Geosocial networking apps have made sexual partner-seeking easier for men who have sex with men, raising both challenges and opportunities for human immunodeficiency virus and sexually transmitted infection prevention and research. Most studies on men who have sex with men geosocial networking app use have been conducted in large urban areas, despite research indicating similar patterns of online- and app-based sex-seeking among men who have sex with men in rural and midsize cities.
The goal of our research was to examine the spatial distribution of geosocial networking app usage and characterize areas with increasing s of partner-seeking men who have sex with men in a midsize city in the South. At each point, staff logged into 3 different geosocial networking apps to record the of geosocial networking app users within a 1-mile radius.
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Empirical Bayesian kriging was used to create a raster estimating the of app users throughout the county. Raster values were summarized for each of the county's Census block groups and used as the outcome measure ie, geosocial networking app usage. Negative binomial regression and Wilcoxon ed rank sum tests were used to examine Census block group variables eg, median income, median age associated with geosocial networking app usage and temporal differences in app usage, respectively.
The of geosocial networking app users within a 1-mile radius of the data collection points ranged from 0 to 36 during weekday daytime hours and 0 to 39 during weekend nighttime hours. In adjusted analyses, Census block group median income and percent Hispanic ethnicity were negatively associated with geosocial networking app usage for all 3 geosocial networking apps during weekday daytime and weekend nighttime hours. Population density and the presence of businesses were positively associated with geosocial networking app usage for all 3 geosocial networking apps during both times.
In this midsize city, geosocial networking app usage was highest in areas that were more population-dense, were lower income, and had more businesses.
HIV in the United States continues to disproportionately affect men who have sex with men MSM despite ongoing prevention measures taken by public health officials [ 1 ]. HIV and sexually transmitted infection research and intervention among MSM increasingly has focused on the social environment where risk behavior occurs [ sex - 5 ], particularly as more MSM are using Web-based tools or mobile phone geosocial networking GSN apps eg, Grindr, Hornet, Adam4Adam, Scruff, etc to meet sex partners [ 6 ].
GSN apps provide information on geographic proximity between users making sexual partner seeking quick and convenient [ 7 - 10 ]. While some studies found no association between GSN app use for partner seeking and Lexington risk behavior [ 1112 ], some research suggests that partner seeking on GSN apps is associated with increased condomless anal intercourse [ 91314 ], drug use ie methamphetamine, Viagra, poppers, painkillers [ 101315 ], of partners [ 10131617 ], and history of sexually transmitted infection diagnosis [ 151618 - 21 ].
The study collected information on the Kentucky 50 users or, when the total was less than 50, all users within a 2-mile radius of each data collection point. The data were then used to create race-stratified maps that highlighted areas of high spatial densities of MSM [ 23 ].
Research projects like the aforementioned show promise in Online geotargeted HIV prevention, treatment, and recruitment strategies.
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For Kentucky, geofencing, a practice widely used in mobile advertising, relies on mobile phone Global Positioning System and radio-frequency identification technology to trigger strategic HIV prevention and treatment messaging when a user enters or exits a specified area [ 24 ]. Much of the research on GSN app usage among MSM has been conducted in large urban areas [ 101522232526 ], yet similar patterns of online sex seeking are reported among MSM residing in rural and midsize cities [ 2728 ].
Smaller cities often differ from larger cities in terms of stigma [ 2930 ] and availability of visible gay spaces [ 31 - 33 ]. As others have noted, research on sexual health and app-facilitated sexual behavior among MSM in midsized cities is limited [ 34 - 36 ]. Some research has shown that, compared with online-recruited MSM in larger cities, those in small towns were more likely to report using apps to meet long-term partners and men for sex [ 37 ].
Other studies have indicated that rural MSM Kentucky hostility, stigma, and social and sexual isolation Online use the internet to find sex partners [ 3839 ]. It is important to sex acknowledge that these online forums and apps can be central in facilitating positive social connectedness and friendship among MSM [ 404142 ].
Taken together, these findings indicate a changing landscape of social connection and risk behavior among Sex in which technology is increasingly relevant yet not well understood, especially in settings outside of Lexington urban centers. This Lexington is among the first of its kind to use the geospatial capabilities of GSN apps to provide insights on the use of 3 different GSN apps by MSM in a midsize city during weekday daytime and weekend nighttime hours, thus building upon research in a large urban area that focused Online on 1 app and lacked detail on weekday daytime versus weekend nighttime differences [ 23 ].
The purpose of this study was to describe the spatial distribution of GSN app-using MSM in a midsize city in the South and identify geographic and demographic factors associated with areas of high s of GSN app users. Fayette County encompasses the city of Lexington, Kentucky, and has a land area of square miles and a population ofpeople who are predominately white The bisecting routes that offered the best county coverage were selected using Google Maps [ 44 ]. We visited each point twice: once during weekday daytime Monday through Friday, am to pm and once during weekend nighttime Friday or Saturday, pm to pm hours.
While stopped at each point approximately 5 minutes per stopwe logged into a blank profile created for study purposes on each of the 3 GSN apps.
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Once we were logged into the profile, the app displayed the of users within varying distances from the collection point. We recorded the of users within 1 mile on each app, the time of collection, and the latitude and longitude at that collection point on a paper form and via the Fulcrum data collection app [ 45 ]. All apps used in this study have been self-described as providing a space for gay men to look for dates, friends, fun, relationships, and hookups.
Independent variables in the model included block group population density population count per square mile; range 3.
Business zoning, the areas specified for business use by the local government, was included to capture the presence of gathering spaces eg, restaurants, bars, shopping venues, employers. Of the 62 data collection locations, 61 had cell service ie, LTE, 3G, 4G to access apps for data collection.
The point with no service was excluded from kriging analysis. We conducted spatial analyses using ArcMap version We constructed maps to illustrate differences in the spatial distribution and of app-using MSM across apps at different time periods.
The Fayette County shapefile used in the depictions was procured from the Census Bureau [ 53 ]. We used empirical Bayesian kriging EBK for spatial interpolation as it predicts values for areas where data has not been collected based upon the specific values at each collected observation point and their relative proximity to other points.
Past research has employed similar techniques, such as kernel smoothing, and found that kriging offered similar [ 23 ]. Empirical Bayesian kriging analysis of the estimated spatial distribution of geosocial networking app users by time and app.
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We next converted the EBK raster grid cell values to points at their centroids so these values could be ased to the Census block groups; there were from 8 to of these points in each block group, depending on area, with a median of This further enabled estimation of the average of GSN app users within each Census block group. Maps displaying temporal weekday day-weekend night differences in the spatial distribution of app users. Our dependent variable was the of app users for a particular app at a particular time period in each Census block group.
Given that we examined 3 different apps, each at 2 different times, with possible duplication of users across apps and times ie, people using more than 1 app at a time and people using the same app at different time windowswe ran 6 independent models.
We used Wilcoxon ed rank sum tests to examine differences in the of Kentucky using the app between the 3 apps and between weekday daytime and weekend nighttime data collection periods for the same app because the outcome variables were paired and nonparametric. Negative binomial regression was used to examine geographic and demographic factors associated with areas with increasing s of GSN app-using MSM at the Census block group level.
Negative binomial regression was used because the counts were overdispersed and therefore not Lexington for a typical Poisson model. We also ran the models with the independent variables median age, median income, and population density log-transformed to try to force more linear relationships with the outcome.
To test for collinearity, we ran the PROC REG collinearity diagnostic collinoint [ 54 ] to determine how related each variable was to sex other in the presence of all other variables. The analysis for collinearity showed that none of the independent variables was collinear and all could be included in the same final model. The of GSN app users within a 1-mile radius of the data collection points Online from 0 to 36 during weekday daytime hours and 0 to 39 during weekend nighttime hours.
The median of estimated GSN app users in each Census block group in Fayette County during weekday daytime and weekend nighttime varied by app Descriptive statistics of estimated average of geosocial networking app users per Census block group.
From weekday daytime to weekend nighttime, the spatial distribution of app-using MSM varied for 2 of the 3 apps. The use of app 1 was concentrated in downtown Lexington ie, the center of the county during weekday daytime and weekend nighttime; however, at weekend nighttime, a second area south of the city emerged as an area of high app usage. For app 3, use was concentrated in the downtown area both during weekday daytime and weekend nighttime but use was more intensely concentrated in the downtown area at weekend nighttime.
Fayette County comprises Census block groups. Based on the dependent variable of estimated of GSN app users in each Census block group, unadjusted negative binomial regression with each app stratified by time of collection was used to estimate crude risk ratios Table 2. For every persons per square mile increase in population density, the of GSN app users increased by 1. For every year increase in median age, the of GSN app users decreased by 1. Unadjusted analysis of the association between Census block level characteristics and of geosocial networking app—using men who have sex with men.
The multivariable models are shown in Table 3.
Percent white was negatively associated with the of GSN app users for app 1 during the weekday daytime and app 2 during the weekend nighttime but not for any other time or app. In multivariable models with income, age, and population density log-transformed data not shown in tablethe were similar except that in both of the models for app 2 and app 3, median age became statistically ificant and in app 1 day and app 2 night, percent white lost statistical ificance.
Multivariable analysis of the association between Census block level characteristics and of geosocial networking app—using men who have sex with men. This study revealed that the presence of business zoning and population density were positively associated with the of GSN app-using MSM during both weekday daytime and weekend nighttime for all GSN apps. We also found that median income and percent of the population who were Hispanic were negatively associated with the of GSN app-using MSM during both weekday daytime and weekend nighttime for all GSN apps, adjusting for other variables in the model.
Increased app use in areas with the presence of business zoning could imply that app users may be using these apps in areas of economic activity eg, bars, restaurants, stores including areas that cater to a predominantly gay clientele. This could highlight an important overlap between virtual and in-person partner-seeking spaces.
By using Wilcoxon ed rank sum tests and comparing choropleth maps of the differences in the spatial density of GSN app-using MSM, we determined that the total of users between weekday daytime and weekend nighttime was not ificantly different but that specific areas within the county could be experiencing changes in the of partner-seeking MSM between these 2 time periods.
This could imply either that the same users are migrating to different areas over time, different users at different locations are logging in at different times, or a combination of these.
Spatial distribution of partner-seeking men who have sex with men using geosocial networking apps: epidemiologic study
This information could be informative to local health departments because instead of using mobile HIV testing units only during weekend nighttime hours at nightlife venues, these units could also be used at specified hotspots during weekday daytime hours. These data may also be able to inform more cost-efficient geotargeted and temporally targeted recruitment strategies for research.
However, more research is needed to explore attitudes about the presence of HIV outreach activities such as lexington HIV testing units or research recruitment efforts near daytime hotspots such as neighborhoods and places of business.
The novel methods of data collection used in this study addressed some of the limitations of past GSN app research. For example, prior research using GSN apps for data collection largely relied on a single app [ 12142326414256 ]. Our study used 3 apps, and the variance in spatial distribution of use and of users across apps highlights the importance of using multiple apps in future research.
research has also aggregated geographic data across time points rather than examining daytime and nighttime use separately [ 23 ]. Our study, which examined weekday daytime and weekend nighttime use separately, revealed that spatial patterns of use may Online by time of day. Finally, data on the use of GSN apps is also novel in the context of midsize cities as most studies to date have focused solely on larger cities [ 1315 - 172022 - 2426 ].
Collecting data on GSN apps for MSM in midsize cities could be of increased importance due to differences in social context [ 29 - 333839 ] and the way in which users interact with the app in contrast with urban GSN app users [ 37 ]. This is especially important given the disparities in resources for sexual and gender minority people in rural areas sex to large urban centers.
Prior research has demonstrated the importance of technology in the lives of rural sexual and gender minority people in combating social isolation and homophobia in public social spaces [ 37 - 41 Kentucky. In general, more research on the role of technology in fostering resilience among MSM in rural areas is needed.