet access who met the following risk criteria in the past six months were eligible: CAS with a male partner, any anal sex with more than three male partners, exchange of money, gifts, shelter, or drugs for anal sex with male partner, or anal sex while under the influence of drugs or alcohol.

Additional details regarding the parent study have been published Cary NC parsons dating, et al. Participants completed a baseline survey and follow-up assessments at three, six and twelve-months post enrollment. Baseline data were used in our study for a cross-sectional study de. The parent study and this secondary analysis were both approved by the University of North Carolina Institutional Review Board. The study exposure was defined as searching for a sex partner on any app within the past three months, including both apps specifically deed for finding romantic and sex partners as well as social networking apps that can also be used for other purposes.

The covariates identified were age, having health insurance, having a college degree, being single, having an HIV-positive partner, recent diagnosis of an STI, of sex partners, engaging in transactional sex, and having a higher perceived risk of HIV, all reported for the prior three months.

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Perceived HIV risk was measured using a validated scale as a score ranging from 4 to 20 lowest to highest perceived risk based on the combined responses to four statements with 5-point Likert scales DeHart and Birkimer, Study measures and definitions are further detailed in Supplemental Table 1. In sensitivity analyses, we examined the impact of using six months rather than 12 as a threshold of testing frequency, and using other HIV testing survey questions.

We compared demographic characteristics and survey responses of app users and non-users using chi square and Kruskal-Wallis tests. For the primary outcome and sensitivity analyses, we used logistic regression to estimate odds ratios OR comparing app users and non-users, unadjusted, and adjusted for all confounders listed above.

In the sensitivity analysis examining the of HIV tests in the past year, Poisson regression was used instead. SAS Software v. A higher of app users also reported having engaged in transactional sex 9. Reported HIV testing frequency using four instruments among all participants and stratified by app use.

In unadjusted analyses, app users were more likely than non app users to get tested at least every 12 months, with an OR of 2.

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In adjusted models, app users had 2. When using a threshold of testing every six months or more often, app users still had higher odds of testing more frequently, with an adjusted OR of 2. In adjusted analyses, other factors associated with testing at least every 12 months were older age OR per 1-year increase 1.

We conducted sensitivity analyses using last HIV test instead of typical testing frequency and obtained similar .

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When using a threshold of testing every 6 months or more often, app users were more likely to test more frequently, with an unadjusted OR of 1. Using a month threshold, the unadjusted OR was 2. Using multivariable Poisson regression with the of HIV tests in the past year as outcome, app users had 1.

In a sensitivity analysis, additionally adjusting for being in school, employed status, low income, and homelessness, the adjusted OR for app use was 2. Almost all participants had ly been tested for HIV, and two-thirds reported getting tested at least every 6 months.

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Participants who reported seeking sex partners online via apps in the prior 3 months reported getting tested for HIV more frequently than non-app users. These findings were consistent across four separate survey items about typical and actual HIV testing behaviors. This may be a consequence of selection bias; those YBSMM who chose to participate in a study addressing HIV risk behaviors may be more likely to test than those who did not choose to participate.

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However, none of these studies compared app users to non-users. One prior study specifically investigated the relationship between seeking sex via apps and HIV testing among young SMM Macapagal, et al. Macapagal et al found that app use was associated with higher perceived risk among adolescent SMM Macapagal, et al. Our data similarly demonstrate that these individuals exhibit higher frequency of testing than non-users, have a higher perceived risk of HIV, and a higher of sex partners, suggesting better HIV risk protection self-efficacy among app users than non-users.

Increased testing and knowledge of HIV prevention strategies among YBSMM app users may be a reflection of increasing mobile sexual health campaigns in recent years Macapagal, et al. Consistent with these studies, our study shows that app users are willing and able to access HIV prevention services, further demonstrating that mobile app prevention approaches have a high potential among YBSMM. The most common reasons for not testing included low risk perception and fear of HIV diagnosis.

Cary NC parsons dating of promoting testing based on individual risk behaviors, and simple provision of risk reduction information, interventions should focus on normalizing HIV testing as part of routine health care. While our population was small, it is possible that the reason they did not test was related to low perceived HIV risk, but we did not find a ificant relationship by comparing perceived risk with testing frequency directly. We did not examine the drivers of risk perception further in our study.

In our study, older age and having insurance were associated with testing at least every 12 months.

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These findings underscore the importance of providing YBSMM with information on where to access free sexual health services. This study has several limitations. A small sample size led to some estimates with wide confidence intervals in our analysis. Further, individuals with higher self-perceived HIV risk may have been more willing to participate in the parent study. However, a survey Jones et al. Data on the use of PrEP was not available in this study, but uptake was extremely limited in this population at the time of the study King et al.

Finally, self-reported measures may be subject to social desirability bias, though the use of computer-assisted self-interviewing has been shown to reduce bias substantially Turner et al. These findings have implications for the scale-up of PrEP, as participants with HIV risk factors who adhere to routine sexual health screenings may be ideal candidates for this prevention intervention. These behaviors may be an indicator of future successful uptake of biomedical prevention strategies, such as Pre-Exposure Prophylaxis.

National Center for Biotechnology InformationU. Author manuscript; available in PMC May 5. Lina Rosengren. Lisa B. Author information Copyright and information Disclaimer. Copyright notice. Associated Data Supplementary Materials.

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Abstract Dating apps are a novel means of delivering HIV prevention messages. Methods HealthMpowerment. Study measures The study exposure was defined as searching for a sex partner on any app within the past three months, including both apps specifically deed for finding romantic and sex partners as well as social networking apps that can also be used for other purposes. Table 1.

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Study population demographics overall and stratified by app use. Open in a separate window. Bolded estimates are statistically ificant. Table 2. Median IQR 2 2 2 Table 3. Factors associated with reported HIV testing frequency every 12 months or more often. Declaration of interest statement The authors have no conflicts of interest to disclose. Right and Mr. Right Now: romantic and casual partner-seeking online among young men who have sex with men. AIDS Behav15 2pp.

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AIDS Behavdoi J Acquir Immune Defic Syndr80 2pp.