Skip to main content

Advertisement

Log in

Latent Class Analysis of Online Platforms for Partner-Seeking and Sexual Behaviors Among Men Who Have Sex with Men from Central Kentucky

  • Original Paper
  • Published:
AIDS and Behavior Aims and scope Submit manuscript

Abstract

Little is known whether engagement in sexual behaviors associated with potential HIV risks differs by subgroups of men who have sex with men (MSM), who are distinct regarding patterns of use of online tools for partner-seeking. Using latent class analysis, we revealed four classes of app-using MSM (n = 181, 18–34 y.o., 82.4% identified as White and non-Hispanic) residing in Central Kentucky: the Grindr/Tinder class; the Poly App Use class of MSM-oriented apps; the General Social Media class, and the Bumble class. Unadjusted penalized logistic regressions showed associations of the Poly App Use class with increased numbers of receptive anal sex partners and reporting condomless receptive anal sex. Adjusting for other covariates, poly app users versus others were more likely to be older (25–34 vs. 18–24, AOR = 3.81, 95%CI = 1.70–9.03), to report past six-month illicit drug use (AOR = 2.93, 95%CI = 1.25–7.43) and to have ever used pre-exposure prophylaxis (AOR = 2.79, 95%CI = 1.10–7.12). Poly app users had behavior profiles associated with an elevated HIV risk and also reported HIV-related protective behaviors likely indicating increased risk awareness among this class. Our findings warrant differentiation of behavior profiles by patterns of app use and suggest not to generalize sexual behaviors associated with potential HIV risks to all app-using MSM.

Resumen

Poco se sabe si la participación en comportamientos sexuales asociados con riesgos potenciales de VIH difiere según distintos subgrupos de hombres que tienen sexo con hombres (HSH) en base a patrones en el uso de herramientas online para la búsqueda de pareja. Mediante el análisis de clases latentes, identificamos cuatro clases de HSH que usan aplicaciones (n = 181, 18–34 años, 82.4% identificados como Blancos y no-Hispanos) y residen en Kentucky Central: la clase Grindr/Tinder, la clase Poly App Use de aplicaciones orientadas a HSH, la clase General Social Media y la clase Bumble. Las regresiones logísticas penalizadas no ajustadas mostraron asociaciones de la clase Poly App Use con un alza en el número de parejas receptivas en relaciones sexuales anales y con reportes de sexo anal receptivo sin condón. Al ajustar por otras covariables, los miembros de la clase Poly App Use, con respecto a las otras clases, tuvieron más probabilidades de ser mayores (25–34 vs. 18–24, ORA = 3,81; IC95%=1,70 − 9,03), de informar el uso de drogas ilícitas en los últimos 6 meses (ORA = 2,93; IC95%=1,25 − 7,43) y haber utilizado alguna vez profilaxis-preexposición (ORA = 2,79; IC95%=1,10 − 7,12). Así mismo, los miembros de esta clase tuvieron perfiles de comportamiento asociado con el riesgo elevado de VIH y también informaron comportamientos de protección relacionados con el VIH que probablemente indican una mayor conciencia del riesgo entre ellos. Nuestros hallazgos justifican la diferenciación de perfiles de comportamiento en base a patrones de uso de aplicaciones y sugieren no generalizar los comportamientos sexuales asociados con riesgos potenciales de VIH a todos los HSH que las usan.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

Data Availability

De-identified data may be made available upon reasonable request to the Principal Investigator, April M. Young.

Code Availability

N/A.

Abbreviations

MSM:

Men who have sex with men

CHAPTER 5. References

  1. Grov C, Breslow AS, Newcomb ME, Rosenberger JG, Bauermeister JA. Gay and bisexual men’s use of the internet: research from the 1990s through 2013. J Sex Res. 2014;51(4):390–409. https://doi.org/10.1080/00224499.2013.871626.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Klausner JD, Wolf W, Fischer-Ponce L, Zolt I, Katz MH. Tracing a syphilis outbreak through cyberspace. J Am Med Association. 2000;284(4):447–9. https://doi.org/10.1001/jama.284.4.447.

    Article  CAS  Google Scholar 

  3. Hospers HJ, Harterink P, van den Hoek K, Veenstra J. Chatters on the internet: a special target group for HIV prevention. AIDS Care. 2002;14(4):539–44. https://doi.org/10.1080/09540120208629671.

    Article  CAS  PubMed  Google Scholar 

  4. Bowen A, Williams M, Horvath K. Using the internet to recruit rural MSM for HIV risk assessment: sampling issues. AIDS Behav. 2004;8(3):311–9. https://doi.org/10.1023/B:AIBE.0000044078.43476.1f.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Horvath KJ, Bowen AM, Williams ML. Virtual and physical venues as contexts for HIV risk among rural men who have sex with men. Health Psychol. 2006;25(2):237–42. https://doi.org/10.1037/0278-6133.25.2.237.

    Article  PubMed  Google Scholar 

  6. Horvath KJ, Rosser BR, Remafedi G. Sexual risk taking among young internet-using men who have sex with men. Am J Public Health. 2008;98(6):1059–67. https://doi.org/10.2105/ajph.2007.111070.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Chew Ng RA, Samuel MC, Lo T, et al. Sex, drugs (methamphetamines), and the internet: increasing syphilis among men who have sex with men in California, 2004–2008. Am J Public Health. 2012;103(8):1450–6. https://doi.org/10.2105/AJPH.2012.300808.

    Article  PubMed  Google Scholar 

  8. Hoenigl M, Little SJ, Grelotti D, et al. Grindr users take more risks, but are more open to human immunodeficiency virus (HIV) pre-exposure prophylaxis: could this dating app provide a platform for HIV prevention outreach? Clin Infect Dis. 2020;71(7):e135–40. https://doi.org/10.1093/cid/ciz1093.

    Article  PubMed  Google Scholar 

  9. Landovitz RJ, Tseng C-H, Weissman M, et al. Epidemiology, sexual risk behavior, and HIV prevention practices of men who have sex with men using GRINDR in Los Angeles, California. J Urb Health. 2013;90(4):729–39. https://doi.org/10.1007/s11524-012-9766-7.

    Article  Google Scholar 

  10. Burrell ER, Pines HA, Robbie E, et al. Use of the location-based social networking application GRINDR as a recruitment tool in rectal microbicide development research. AIDS Behav. 2012;16(7):1816–20. https://doi.org/10.1007/s10461-012-0277-z.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Winetrobe H, Rice E, Bauermeister J, Petering R, Holloway IW. Associations of unprotected anal intercourse with Grindr-met partners among Grindr-using young men who have sex with men in Los Angeles. AIDS Care. 2014;26(10):1303–8. https://doi.org/10.1080/09540121.2014.911811.

    Article  PubMed  Google Scholar 

  12. Rice E, Holloway I, Winetrobe H, et al. Sex risk among young men who have sex with men who use Grindr, a smartphone geosocial networking application. J AIDS Clin Res. 2012;Suppl4:005.

    Google Scholar 

  13. Goedel WC, Duncan DT. Geosocial-networking app usage patterns of gay, bisexual, and other men who have sex with men: Survey among users of Grindr, a mobile dating app. JMIR Public Health Surveillance. 2015;1(1):e4. https://doi.org/10.2196/publichealth.4353.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Rendina HJ, Jimenez RH, Grov C, Ventuneac A, Parsons JT. Patterns of lifetime and recent HIV testing among men who have sex with men in New York City who use Grindr. AIDS Behav. 2014;18(1):41–9. https://doi.org/10.1007/s10461-013-0573-2.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Paz-Bailey G, Hoots BE, Xia M, Finlayson T, Prejean J, Purcell DW. Trends in Internet use among men who have sex with men in the United States. J Acquir Immune Defic Syndr. 2017;75(Suppl 3):288–s295. https://doi.org/10.1097/qai.0000000000001404.

    Article  Google Scholar 

  16. Rogge RD, Crasta D, Legate N. Is tinder–grindr use risky? Distinguishing venue from individuals’ behavior as unique predictors of sexual risk. Arch Sex Behav. 2020;49(4):1263–77. https://doi.org/10.1007/s10508-019-01594-w.

    Article  PubMed  Google Scholar 

  17. Reviews.com DS. Grindr information, statistics, facts and history. 2021. Available from: https://www.datingsitesreviews.com/staticpages/index.php?page=grindr-statistics-facts-history Accessed October 20, 2020.

  18. Beymer MR, Rossi AD, Shu SB. Assessing self-control and geosocial networking app behavior among an online sample of men who have sex with men. J Urb Health. 2016;93(4):698–708. https://doi.org/10.1007/s11524-016-0056-7.

    Article  Google Scholar 

  19. GROWLr. 2021. Available from: https://play.google.com/store/apps/details?id=com.initechapps.growlr&hl=en_US&gl=US Accessed April 22. 2021.

  20. Badal HJ, Stryker JE, DeLuca N, Purcell DW. Swipe right: dating website and app use among men who have sex with men. AIDS Behav. 2018;22(4):1265–72. https://doi.org/10.1007/s10461-017-1882-7.

    Article  PubMed  Google Scholar 

  21. Holloway IW, Winder TJ, Lea CH III, Tan D, Boyd D, Novak D. Technology use and preferences for mobile phone–based HIV prevention and treatment among black young men who have sex with men: exploratory research. JMIR Mhealth Uhealth. 2017;5(4):e46. https://doi.org/10.2196/mhealth.6436.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Jack’d. 2021. Available from: https://play.google.com/store/apps/details?id=mobi.jackd.android&hl=en_US&gl=US Accessed April 22, 2021.

  23. Scruff. 2021. Available from: https://play.google.com/store/apps/details?id=com.appspot.scruffapp&hl=en_US&gl=US Accessed April 22, 2021.

  24. Sousa AFL, Queiroz AAFLN, Fronteira I, Lapão L, Mendes IAC, Brignol S. HIV testing among middle-aged and older men who have sex with men (MSM): a blind spot? Am J Men’s Health. 2019;13(4):1557988319863542. https://doi.org/10.1177/1557988319863542.

    Article  Google Scholar 

  25. Datta T, Shivdas S. Match tops sales estimates as Tinder, Hinge keep sparks flying. 2021. Available from: https://www.reuters.com/article/us-match-group-results-idUSKBN2A22V1 Accessed April 22, 2021.

  26. Curry D. Bumble revenue and usage statistics (2022). Business of Apps 2022. Available from: https://www.businessofapps.com/data/bumble-statistics/ Accessed November 21, 2022.

  27. Beymer MR, Weiss RE, Bolan RK, et al. Sex on demand: Geosocial networking phone apps and risk of sexually transmitted infections among a cross-sectional sample of men who have sex with men in Los Angeles County. Sex Transm Infect. 2014;90(7):567–72. https://doi.org/10.1136/sextrans-2013-051494.

    Article  PubMed  Google Scholar 

  28. Grov C, Agyemang L, Ventuneac A, Breslow AS. Navigating condom use and HIV status disclosure with partners met online: a qualitative pilot study with gay and bisexual men from Craigslist.org. AIDS Educ Prev. 2013;25(1):72–85. https://doi.org/10.1521/aeap.2013.25.1.72.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Bineau L, Lambert D, Truszczynski N, Hansen N, Lauckner C. Dating app use among rural men who have sex with men and its relationship to HIV prevention and risk behaviors: a mixed-methods analysis. Rural Remote Health. 2021;21(2):6556. https://doi.org/10.22605/rrh6556.

    Article  PubMed  Google Scholar 

  30. Liau A, Millett G, Marks G. Meta-analytic examination of online sex-seeking and sexual risk behavior among men who have sex with men. Sex Transm Dis. 2006;33(9):576–84. https://doi.org/10.1097/01.olq.0000204710.35332.c5.

    Article  PubMed  Google Scholar 

  31. Zou H, Fan S. Characteristics of men who have sex with men who use smartphone geosocial networking applications and implications for HIV Interventions: a systematic review and meta-analysis. Arch Sex Behav. 2017;46(4):885–94. https://doi.org/10.1007/s10508-016-0709-3.

    Article  PubMed  Google Scholar 

  32. Wang H, Zhang J, Chu Z, et al. Risk-taking behaviors and adherence to HIV pre-exposure prophylaxis in users of geosocial networking apps: Real-world, multicenter study. J Med Internet Res. 2020;22(10):e22388. https://doi.org/10.2196/22388.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Newcomb ME, Mongrella MC, Weis B, McMillen SJ, Mustanski B. Partner disclosure of PrEP use and undetectable viral load on geosocial networking apps: frequency of disclosure and decisions about condomless sex. J Acquir Immune Defic Syndr. 2016;71(2):200–6. https://doi.org/10.1097/qai.0000000000000819.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Brown G, Maycock B, Burns S. Your picture is your bait: use and meaning of cyberspace among gay men. J Sex Res. 2005;42(1):63–73. https://doi.org/10.1080/00224490509552258.

    Article  PubMed  Google Scholar 

  35. Carballo-Diéguez A, Miner M, Dolezal C, Rosser BRS, Jacoby S. Sexual negotiation, HIV-status disclosure, and sexual risk behavior among latino men who use the internet to seek sex with other men. Arch Sex Behav. 2006;35(4):473–81. https://doi.org/10.1007/s10508-006-9078-7.

    Article  PubMed  Google Scholar 

  36. Handel MJ, Shklovski I. Disclosure, ambiguity and risk reduction in real-time dating sites. Proceedings of the 17th ACM international conference on Supporting group work; 2012; Sanibel Island, Florida, USA.

  37. De Lore JSt, Thiede H, Cheadle A, et al. HIV disclosure and subsequent sexual behaviors among men who have sex with men who meet online. J Homosex. 2012;59(4):592–609. https://doi.org/10.1080/00918369.2012.665704.

    Article  Google Scholar 

  38. Muessig KE, Pike EC, Legrand S, Hightow-Weidman LB. Mobile phone applications for the care and prevention of HIV and other sexually transmitted diseases: a review. J Med Internet Res. 2013;15(1):e1–e1. https://doi.org/10.2196/jmir.2301.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Bowen AM, Horvath K, Williams ML. A randomized control trial of internet-delivered HIV prevention targeting rural MSM. Health Educ Res. 2006;22(1):120–7. https://doi.org/10.1093/her/cyl057.

    Article  PubMed  Google Scholar 

  40. Ybarra ML, Bull SS. Current trends in internet- and cell phone-based HIV prevention and intervention programs. Curr HIV/AIDS Rep. 2007;4(4):201–7. https://doi.org/10.1007/s11904-007-0029-2.

    Article  PubMed  Google Scholar 

  41. Du Bois SN, Johnson SE, Mustanski B. Examining racial and ethnic minority differences among YMSM during recruitment for an online HIV prevention intervention study. AIDS Behav. 2012;16(6):1430–5. https://doi.org/10.1007/s10461-011-0058-0.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Pennise M, Inscho R, Herpin K, et al. Using smartphone apps in STD interviews to find sexual partners. Public Health Rep. 2015;130(3):245–52. https://doi.org/10.1177/003335491513000311.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Huang ET, Williams H, Hocking JS, Lim MS. Safe sex messages within dating and entertainment smartphone apps: a review. JMIR Mhealth Uhealth. 2016;4(4):e124. https://doi.org/10.2196/mhealth.5760.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Chiasson MA, Shaw FS, Humberstone M, Hirshfield S, Hartel D. Increased HIV disclosure three months after an online video intervention for men who have sex with men (MSM). AIDS Care. 2009;21(9):1081–9. https://doi.org/10.1080/09540120902730013.

    Article  PubMed  Google Scholar 

  45. Bowen AM, Williams ML, Daniel CM, Clayton S. Internet based HIV prevention research targeting rural MSM: feasibility, acceptability, and preliminary efficacy. J Behav Med. 2008;31(6):463–77. https://doi.org/10.1007/s10865-008-9171-6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Chan PA, Towey C, Poceta J, et al. Online hookup sites for meeting sexual partners among men who have sex with men in Rhode Island, 2013: a call for public health action. Public Health Rep. 2016;131(2):264–71. https://doi.org/10.1177/003335491613100210.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Pravosud V, Ballard AM, Holloway IW, Young AM. Online partner seeking and sexual behaviors among men who have sex with men from small and midsized towns: cross-sectional study. JMIR Form Res. 2022;6(6):e35056. https://doi.org/10.2196/35056.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Smith MK, Stein G, Cheng W, Miller WC, Tucker JD. Identifying high risk subgroups of MSM: a latent class analysis using two samples. BMC Infect Dis. 2019;19(1):213. https://doi.org/10.1186/s12879-019-3700-5.

    Article  PubMed  Google Scholar 

  49. Dangerfield DT, Carmack CC, Gilreath TD, Duncan DT. Latent classes of partner-seeking venues and sexual risk among men who have sex with men in Paris, France. Int J STD AIDS. 2020;31(6):502–9. https://doi.org/10.1177/0956462419899012.

    Article  PubMed  Google Scholar 

  50. Choi SK, Bauermeister J. A latent profile analysis of online dating patterns among single young men who have sex with men. AIDS Behav. 2022;26(4):1279–88. https://doi.org/10.1007/s10461-021-03485-5.

    Article  PubMed  Google Scholar 

  51. Grosskopf NA, LeVasseur MT, Glaser DB. Use of the internet and mobile-based apps for sex-seeking among men who have sex with men in New York City. Am J Men’s Health. 2014;8(6):510–20. https://doi.org/10.1177/1557988314527311.

    Article  Google Scholar 

  52. Chiu CJ, Young SD. The relationship between online social network use, sexual risk behaviors, and HIV sero-status among a sample of predominately african american and latino men who have sex with men (MSM) social media users. AIDS Behav. 2015;19(Suppl 2):98–105. https://doi.org/10.1007/s10461-014-0986-6.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Grosskopf NA, Harris JK, Wallace BC, Nanin JE. Online sex-seeking behaviors of men who have sex with men in New York City. Am J Men’s Health. 2011;5(5):378–85. https://doi.org/10.1177/1557988310372801.

    Article  Google Scholar 

  54. Patel VV, Masyukova M, Sutton D, Horvath KJ. Social media use and HIV-related risk behaviors in young black and latino gay and bi men and transgender individuals in New York City: implications for online interventions. J Urb Health. 2016;93(2):388–99. https://doi.org/10.1007/s11524-016-0025-1.

    Article  Google Scholar 

  55. Kim AA, Kent C, McFarland W, Klausner JD. Cruising on the internet highway. J Acquir Immune Defic Syndr. 2001;28(1):89–93. https://doi.org/10.1097/00042560-200109010-00013.

    Article  CAS  PubMed  Google Scholar 

  56. DeMio T. HIV testing bolstered, syringe exchange encouraged as Butler County sees cluster of cases. 2022. Available from: https://www.cincinnati.com/story/news/2022/03/03/hamilton-ohio-hiv-cluster-prompts-tests-awareness-syringe-services-harm-reduction-in-butler-county/9340530002/ Accessed November 22, 2022.

  57. Peters PJ, Pontones P, Hoover KW, et al. HIV infection linked to injection use of oxymorphone in Indiana, 2014–2015. N Engl J Med. 2016;375(3):229–39.

    Article  CAS  PubMed  Google Scholar 

  58. Northern Kentucky Health Department. Health officials see increase in HIV infection among individuals who inject drugs. NKYHEALTH. 2018. Available from: https://nkyhealth.org/2018/01/09/health-officials-see-increase-in-hiv-infection-among-individuals-who-inject-drugs/ or http://www.buffalotracehealth.com/wp-content/uploads/2018/01/HIV-Cluster-Investigation-Press-Release.pdf Accessed February 2, 2021.

  59. Northern Kentucky Health Department. As HIV cluster investigation moves into second month, health officials increase opportunities for HIV testing. NKYHEALTH. 2018. Available from: https://nkyhealth.org/2018/02/22/as-hiv-cluster-investigation-moves-into-second-month-health-officials-increase-opportunities-for-hiv-testing/ or https://www.nkytribune.com/2018/02/as-hiv-cluster-investigation-moves-into-second-month-health-officials-increase-opportunities-to-test/ Accessed February 2, 2021.

  60. McClung RP, Atkins AD, Kilkenny M, et al. Response to a large HIV outbreak, Cabell County, West Virginia, 2018–2019. Am J Prev Med. 2021;61(5):143–S150. https://doi.org/10.1016/j.amepre.2021.05.039.

    Article  Google Scholar 

  61. WSAZ News Staff. HIV cases increasing in Cabell County. WSAZ NewsChannel 3 2019:Accessed on February 2, 2021. Available at: https://www.wsaz.com/content/news/HIV-cluster-confirmed-in-Cabell-County-506708841.html.

  62. Van Handel MM, Rose CE, Hallisey EJ, et al. County-level vulnerability assessment for rapid dissemination of HIV or HCV infections among persons who inject drugs, United States. J Acquir Immune Defic Syndr. 2016;73(3):323–31. https://doi.org/10.1097/qai.0000000000001098.

    Article  PubMed  PubMed Central  Google Scholar 

  63. Ballard AM, Cardwell T, Young AM. Fraud detection protocol for web-based research among men who have sex with men: development and descriptive evaluation. JMIR Public Health Surveillance. 2019;5(1):e12344. https://doi.org/10.2196/12344.

    Article  PubMed  PubMed Central  Google Scholar 

  64. Centers for Disease Control and Prevention. Estimated HIV incidence in the United States, 2007–2010. HIV surveillance supplemental report. 2012;17(4). Available from: https://www.cdc.gov/hiv/pdf/library/reports/surveillance/cdc-hiv-surveillance-supplemental-report-vol-17-4.pdf.

  65. Joho J. HOTorNOT shaped the social web as we know it. Available from: https://mashable.com/feature/hotornot-history-20-year-anniversary/ Accessed April 20, 2021.

  66. Bien CH, Best JM, Muessig KE, Wei C, Han L, Tucker JD. Gay apps for seeking sex partners in China: implications for MSM sexual health. AIDS Behav. 2015;19(6):941–6. https://doi.org/10.1007/s10461-014-0994-6.

    Article  PubMed  PubMed Central  Google Scholar 

  67. Knox J, Chen YN, He Q, et al. Use of geosocial networking apps and HIV risk behavior among men who have sex with men: case-crossover study. JMIR Public Health Surveill. 2021;7(1):e17173. https://doi.org/10.2196/17173.

    Article  PubMed  PubMed Central  Google Scholar 

  68. State and County QuickFacts. 2021. https://www.census.gov/quickfacts/fact/table/lexingtonfayettekentucky,KY,US. Accessed November 21, 2022.

  69. United States Department of Agriculture (USDA). The 2013 rural-urban continuum codes. 2016. Available from: https://www.ers.usda.gov/data-products/rural-urban-continuum-codes.aspx Accessed April 21, 2021.

  70. Centers for Disease Control and Prevention. Male condom effectiveness: fact sheet for public health personnel. 2013. Available from: https://www.cdc.gov/condomeffectiveness/latex.html Accessed April 19, 2021.

  71. Patel P, Borkowf CB, Brooks JT, Lasry A, Lansky A, Mermin J. Estimating per-act HIV transmission risk: a systematic review. AIDS. 2014;28(10):1509–19. https://doi.org/10.1097/QAD.0000000000000298.

    Article  PubMed  Google Scholar 

  72. RStudio Team. RStudio: Integrated Development for R. RStudio, Inc., Boston, MA. 2016. Available from: http://www.rstudio.com/.

  73. Collins LM, Lanza ST. Latent class and latent transition analysis: With applications in the social, behavioral, and health sciences. 2010:97–98. https://doi.org/10.1002/9780470567333.

  74. Knezevic A. Overlapping confidence intervals and statistical significance. Cornell Statistical Consulting Unit 2008. Available from: https://cscu.cornell.edu/wp-content/uploads/73_ci.pdf Accessed March 14, 2023.

  75. Nagin D. Group-based modeling of development. Harv Univ Press 2009:88–9.

  76. Nagin DS, Heinz T, Heinz HJI. Group-based modeling of development. Harvard University Press.; 2005.

  77. Clogg C. Latent class models: Recent developments and prospects for the future. (In: Arminger G, Clogg CC, Sobel ME, editors.) Handbook of statistical modeling for the social and behavioral sciences. New York, NY: Plenum Press 1995:311–359.

  78. Royston P. Profile likelihood for estimation and confidence intervals. Stata J. 2007;7(3):376–87. https://doi.org/10.1177/1536867x0700700305.

    Article  Google Scholar 

  79. Bull SB, Mak C, Greenwood CMT. A modified score function estimator for multinomial logistic regression in small samples. Comput Stat Data Anal. 2002;39(1):57–74. https://doi.org/10.1016/S0167-9473(01)00048-2.

    Article  MathSciNet  Google Scholar 

  80. Devika S, Jeyaseelan L, Sebastian G. Analysis of sparse data in logistic regression in medical research: a newer approach. J Postgrad Med. 2016;62(1):26–31. https://doi.org/10.4103/0022-3859.173193.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Kingdon MJ, Storholm ED, Halkitis PN, et al. Targeting HIV prevention messaging to a new generation of gay, bisexual, and other young men who have sex with men. J Health Communication. 2013;18(3):325–42. https://doi.org/10.1080/10810730.2012.727953.

    Article  PubMed  Google Scholar 

  82. Holloway IW, Rice E, Gibbs J, Winetrobe H, Dunlap S, Rhoades H. Acceptability of smartphone application-based HIV prevention among young men who have sex with men. AIDS Behav. 2014;18(2):285–96. https://doi.org/10.1007/s10461-013-0671-1.

    Article  PubMed  PubMed Central  Google Scholar 

  83. Kubicek K, Carpineto J, McDavitt B, Weiss G, Kipke MD. Use and perceptions of the internet for sexual information and partners: a study of young men who have sex with men. Arch Sex Behav. 2011;40(4):803–16. https://doi.org/10.1007/s10508-010-9666-4.

    Article  PubMed  Google Scholar 

  84. Kubicek K, Carpineto J, McDavitt B, et al. Integrating professional and folk models of HIV risk: YMSM’s perceptions of high–risk sex. AIDS Educ Prev. 2008;20(3):220–38. https://doi.org/10.1521/aeap.2008.20.3.220.

    Article  PubMed  PubMed Central  Google Scholar 

  85. Torres TS, De Boni RB, de Vasconcellos MT, et al. Awareness of prevention strategies and willingness to use preexposure prophylaxis in brazilian men who have sex with men using apps for sexual encounters: online cross-sectional study. JMIR Public Health Surveillance. 2018;4(1):e11. https://doi.org/10.2196/publichealth.8997.

    Article  PubMed  PubMed Central  Google Scholar 

  86. Torres TS, Luz PM, De Boni RB, et al. Factors associated with PrEP awareness according to age and willingness to use HIV prevention technologies: the 2017 online survey among MSM in Brazil. AIDS Care. 2019;31(10):1193–202. https://doi.org/10.1080/09540121.2019.1619665.

    Article  PubMed  Google Scholar 

  87. Aghaizu A, Mercey D, Copas A, Johnson AM, Hart G, Nardone A. Who would use PrEP? Factors associated with intention to use among MSM in London: a community survey. Sex Transm Infect. 2013;89(3):207–11. https://doi.org/10.1136/sextrans-2012-050648.

    Article  PubMed  Google Scholar 

  88. Grov C, Whitfield THF, Rendina HJ, Ventuneac A, Parsons JT. Willingness to take PrEP and potential for risk compensation among highly sexually active gay and bisexual men. AIDS Behav. 2015;19(12):2234–44. https://doi.org/10.1007/s10461-015-1030-1.

    Article  PubMed  PubMed Central  Google Scholar 

  89. Krakower DS, Mimiaga MJ, Rosenberger JG, et al. Limited awareness and low immediate uptake of pre-exposure prophylaxis among men who have sex with men using an internet social networking site. PLoS ONE. 2012;7(3):e33119–9. https://doi.org/10.1371/journal.pone.0033119.

    Article  CAS  PubMed  PubMed Central  ADS  Google Scholar 

  90. Hillis A, Germain J, Hope V, McVeigh J, Van Hout MC. Pre-exposure prophylaxis (PrEP) for HIV prevention among men who have sex with men (MSM): a scoping review on PrEP service delivery and programming. AIDS Behav. 2020;24(11):3056–70. https://doi.org/10.1007/s10461-020-02855-9.

    Article  PubMed  PubMed Central  Google Scholar 

  91. Tomkins A, George R, Kliner M. Sexualised drug taking among men who have sex with men: a systematic review. Perspect Public Health. 2019;139(1):23–33. https://doi.org/10.1177/1757913918778872.

    Article  PubMed  Google Scholar 

  92. Kaufman M. This new Grindr feature could persuade users to regularly get tested for HIV. 2018. Available from: https://mashable.com/2018/03/28/grindr-lauches-hiv-reminder-feature/ Accessed February 10, 2021.

  93. PRNewswire. Grindr launches new opt-in HIV testing reminders to help users get tested more regularly. 2018. Available from: https://www.prnewswire.com/news-releases/grindr-launches-new-opt-in-hiv-testing-reminders-to-help-users-get-tested-more-regularly-300619811.html Accessed March 14, 2023.

  94. Ventuneac A, John SA, Whitfield THF, Mustanski B, Parsons JT. Preferences for sexual health smartphone app features among gay and bisexual men. AIDS Behav. 2018;22(10):3384–94. https://doi.org/10.1007/s10461-018-2171-9.

    Article  PubMed  PubMed Central  Google Scholar 

  95. Matthews H. 27 Online dating statistics & what they mean for the future of dating. 2018. Available from: https://www.datingnews.com/industry-trends/online-dating-statistics-what-they-mean-for-future/ Accessed February 9, 2021.

  96. Duncan DT, Park SH, Hambrick HR, et al. Characterizing geosocial-networking app use among young black men who have sex with men: a multi-city cross-sectional survey in the Southern United States. JMIR Mhealth Uhealth. 2018;6(6):e10316. https://doi.org/10.2196/10316.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank research staff members, the research team (including Angel Algarin and Trey Cardwell), and research participants. We thank Dr. Sergio Rivera Polanco for editing the abstract in Spanish.

Funding

The study was supported by the National Institute on Drug Abuse (NIH NIDA R03 DA039740). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. IWH is supported by the California HIV/AIDS Research Program (RP15-LA-007); the Center for HIV Identification, Prevention, and Treatment (MH58107); the University of California Los Angeles Center for AIDS Research (5P30AI028697); and the National Institutes of Health National Center for Advancing Translational Science (UL1TR000124).

Author information

Authors and Affiliations

Authors

Contributions

VP and AMY shaped the research question. VP conducted data analysis, interpreted the results, and drafted and revised the manuscript. AMB, IWH, and AMY contributed to study design, data collection, and revisions of the manuscript. AMY led funding acquisition. All authors approved the final version of the manuscript.

Corresponding author

Correspondence to Vira Pravosud.

Ethics declarations

Competing Interests

None declared.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic Supplementary Material

Below is the link to the electronic supplementary material.

Supplementary Material 1

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Pravosud, V., Ballard, A.M., Holloway, I.W. et al. Latent Class Analysis of Online Platforms for Partner-Seeking and Sexual Behaviors Among Men Who Have Sex with Men from Central Kentucky. AIDS Behav 28, 1015–1028 (2024). https://doi.org/10.1007/s10461-023-04210-0

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10461-023-04210-0

Keywords

Palabras Clave

Navigation