Relationship Between Variables
Finally, we did not identify significant relationships between app-use related variables and sociodemographic characteristics such as sexual orientation, ethnicity, nationality, education level, and religious practicing. Nevertheless, our findings suggest that participants in cohabiting relationships had a higher number of fulfilled expectations compared to those in non-cohabiting relationships and those who were single. Previous studies in the U.S. and Brazil have indicated that partnered men commonly use GSN apps as ways to satisfy sexual and social gratifications, and experience relational benefits and costs as a consequence of their app use (Goedel Duncan, 2015; Macapagal et al., 2016; Queiroz et al., 2019). One explanation is that participants who reported being in cohabiting relationships were able to meet their romantic partners through apps, thus increasing the number of fulfilled expectations to the men in other groups. However, it is necessary to conduct further studies to reach tendermeets more accurate conclusions. Also, we found that participants’ apps experiences vary based on their monthly income levels; SMM with lower earnings had more unfulfilled expectations than those with higher ones. Following previous statements on GSN apps as environments that reproduce power differences among members of the queer community (e.g., White, masculine, fit, rich; Miller, 2015a), men with lower incomes may have higher difficulties meeting expectations when interacting with men who seek certain characteristics in others.
Limitations and Future Studies
This study had several limitations. First, the instrument employed was developed by the authors to gather information in Ecuador, a country in which no study on SMM’s GSN app use and experiences had been conducted. This situation may bring questions on the content validity of the instrument. To ensure that our instruments were sensitive to the context, we constructed a survey that was reviewed by four experts in the field of sexuality, sexual health, and gender issues. While we believe this helped us develop an instrument that gathered pertinent and useful information, we believe that future studies should revise some of its aspects. We believe it would be of great use for future studies to explore the participant’s perceptions and behaviors separately. This would help better identify the gratifications sought and met in SMM-specific apps versus other non-SMM specific apps and other social media.
Also, we used online snowball sampling methods to recruit our participants. To avoid invading people’s privacy, we decided not to create a profile inside each of the apps to promote the study. However, the use of this sampling method can have consequences in terms of the underrepresentation of certain sociodemographic groups (e.g., Black, Indigenous SMM) (Burrell et al., 2012; Sullivan et al., 2011). Thus, future studies could try to recruit app users directly. Also, despite not recognizing any potential cases, researchers should take precautions to avoid repeated entries during data collection.
Future studies should attempt to gather a bigger and more representative sample. In this study, we were able to recruit a sample comprised of mainly gay, single, cisgender, multiracial men in their mid-20’s. Despite this being probably the average characteristics of men using apps in the country, experiences of app users may vary widely according to their age, ethnicity, gender identity, sexual orientation, and relationship status. Future research should consider ways to locate more diverse populations and analyze their experiences using apps.
Despite its limitations, this research has allowed us to gather a broad perspective of GSN app use and its importance for SMM in a country where research is still limited. Future studies could examine possible differences in app-use related variables based on the main app used, type of app (i.e., SMM-specific vs. non-SMM specific), age group, ethnicity, religious affiliation, religiosity, and current relationship status. For example, expectations, support, and discrimination experiences ong younger and older cohorts, as well as those who are in a stable relationship, and those who are not. Larger samples, with higher heterogeneity in these variables, would allow making these comparisons.