Abstract
Background
Geosocial networking applications (e.g., “hookup apps”) are widely used among adult men who have sex with men (MSM). Little is known about adolescent MSM’s (AMSM) use of these apps. Exploratory research is needed as AMSM’s app use poses various ethical, legal, and sexual health concerns.
Methods
200 sexually experienced AMSM in the USA (M age = 16.2, 49% racial/ethnic minority) completed online survey questions assessing their use of apps specific to MSM and not specific to MSM to meet partners for dating and sex as well as their sexual behavior and HIV risk.
Results
52.5% of participants (n = 105) reported using MSM-specific apps to meet partners for sex. Of these, most reported having oral (75.7%, n = 78) and anal sex (62.1%, n = 64) with those partners. Of those who reported having anal sex, 78.1% (n = 50) had sex with those partners more than once, and only 25.0% (n = 16) always used condoms with those partners. Relative to those who used only non-MSM-specific apps, MSM-specific app users reported more sex partners and condomless anal sex partners, greater perceived risk of HIV, more engagement in sexual health services, and greater odds of HIV testing.
Conclusions
Use of MSM-specific apps was not uncommon among this sample of AMSM. Patterns of risk behavior and HIV testing were similar to samples of adult MSM-app users. Further research should investigate AMSM’s app-related sexual and HIV/STI prevention decision making to guide sexual health education efforts for AMSM.
Keywords: adolescent sexual behavior, men who have sex with men, geosocial networking applications, social media, HIV/AIDS
Geosocial networking applications are widely used by adult men who have sex with men (MSM) in the United States to meet partners for sex and dating.1–3 Online social networks, including mobile technologies, provide a means for MSM to explore sexual desires, meet sexual needs, and connect to the gay community4–6 and have been linked with positive psychosocial outcomes, such as low levels of internalized homophobia and high levels of gay identity affirmation.7 However, use of these technologies (referred to as “hookup apps” here) is also associated with sexual risk taking and adverse sexual health outcomes,8 such as higher numbers of sex partners9 and greater incidence of sexually transmitted infections (STIs),10 compared to general samples of MSM. Moreover, some studies indicate MSM are less likely to use condoms with partners met via hookup apps,11 though evidence for this is equivocal.12,13 MSM who use hookup apps report relatively high rates of lifetime and past-year HIV testing as well, suggesting either that engaging in risk behavior may prompt men to seek sexual health services or that testing negative for HIV/STIs may make men feel invulnerable and lead to greater risk behavior.8,14
Media reports suggest that adolescent MSM under 18 (AMSM) may also use hookup apps to seek partners,15 and AMSM may gravitate toward them for similar reasons as adults: hookup apps provide a convenient and discreet way to explore their developing sexual identities and overcome common obstacles to meeting same-sex partners, such as proximity, sexual identity disclosure, and ascertaining a prospective partner’s sexual orientation.16,17 However, the explicitly sexual context of hookup apps, and the fact that adolescents are still developing their ability to delay gratification, control impulses, and self-regulate in the face of emotional and rewarding stimuli,18 may also result in greater sexual risk taking among AMSM using hookup apps. Indeed, studies of adolescent sexual behavior and internet use indicate that relative to heterosexual youth, gay adolescents are more likely to report online partner seeking19,20 and unprotected sex with a partner met online,19 and these behavior patterns may generalize to MSM-specific hookup apps. Finally, hookup app use poses legal risks if AMSM are under the legal age of consent in their state and have adult partners.
To date, no empirical studies have examined hookup app usage patterns among AMSM. Reasons for this lack of research may include the fact that studies on MSM app use often recruit participants from the apps, whose terms of service require users to be over 18, as well as actual and perceived barriers among researchers to conducting research on sexual behavior in sexual minority adolescents.21 However, this is a critical gap in our knowledge. AMSM are disproportionately affected by HIV, accounting for 77% of diagnoses among teenagers,22 and their HIV incidence rate is rising.23 Research is needed to shed light on a unique sexual context that may be linked with elevated rates of HIV risk behavior among a group at disproportionately high risk for HIV. This study sought to describe patterns of hookup app use among AMSM and examine relationships between their hookup app use and HIV risk and preventive behaviors.
Methods
As part of a larger study,24–26 AMSM aged 14–17 were recruited from December 2016 to February 2017 through paid Facebook advertisements to complete an online survey on ethical issues in adolescent HIV prevention research. The advertisements targeted adolescents who indicated they were romantically interested in the same or both genders on their profile and/or listed interests relevant to sexual minority youth (e.g., pop culture figures, sexual minority-related organizations). Clicking on the advertisement directed the individual to a brief eligibility survey. Eligible individuals were assigned male at birth; identified as gay, bisexual, queer, or questioning/unsure; reported having had anal sex with a male partner; lived in the United States; could read English at an 8th grade level; and self-reported an HIV-negative status or had not previously been tested for HIV. Eligible individuals reviewed an online consent form and were automatically routed to the survey upon confirming consent. Participants who completed the survey and whose data passed the study’s validation protocol27 received a $30 electronic gift card. Procedures were approved by the universities’ Institutional Review Boards with a waiver of parental permission and the National Institutes of Health issued a Certificate of Confidentiality.
Measures
Sociodemographic characteristics
Participants completed items assessing age, race and ethnicity, birth-assigned sex, gender identity, sexual orientation, and sexual orientation disclosure (i.e., “outness”) to parents. For analysis, race/ethnicity was dichotomized to non-Hispanic White versus racial/ethnic minority, sexual orientation was dichotomized to gay versus non-gay-identified, and disclosure to parents was dichotomized to being not out versus being out to at least one parent.
Sexual history and HIV/STI risk
One item asked participants to select whether they had sex with “only guys”, “mostly guys but some girls”, “guys and girls equally”, “mostly girls but some guys”, or “only girls”; those endorsing the last option were ineligible, and the rest were dichotomized to behaviorally homosexual versus behaviorally bisexual for analysis. Additional items obtained more details about participants’ sexual behavior and sexual risk specific to sex with male partners. Items included number of lifetime anal sex partners, number of lifetime condomless anal sex (CAS) partners, and frequency of substance and alcohol use before sex in the past 12 months. Finally, items assessing perceived risk of HIV28 asked about participants’ perceived likelihood of becoming infected with HIV (1 = extremely unlikely, 5 = extremely likely) and how frequently participants worried about getting infected with HIV (1 = none of the time, 5 = all of the time).
Sexual healthcare engagement and testing
Six items assessed participants’ healthcare experiences relevant to their sexual health.29 Items began with “In the past I have spoken to a doctor, nurse, or other healthcare provider about…” and asked about sexual orientation, sex with male partners, HIV testing, pre-exposure prophylaxis (PrEP) to prevent HIV infection, condoms and other HIV/STI prevention methods, and HIV/STI prevention specific to male–male sex. Response options were on a 5-point scale (1 = never; 5 = always), and for analysis, a sexual healthcare engagement score was calculated based on the mean of all six items, with higher scores indicating greater levels of engagement. Two other items assessed whether participants had ever been tested for HIV in their lifetime and whether they had been tested for STIs in the past year.
Hookup-app use
Ten investigator-created items assessed respondents’ use of social media websites and mobile apps to meet men for dating, romantic relationships, and sex. First, participants were asked to select what websites/apps they had ever used for these purposes from the following options: four popular hookup apps for MSM at the time of the study (Grindr, SCRUFF, Jack’d, Adam4Adam); “a social media site or app that is NOT specifically for gay/bisexual guys (e.g., Facebook, Instagram, Twitter, Snapchat, Reddit)”; “a dating site or app that is NOT specifically for gay/bisexual guys (e.g., Tinder, OkCupid, Match.com)”; “not listed”; “I have never used a website/mobile app to meet other guys for dating, romantic relationships, or sex”; and “I do not want to answer.” Those who selected “not listed” were asked to list other websites or apps they had used. For analysis, participants were grouped based on whether they endorsed using any MSM-hookup apps (MSM-app users), using exclusively sites or apps other than MSM-hookup apps (other-app users), and using no apps (non-users). Two items assessed whether participants used these websites or apps to avoid being outed to other people they knew and because they did not know many gay or bisexual men where they lived (1 = strongly disagree; 5 = strongly agree).
Participants who did not report using an MSM-specific app did not receive any other questions about app use and continued to other parts of the survey. MSM-app users were routed to additional items asking for more detail on how they had used the MSM-specific mobile apps (e.g., meeting friends, chatting, having cybersex, meeting guys for sex, finding a boyfriend) and whether they had ever met a man from the apps in person. Those who endorsed meeting a man from an MSM-specific app in person were asked what types of sexual acts, if any, they had engaged in with those men. Finally, those who reported having had anal sex with a partner met from an app were asked about the frequency of sex and condom use with those partners.
Data analysis
We assessed differences in demographics, HIV/STI risk factors, and HIV/STI healthcare engagement by app-use group at the bivariate level using one-way ANOVA and Pearson’s χ2. Among MSM-app users, we similarly assessed group differences between those who had anal sex with a partner met from an app and those who had not. We then conducted a series of multivariable regression models examining the associations between MSM-app use and HIV/STI risk factors and healthcare engagement measures, controlling for age, race/ethnicity, sexual orientation, outness, and sex of sexual partners. The type of regression was matched to the dependent variable structure: negative binomial for counts, linear for continuous, and logistic for binary outcomes. Finally, we conducted the same multivariable analyses with having had anal sex with a partner met from an MSM-specific app as the independent variable.
Results
Participant characteristics are presented in Table 1. Participants ranged in age from 14–17 years old (M age = 16.6) and were ethnically diverse, with 49.0% identifying as a racial/ethnic minority. Most participants identified as male (99.0%) and gay (82.5%), were out to at least one parent (67.5%), and had only male sex partners (80.5%). Thirty-five percent of participants reported ever having an HIV test, and 25.0% reported having an STI test in the past year. Of participants who provided a state of residence (n = 180), participants lived in 49 states reflecting all four geographic regions of the country30 (South 32.2%, West 32.2%, Northeast 18.9%, Midwest 16.7%). Of the 176 participants who provided a valid ZIP code, 91% were in urban areas and 9% were in rural areas. Outcomes did not differ by geographic location or urbanicity.
Table 1.
Descriptive statistics (N = 200)1
| n | % | |
|---|---|---|
| Age (M = 16.64, SD = 0.86) | ||
| 14 | 8 | 4.0 |
| 15 | 27 | 13.5 |
| 16 | 82 | 41.0 |
| 17 | 83 | 41.5 |
| Race/Ethnicity | ||
| White | 102 | 51.0 |
| Black or African American | 9 | 4.5 |
| Hispanic/Latino | 68 | 34.0 |
| Asian | 10 | 5.0 |
| Multiracial | 8 | 4.0 |
| Other | 1 | 0.5 |
| Sexual orientation | ||
| Gay | 165 | 82.5 |
| Bisexual | 26 | 13.0 |
| Pansexual | 6 | 3.0 |
| Queer | 2 | 1.0 |
| Questioning/unsure | 1 | 0.5 |
| Gender identity | ||
| Man | 198 | 99.0 |
| Transgender woman | 2 | 1.0 |
| Outness to parents/guardians | ||
| Not out to parents | 64 | 32.0 |
| Out to one parent, but not all | 26 | 13.0 |
| Out to all parents | 109 | 54.5 |
| Sex of sexual partners | ||
| Only guys | 161 | 80.5 |
| Mostly guys but some girls | 28 | 14.0 |
| Guys and girls equally | 5 | 2.5 |
| Mostly girls but some guys | 6 | 3.0 |
| Types of apps used | ||
| Grindr | 102 | 51.0 |
| Scruff | 11 | 5.5 |
| Jack’d | 10 | 5.0 |
| Adam4Adam | 3 | 1.5 |
| Social media app/site, non-MSM-specific | 102 | 54.0 |
| Dating app/site, non-MSM-specific | 64 | 32.0 |
| Other apps not listed | 40 | 20.0 |
| No apps | 32 | 16.0 |
| MSM-app use | ||
| Used MSM-specific apps | 105 | 53.0 |
| Used only non-MSM-specific apps | 61 | 30.5 |
| Used no apps | 32 | 16.0 |
| Used app to avoid being outed (n = 168) | ||
| Strongly disagree | 63 | 37.5 |
| Disagree | 26 | 15.5 |
| Neither disagree nor agree | 25 | 14.9 |
| Agree | 36 | 21.4 |
| Strongly agree | 16 | 9.5 |
| Used app to meet gay/bisexual guys (n = 168) | ||
| Strongly disagree | 12 | 7.1 |
| Disagree | 6 | 3.6 |
| Neither disagree nor agree | 11 | 6.5 |
| Agree | 61 | 36.3 |
| Strongly agree | 78 | 46.4 |
| MSM-app-use purpose (n = 103) | ||
| Meeting new gay/bisexual friends | 63 | 61.2 |
| Chatting with gay/bisexual friends | 68 | 66.0 |
| Having cybersex with guys | 44 | 42.7 |
| Meeting guys in person for sex | 71 | 68.9 |
| Finding a boyfriend | 51 | 49.5 |
| Other reasons not listed | 6 | 5.8 |
| Ever met a person from app (n = 103) | ||
| Yes, a guy for sex | 69 | 67.0 |
| Yes, a guy I casually dated | 35 | 34.0 |
| Yes, a boyfriend | 26 | 25.2 |
| Yes, a new gay/bisexual friend | 35 | 34.0 |
| I have never met anyone from these apps in person | 18 | 17.5 |
| Sexual acts among MSM-app users (n = 103) | ||
| Hand job | 68 | 66.0 |
| Oral sex | 78 | 75.7 |
| Anal sex | 64 | 62.1 |
| Other type of sexual contact | 14 | 13.5 |
| Anal sex among MSM-app users (n = 103) | ||
| Had anal sex with a partner met off an app | 64 | 62.1 |
| Did not have anal sex with a partner met off an app | 39 | 37.9 |
| Anal sex frequency among MSM-app users (n = 64) | ||
| One time | 14 | 21.9 |
| 2–5 times | 29 | 45.3 |
| 6–10 times | 8 | 12.5 |
| More than 10 times | 13 | 20.3 |
| Anal sex and condom use among MSM-app users (n = 64) | ||
| Always used condoms with anal sex partner from app | 16 | 25.0 |
| Did not always use condoms with anal sex partner from app | 48 | 75.0 |
| HIV/STI Testing | ||
| HIV test (lifetime) | 70 | 35.0 |
| STI test (past year) | 50 | 25.0 |
|
| ||
| M | SD | |
|
| ||
| HIV/STI risk factors | ||
| Number of male sex partners | 3.36 | 4.57 |
| Number of male CAS partners | 1.83 | 2.97 |
| Substance use before sex | 1.56 | 0.92 |
| Perceived risk of HIV | 2.49 | 0.90 |
| HIV/STI healthcare engagement | ||
| Engagement in sexual health services | 1.68 | 0.86 |
Note. AMSM = adolescent men who have sex with men. CAS = condomless anal sex.
Missingness in individual sections due to skip logic and/or participants’ selecting “I do not want to answer”
App engagement and sexual behavior
App use and sexual behaviors are also presented in Table 1. Over half of participants endorsed using Grindr (51.0%); the other three MSM-specific apps were endorsed at substantially lower rates (1.5–5.5%). Over half of participants endorsed using general social media to meet other male partners (54.0%), and approximately one-third endorsed general dating apps (32.0%). Most MSM-app users reported also using other apps not specific to MSM to meet men (67.6%). Of the forty participants (20.0%) who reported using apps or sites that were not listed, the most frequently mentioned venues included sites both specific to (Distinc.tt, n = 8; Hornet, n = 6) and not specific to (MeetMe, n = 6; Craigslist, n = 5) individuals seeking same-sex partners. Overall, 52.5% (n = 105) of participants reported using any type of MSM-specific app for the purposes of meeting partners, 30.0% (n = 60) solely used apps not specific to MSM, and 16.5% (n = 33) did not use any apps for this purpose.
Of the 168 AMSM who reported ever using any apps or websites to meet male partners, the vast majority (82.7%) agreed or strongly agreed that they had used these technologies because of lack of access to same-sex partners, and nearly one third (31.0%) agreed or strongly agreed that they had used these technologies to avoid being outed.
Of the 103 AMSM who reported using one of the four listed MSM-specific apps, the most frequently endorsed reason for using the apps was to meet men in person for sex (68.9%); however, a large percentage of users also endorsed other reasons, including chatting with friends (66.0%), meeting new friends (61.2%), and finding a boyfriend (49.5%). Curiosity was mentioned by three participants in the subsequent free-response item. MSM-app users also reported having a variety of relationships with men met from the apps, including hookups (67.0%), casual dating partners (34.0%), friends (34.0%), and boyfriends (25.2%). Regardless of relationship type, a majority of MSM-app users reported engaging in oral sex (75.7%), hand jobs (66.0%), and anal sex (62.1%) with partners met from the apps. Finally, of the 64 who reported having had anal sex, most had anal sex with the partners more than once (78.1%), and only 25% reported they always used condoms with partners they met through the apps.
Group differences in app engagement & sexual behavior
Group differences among all participants by their level of app engagement (i.e., MSM-app users vs. other-app users vs. non-users) are presented in Table 2. Regarding demographic characteristics, MSM-app users were slightly older, and a larger percentage had exclusively male sex partners relative to other-app users and non-users. Regarding HIV/STI risk factors, MSM-app users reported a greater number of both male sex partners and male CAS partners as well as greater perceived risk of HIV. Non-users reported the greatest proportion of lifetime HIV testing (46.9%), though MSM-app users reported similarly high levels of HIV testing (40.2%). Non-users were not statistically similar to either MSM-app or other-app users and were excluded from further analyses.
Table 2.
Group differences by type of apps used
| MSM-app users (n = 105) n (%) or M (SD) |
Other-app users (n = 61) n (%) or M (SD) |
Non-users (n = 32) n (%) or M (SD) |
Pearson’s χ2 or F | p | |
|---|---|---|---|---|---|
| Demographics | |||||
| Age | 16.82 (0.76) | 16.44 (0.89) | 16.44 (1.01) | F = 5.03 | .007 |
| Racial or ethnic minority | n = 51 (49.0%) | n = 30 (49.2%) | n = 15 (48.4%) | χ2 = 0.005 | .997 |
| Non-gay sexual orientation | n = 14 (13.3%) | n = 17 (27.9%) | n = 4 (12.5%) | χ2 = 6.31 | .051 |
| Out to at least one parent | n = 73 (70.2%) | n = 42 (68.9%) | n = 19 (59.4%) | χ2 = 1.34 | .511 |
| Behaviorally bisexual | n = 14 (13.3%) | n = 18 (29.5%) | n = 7 (21.9%) | χ2 = 6.497 | .039 |
| HIV/STI risk factors | |||||
| Number of male sex partners | 4.51 (5.83) | 2.13 (1.89) | 2.00 (1.92) | F = 7.35 | .001 |
| Number of male CAS partners | 2.40 (3.65) | 1.21 (1.59) | 0.97 (1.72) | F = 4.55 | .012 |
| Substance use before sex | 1.58 (0.82) | 1.63 (0.93) | 1.28 (0.44) | F = 2.13 | .122 |
| Perceived risk of HIV | 2.70 (0.91) | 2.25 (0.79) | 2.22 (0.93) | F = 6.89 | .001 |
| HIV/STI healthcare engagement | |||||
| Engagement in sexual health services | 1.78 (0.91) | 1.51 (0.63) | 1.75 (1.02) | F = 2.01 | .136 |
| HIV test (lifetime) | n = 41 (40.2%) | n = 13 (23.6%) | n = 15 (46.9%) | χ2 = 6.01 | .049 |
| STI test (past year) | n = 25 (23.8%) | n = 13 (21.3%) | n = 11 (34.4%) | χ2 = 2.03 | .363 |
Note. MSM = men who have sex with men. CAS = condomless anal sex.
Group differences among MSM-app users by whether or not they had sex with a partner met from the apps are presented in Table 3. MSM-app users who had anal sex with a partner met from the apps were slightly older, reported a greater number of male sex partners and male CAS partners, and were more likely to report having an HIV test in their lifetime and an STI test in the past year relative to those who did not have anal sex with a partner met from the apps.
Table 3.
Group differences among MSM-app users by anal sex with a partner met from the app
| Yes anal sex (n = 64) n (%) or M (SD) |
No anal sex (n = 41) n (%) or M (SD) |
Pearson’s χ2 or t | p | |
|---|---|---|---|---|
| Demographics | ||||
| Age | 16.95 (0.72) | 16.61 (0.77) | t = −2.31 | .023 |
| Non-White race/ethnicity | n = 31 (48.4%) | n = 20 (50.0%) | χ2 = 0.02 | .877 |
| Non-gay sexual orientation | n = 6 (14.6%) | n = 8 (12.5%) | χ2 = 0.10 | .754 |
| Out to at least one parent | n = 45 (70.3%) | n = 28 (70.0%) | χ2 = 0.00 | .973 |
| Behaviorally bisexual | n = 10 (15.6%) | n = 4 (9.8%) | χ2 = 0.745 | .388 |
| HIV/STI risk factors | ||||
| Number of male sex partners | 6.13 (6.96) | 2.00 (1.23) | t = −4.63 | 0.000 |
| Number of male CAS partners | 3.31 (4.37) | 0.95 (0.93) | t = −4.18 | 0.000 |
| Substance use before sex | 1.65 (0.88) | 1.46 (0.69) | t = −1.20 | 0.235 |
| Perceived risk of HIV | 2.77 (0.90) | 2.60 (0.92) | t = −0.93 | 0.356 |
| HIV/STI healthcare engagement | ||||
| Engagement in sexual health services | 1.84 (0.93) | 1.67 (0.88) | t = −0.93 | 0.357 |
| HIV test (lifetime) | n = 30 (49.2%) | n = 11 (26.8%) | χ2 = 5.10 | 0.024 |
| STI test (past year) | n = 22 (34.4%) | n = 3 (7.3%) | χ2 = 10.09 | 0.001 |
Note. MSM = men who have sex with men. CAS = condomless anal sex.
Associations with HIV/STI risk factors and engagement in healthcare services
Results from the multivariable regression models of HIV/STI risk factors and engagement in sexual healthcare services on MSM-app use are presented in Table 4. After accounting for demographic variables, MSM-app use was associated with having twice as many male sex partners as well as twice as many male CAS partners. MSM-app use was also associated with greater perceived risk of HIV, more engagement in sexual health services, and 2.86 times the odds of ever having received an HIV test.
Table 4.
Adjusted odds ratios, incident rate ratios, regression coefficients, and 95% confidence intervals for the association between MSM-app use and HIV/STI risk factors and healthcare engagement among AMSM (N = 166)
| Correlate | Number of male sex partners1 | Number of male CAS partners1 | Substance use before sex2 | Perceived risk of HIV2 | Engagement in sexual health services2 | HIV test (lifetime)3 | STI test (past year) 3 |
|---|---|---|---|---|---|---|---|
| MSM-app use | 2.07*** | 2.06** | 0.03 | 0.40** | 0.36* | 2.86* | 1.30 |
| [1.50, 2.86] | [1.36, 3.14] | [−0.25, 0.31] | [0.11, 0.69] | [0.09, 0.67] | [1.26, 6.47] | [0.58, 2.92] | |
| Age | 1.11 | 1.14 | 0.02 | 0.01 | −0.10 | 1.15 | 1.12 |
| [0.96, 1.32] | [0.91, 1.42] | [−0.15, 0.19] | [−0.16, 0.19] | [−0.26, 0.06] | [0.73, 1.79] | [0.69, 1.82] | |
| Non-White race/ethnicity | 1.37* | 1.33 | −0.17 | 0.10 | −0.13 | 1.15 | 1.43 |
| [1.034, 1.82] | [0.92, 1.91] | [−0.44, 0.09] | [−0.18, 0.37] | [−0.39, 0.12] | [0.56, 2.33] | [0.67, 3.03] | |
| Non-gay sexual orientation | 0.74 | 0.94 | −0.10 | 0.01 | 0.21 | 1.29 | 1.32 |
| [0.48, 1.15] | [0.55, 1.61] | [−0.50, 0.29] | [−0.40, 0.42] | [−0.17, 0.59] | [0.43, 3.88] | [0.43, 4.06] | |
| Out to at least one parent | 1.07 | 1.15 | 0.09 | 0.01 | 0.41** | 2.49* | 3.12* |
| [0.77, 1.49] | [0.75, 1.78] | [−0.22, 0.41] | [−0.31, 0.34] | [0.11, 0.78] | [1.00, 6.16] | [1.11, 8.77] | |
| Behaviorally bisexual | 1.37 | 1.28 | 0.71*** | −0.22 | 0.08 | 3.17* | 1.93 |
| [.92, 2.06] | [0.77, 2.11] | [0.33, 1.09] | [−0.62, 0.17] | [−0.29, 0.45] | [1.13, 8.88] | [0.69, 5.43] |
Note. AMSM = adolescent men who have sex with men. CAS = condomless anal sex.
Incident Rate Ratios (IRR)
Regression Coefficients (B)
Odds Ratios (OR)
p < .05;
p < .01;
p < .001
In the parallel regression models among MSM-app users (Table 5), having had anal sex with a partner met through an MSM-app was associated with almost three times the number of male sex partners and 3.43 times the number of male CAS partners compared to MSM-app users who had not had anal sex with a partner met through an app, controlling for demographics. Anal sex with a partner met from an MSM-specific app was also significantly associated with 2.60 times the odds of lifetime HIV testing and 9.69 times the odds of past-year STI testing.
Table 5.
Adjusted odds ratios, incident rate ratios, regression coefficients, and 95% confidence intervals for the association between having anal sex with a partner met from an MSM app and HIV/STI risk factors and healthcare engagement among MSM-app users (N = 105)
| Correlate | Number of male sex partners1 | Number of male CAS partners1 | Substance use before sex2 | Perceived risk of HIV2 | Engagement in sexual health services2 | HIV test (lifetime)3 | STI test (past year) 3 |
|---|---|---|---|---|---|---|---|
| Anal sex with partner from MSM-app | 2.97*** | 3.43*** | 0.17 | 0.24 | 0.25 | 2.60* | 9.69** |
| [2.02, 4.38] | [2.10, 5.62] | [−0.17, 0.51] | [−0.15, 0.62] | [−0.12, 0.62] | [1.02, 6.63] | [2.34, 40.04] | |
| Age | 1.10 | 1.076 | −0.09 | 0.01 | −0.18 | 0.98 | 0.56 |
| [0.87, 1.38] | [0.81, 1.42] | [−0.31, 0.13] | [−0.25, 0.26] | [−0.42, 0.06] | [0.54, 1.78] | [0.27, 1.17] | |
| Non-White race/ethnicity | 1.37 | 0.995 | −0.01 | 0.19 | −0.10 | 1.32 | 1.62 |
| [0.97, 1.97] | [0.66, 1.51] | [−0.33, 0.32] | [−0.19, 0.56] | [−0.46, 0.25] | [0.55, 3.15] | [0.59, 4.49] | |
| Non-gay sexual orientation | 0.903 | 1.102 | −0.16 | −0.19 | 0.09 | 0.92 | 0.96 |
| [0.52, 1.58] | [0.58, 2.09] | [−0.68, 0.37] | [−0.79, 0.41] | [−0.48, 0.66] | [0.20, 4.21] | [0.19, 4.91] | |
| Out to at least one parent | 1.025 | 1.04 | 0.21 | 0.04 | 0.66** | 2.84 | 4.18* |
| [0.70, 1.50] | [0.65, 1.66] | [−0.16, 0.57] | [−0.38, 0.46] | [0.26, 1.07] | [0.97, 8.32] | [1.09, 16.00] | |
| Behaviorally bisexual | 0.97 | 1.021 | 0.71** | −0.08 | −0.10 | 3.23 | 1.28 |
| [0.58, 1.63] | [0.56, 1.86] | [0.21, 1.21] | [−0.66, 0.49] | [−0.65, 0.45] | [0.76, 13.84] | [0.30, 5.55] |
Note. MSM = men who have sex with men. CAS = condomless anal sex.
Incident Rate Ratios (IRR)
Regression Coefficients (B)
Odds Ratios (OR)
p < .05;
p < .01;
p < .001
Discussion
To our knowledge, our study is the first to describe the use of MSM-specific hookup apps among a large sample of AMSM. Our findings indicate that, although individuals under age 18 are not permitted to use hookup apps according to the apps’ terms of service, MSM-app use among AMSM is prevalent and may be as normative as among adult MSM. For example, over half of our sample reported using MSM-specific hookup apps, and the percentage of adult MSM-app-users reported in other studies has ranged from 54%9 to 63%.31
While participants in our study most frequently reported using MSM-specific apps to meet partners for sex, a majority also endorsed nonsexual purposes. These reasons for use echo findings among adult samples.2,5,13,32 Many AMSM in our sample also endorsed using general social media and dating sites to meet potential partners. The motivations behind the selection of media may be nuanced: Holloway and colleagues4 reported that among MSM aged 18–24, Grindr, Facebook, and dating sites were more likely used for making new friends, connecting with existing friends, and meeting people for sex, respectively. Future research among AMSM should examine whether they also make such distinctions. Regardless, participants in our sample reported using MSM-apps largely because they felt they lacked access to other MSM nearby, which has been voiced by other samples of sexual minority youth.16 Previous work has demonstrated that the Internet serves multiple functions in the exploration and acceptance of sexual orientation identity, including communicating with and meeting other sexual minorities and connecting with the sexual minority community.17,33 Hookup apps may be another avenue by which AMSM perform normative developmental tasks of adolescence, such as dating and initiating sexual behaviors. AMSM have a smaller pool of potential partners relative to their heterosexual peers due to the smaller size of the sexual minority community, as well as the relative lack of sexual minority male peers who are out in any given school, where youth tend to meet partners.16,34 As such, MSM-specific apps may be one of the few ways in which AMSM can explore relationships with same-sex partners.
The potential benefits of AMSM’s use of hookup apps notwithstanding, MSM-app users engaged in more risky sexual behaviors than their counterparts. Like in adult samples,8,9,11–13 MSM-app use was linked with increased perceived risk of HIV as well as number of total and CAS partners. MSM-apps provide a forum to meet sex partners quickly and easily and communicate specific risk-related desires (e.g., CAS) and sexual expectations. Adolescents may be relatively inexperienced at understanding and negotiating such communication, leading to offline outcomes in which sexual risk may be expected. Conversely, AMSM who engage in risky health behaviors may be more inclined to use MSM-apps that they know to be highly sexualized.3,35 These AMSM could gravitate towards this method of finding partners precisely because of its ease, anonymity, and ability to occlude one’s age. Future research should assess how AMSM’s level of experience with hookup apps contributes to elevated risk perceptions and behaviors.
Regardless of the reasoning behind the increased risk, the data suggest that AMSM may be aware of their risk-taking behavior and utilize sexual health services accordingly. Similar to findings from adult samples,31 youth who used MSM-specific apps reported greater odds of HIV testing and more use of sexual health services compared to peers who only used other apps. That both risk and health engagement behaviors were similarly increased among AMSM who had had anal sex with a partner met from an MSM-app relative to those who had not further corroborates the impression that AMSM’s sexual risk-taking is not a function of naivety. Increased testing and use of sexual health services could be linked to the fact that sexual health outreach is increasingly common on MSM-specific apps, and the fact that user profiles often describe sexual health information such as last HIV testing date and PrEP use.
Last, there are other public health implications from our findings beyond adolescents’ sexual risk-taking behavior. As our results suggest that underage MSM-app use is not uncommon, strategies that increase the safety of both adolescent and legal adult users are needed. AMSM hookup app users may post personal information and share sexually explicit pictures of themselves, but youth could be prosecuted for sexting pictures of themselves to potential partners. Adult users, who may knowingly or unknowingly interact with AMSM online, may risk greater legal consequences should their interactions escalate to sexual contact offline. Finally, AMSM who meet adult partners online could be at higher risk of sexual victimization and HIV infection associated with age-discrepant sexual relationships.36,37
Limitations
Our study was not without limitations. First, we used a cross-sectional design with a moderately-sized sample of AMSM, which precludes our drawing causal links and hinders our ability to generalize to larger populations. Second, while the age range for inclusion was 14–17 years, most participants were between the ages of 16–17, and it is unclear whether younger adolescent MSM-app users’ behaviors differ. Third, we recruited participants primarily from Facebook and Instagram, and it is possible these youth may differ from those recruited from MSM-apps or the community. Fourth, our measures may have been a limiting factor. For example, we did not assess the nature of participants’ relationships with the partners they met through the apps, which may influence inconsistent condom use if the relationships are romantic or known partners.38 Finally, these items were embedded within a larger survey, and we were limited in the depth of information we were able to obtain about hookup app use among AMSM. Nevertheless, these results provide an initial glance into a phenomenon that warrants future research.
Future directions
While our findings paint a preliminary picture of hookup app use and sexual behavior among AMSM, other important questions remain about the perceived risks and benefits of using hookup apps, AMSM’s self-presentation in these venues,39 and youth’s decision making around the trustworthiness of others’ profiles.40 In addition, the types of partners met from hookup apps and whether and how AMSM navigate sexual consent discussions with adult partners should be explored. Given the now-normative nature of hookup apps among adolescent and adult MSM, implementing stricter policies is likely to be ineffective in preventing AMSM’s access to these apps. Thus, future studies should also examine the potential role of hookup apps as a context for HIV prevention and testing among AMSM41 and the education needed for AMSM to navigate such apps safely. To the former, MSM-apps could be a forum through which to educate young users about HIV risk behaviors and sexual health responsibilities (e.g., condom use, PrEP uptake and adherence, serostatus assumptions). However, this must be preceded by education about navigating online interactions, dating, and sex to protect themselves from negative encounters that may stem from such venues. As the internet and connected technologies evolve further, continued attention to how young people adopt new media is critical.
Implications and contributions.
This study examined and demonstrated normative use of MSM-specific geosocial networking applications among adolescent men who have sex with men, which has ethical, legal, and sexual health considerations. Education on how to navigate such online environments as well as HIV/STI prevention and testing are critical.
Acknowledgments
This research was supported by the National Institute on Minority Health and Health Disparities of the National Institutes of Health under awards R01MD009561 (PIs: Mustanski & Fisher) and U01MD011281 (PI: Mustanski). This content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Selected findings from this study were presented at the 2017 meeting of the International Academy of Sex Research, Charleston, SC, USA.
Abbreviations
- MSM
men who have sex with men
- AMSM
adolescent men who have sex with men
- HIV
human immunodeficiency virus
- STI
sexually transmitted infections
Footnotes
Conflicts of Interest: The authors have no conflicts of interest relevant to this article to disclose. The study sponsor was not involved in study design, collection, analysis, or interpretation of data, the writing of this report, or the decision to submit this manuscript for publication. Kathryn Macapagal, David Moskowitz, Dennis Li, and Andres Carrion wrote the first draft of the manuscript and were not given honoraria to produce this manuscript.
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References
- 1.Choi EPH, Wong JYH, Fong DYT. The use of social networking applications of smartphone and associated sexual risks in lesbian, gay, bisexual, and transgender populations: a systematic review. AIDS Care. 2017 Feb;29(2):145–155. doi: 10.1080/09540121.2016.1211606. [DOI] [PubMed] [Google Scholar]
- 2.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. doi: 10.2196/publichealth.4353. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Paz-Bailey G, Hoots BE, Xia M, et al. Trends in Internet Use Among Men Who Have Sex With Men in the United States. J Acquir Immune Defic Syndr. 2017 Jul 1;75(Suppl 3):S288–S295. doi: 10.1097/QAI.0000000000001404. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.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 Feb;18(2):285–296. doi: 10.1007/s10461-013-0671-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Macapagal K, Coventry R, Puckett JA, Phillips G, Mustanski B. Geosocial Networking App Use Among Men Who Have Sex With Men in Serious Romantic Relationships. Archives of Sexual Behavior. 2016 Aug;45(6):1513–1524. doi: 10.1007/s10508-016-0698-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Van De Wiele C, Tong ST. Breaking boundaries: The uses and gratifications of Grindr. Paper presented at: ACM International joint Conference on Pervasive and Ubiquitous Computing; 2014; New York, NY. [Google Scholar]
- 7.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 Mens Health. 2014 Nov;8(6):510–520. doi: 10.1177/1557988314527311. [DOI] [PubMed] [Google Scholar]
- 8.Landovitz RJ, Tseng CH, 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 Urban Health. 2013 Aug;90(4):729–739. doi: 10.1007/s11524-012-9766-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Lehmiller JJ, Ioerger M. Social networking smartphone applications and sexual health outcomes among men who have sex with men. PLoS One. 2014;9(1):e86603. doi: 10.1371/journal.pone.0086603. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.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 Nov;90(7):567–572. doi: 10.1136/sextrans-2013-051494. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Holloway I, Pulsipher C, Gibbs J, Barman-Adhikari A, Rice E. Network Influences on the Sexual Risk Behaviors of Gay, Bisexual and Other Men Who Have Sex with Men Using Geosocial Networking Applications. AIDS and Behavior. 2015 Jan 09;2015:1–11. doi: 10.1007/s10461-014-0989-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.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 Oct;26(10):1303–1308. doi: 10.1080/09540121.2014.911811. [DOI] [PubMed] [Google Scholar]
- 13.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. Journal of AIDS & Clinical Research. 2012;1(S4):1–8. [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 Jan;18(1):41–49. doi: 10.1007/s10461-013-0573-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Toutant C. Grindr fights claims it failed to block underage member. New Jersey Law Journal. 2014 http://www.njlawjournal.com/id=1202666572738/Grindr-Fights-Claims-It-Failed-to-Block-Underage-Member?slreturn=20170122153052.
- 16.DuBois LZ, Macapagal KR, Rivera Z, Prescott TL, Ybarra ML, Mustanski B. To have sex or not to have sex? An online focus group study of sexual decision making among sexually experienced and inexperienced gay and bisexual adolescent men. Arch Sex Behav. 2015 Oct;44(7):2027–2040. doi: 10.1007/s10508-015-0521-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Harper GW, Serrano PA, Bruce D, Bauermeister JA. The Internet’s Multiple Roles in Facilitating the Sexual Orientation Identity Development of Gay and Bisexual Male Adolescents. Am J Mens Health. 2016 Sep;10(5):359–376. doi: 10.1177/1557988314566227. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Steinberg L. A social neuroscience perspective on adolescent risk-taking. Developmental Review. 2008 Mar;28:78–106. doi: 10.1016/j.dr.2007.08.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Rice E, Winetrobe H, Holloway IW, Montoya J, Plant A, Kordic T. Cell phone internet access, online sexual solicitation, partner seeking, and sexual risk behavior among adolescents. Arch Sex Behav. 2015 Apr;44(3):755–763. doi: 10.1007/s10508-014-0366-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Ybarra ML, Mitchell KJ. A National Study of Lesbian, Gay, Bisexual (LGB), and Non-LGB Youth Sexual Behavior Online and In-Person. Arch Sex Behav. 2016 Aug;45(6):1357–1372. doi: 10.1007/s10508-015-0491-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Mustanski B. Ethical and regulatory issues with conducting sexuality research with LGBT adolescents: a call to action for a scientifically informed approach. Arch Sex Behav. 2011 Aug;40:673–686. doi: 10.1007/s10508-011-9745-1. [DOI] [PubMed] [Google Scholar]
- 22.CDC. [Accessed 2 February 2016];HIV Surveillance - adolescents and young adults through 2014. 2016 6(7):43. http://www.cdc.gov/hiv/pdf/library/slidesets/cdc-hiv-surveillance-adolescents-young-adults-2014.pdf. [Google Scholar]
- 23.CDC. New HIV Infections in the United States. Atlanta: National Center for HIV/AIDS, Viral Hepatitis, STD and TB Prevention; 2016. [Google Scholar]
- 24.Mustanski B, Coventry R, Macapagal K, Arbeit MR, Fisher CB. Sexual and gender minority adolescents’ views on HIV research participation and parental permission: A mixed-methods study. Perspect Sex Reprod Health. 2017 Jun;49(2):111–121. doi: 10.1363/psrh.12027. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Macapagal K, Coventry R, Arbeit MR, Fisher CB, Mustanski B. “I won’t out myself just to do a survey”: Sexual and gender minority adolescents’ perspectives on the risks and benefits of sex research. Archives of Sexual Behavior. 2016 doi: 10.1007/s10508-016-0784-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Fisher CB, Arbeit MR, Dumont MS, Macapagal K, Mustanski B. Self-consent for HIV prevention research involving sexual and gender minority youth: Reducing barriers through evidence-based ethics. Journal of Empirical Research on Human Research Ethics. 2016;11(1):3–14. doi: 10.1177/1556264616633963. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Grey JA, Konstan J, Iantaffi A, Wilkerson JM, Galos D, Rosser BR. An updated protocol to detect invalid entries in an online survey of men who have sex with men (MSM): how do valid and invalid submissions compare? AIDS Behav. 2015 Oct;19(10):1928–1937. doi: 10.1007/s10461-015-1033-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Napper LE, Fisher DG, Reynolds GL. Development of the perceived risk of HIV scale. AIDS Behav. 2012 May;16(4):1075–1083. doi: 10.1007/s10461-011-0003-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Fisher CB, Fried AL, Desmond M, Macapagal K, Mustanski B. Facilitators and Barriers to Participation in PrEP HIV Prevention Trials Involving Transgender Male and Female Adolescents and Emerging Adults. AIDS Educ Prev. 2017 Jun;29(3):205–217. doi: 10.1521/aeap.2017.29.3.205. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.CDC. HIV Surveillance Report, 2016. Nov, 2017. [Google Scholar]
- 31.Phillips G, 2nd, Magnus M, Kuo I, et al. Use of Geosocial Networking (GSN) Mobile Phone Applications to Find Men for Sex by Men Who Have Sex with Men (MSM) in Washington, DC. AIDS Behav. 2014 Sep;18(9):1630–1637. doi: 10.1007/s10461-014-0760-9. [DOI] [PubMed] [Google Scholar]
- 32.Gudelunas D. There’s an App for that: The Uses and Gratifications of Online Social Networks for Gay Men. Sexuality & Culture. 2012 Dec 01;16(4):347–365. [Google Scholar]
- 33.Craig SL, McInroy L. You Can Form a Part of Yourself Online: The Influence of New Media on Identity Development and Coming Out for LGBTQ Youth. Journal of Gay & Lesbian Mental Health. 2014 Jan 01;18(1):95–109. [Google Scholar]
- 34.Mustanski B, Birkett M, Greene GJ, Hatzenbuehler ML, Newcomb ME. Envisioning an America without sexual orientation inequities in adolescent health. Am J Public Health. 2014 Feb;104(2):218–225. doi: 10.2105/AJPH.2013.301625. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Downing MJ. Using the Internet in Pursuit of Public Sexual Encounters: Is Frequency of Use Associated With Risk Behavior Among MSM? American Journal of Mens Health. 2012 Jan;6(1):18–27. doi: 10.1177/1557988311407906. [DOI] [PubMed] [Google Scholar]
- 36.Chamberlain N, Mena LA, Geter A, Crosby RA. Is sex with older male partners associated with higher sexual risk behavior among young Black MSM? AIDS & Behavior. 2017 Jan 31; doi: 10.1007/s10461-017-1699-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Guadamuz TE, Wimonsate W, Varangrat A, et al. Correlates of forced sex among populations of men who have sex with men in Thailand. Arch Sex Behav. 2011 Apr;40(2):259–266. doi: 10.1007/s10508-009-9557-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Sullivan PS, Salazar L, Buchbinder S, Sanchez TH. Estimating the proportion of HIV transmissions from main sex partners among men who have sex with men in five US cities. AIDS. 2009 Jun 1;23(9):1153–1162. doi: 10.1097/QAD.0b013e32832baa34. [DOI] [PubMed] [Google Scholar]
- 39.Blackwell C, Birnholtz J, Abbott C. Seeing and being seen: Co-situation and impression formation using Grindr, a location-aware gay dating app. New Media Soc. 2015 Aug;17(7):1117–1136. [Google Scholar]
- 40.Corriero EF, Tong ST. Managing uncertainty in mobile dating applications: Goals, concerns of use, and information seeking in Grindr. Mobile Media & Communication. 2016;4(1):121–141. [Google Scholar]
- 41.Jenkins Hall W, Sun CJ, Tanner AE, Mann L, Stowers J, Rhodes SD. HIV-prevention opportunities with GPS-based social and sexual networking applications for men who have sex with men. AIDS Education and Prevention. 2017 Feb 01;29(1):38–48. doi: 10.1521/aeap.2017.29.1.38. [DOI] [PMC free article] [PubMed] [Google Scholar]