Addictive Behaviors
Miguel A. Garcia, B.A.
Graduate Research Assistant
The University of Texas at El Paso
El Paso, Texas
Anna Ziencina, M.A.
Graduate Research Assistant
The University of Texas at El Paso
El Paso, Texas
Ariana Cervantes-Borges, M.A.
Graduate Research Assistant
The University of Texas at El Paso
El Paso, Texas
Andrea Rodriguez-Crespo, B.S.
Graduate Research Assistant
The University of Texas at El Paso
El Paso, Texas
Angelica Aguirre, None
Research Assistant
The University of Texas at El Paso
El Paso, Texas
Theodore V. Cooper, Ph.D.
Associate Professor
The University of Texas at El Paso
El Paso, Texas
Online social experiences have become increasingly common in recent years given the rise in social media users (Statista, 2022). Past research has focused largely on how social media use frequency and addiction relate with mental and sleep health (e.g., Mathis et al., 2021), yet fewer studies have investigated how one’s perceived experiences with social media relate with mental and sleep health. Investigating these relationships among Hispanics is vital given that Hispanic groups suffer from sleep disparities (Roncoroni et al., 2022). Additionally, emerging adults are at increased risk for mental illness (National Institute of Mental Health, 2022) and are using social media at striking rates (Lerma et al., 2021). Thus, the aim of the present study was to assess how online social support and online social negativity relate with depression, anxiety, stress, and sleep quality in Hispanic emerging adults.
Self-identified Hispanic emerging adult college students (n=304) from a Hispanic Serving Institution (Mage=19.75 years, SD=1.73; 79.3% female) were recruited via SONA, a web-based recruitment system. After signing an electronic consent form, participants completed a survey assessing sociodemographics, social media use frequency, online social experiences, depression, anxiety, stress, and sleep quality. Four multiple linear regressions assessed the relationships between depression, anxiety, stress, and sleep quality with online social positivity and online social negativity while controlling for age, sex, and social media use frequency.
The regression model assessing depression was statistically significant (F(5,268)=7.771, R2=.129, p< .001); depression was positively associated with online social negativity (b =.327, p< .001). The regression model assessing anxiety was statistically significant (F(5,266)=6.429, R2=.110, p< .001); anxiety was positively associated with online social negativity (b =.304, p< .001). The regression model assessing stress was statistically significant (F(5,268)=8.957, R2=.146, p< .001); stress was positively associated with age (b =.124, p=.032) and online social negativity (b =.320, p< .001). The regression model assessing sleep quality was statistically significant (F(5,245)=5.234, R2=.098, p< .001); poor sleep quality was positively associated with online social negativity (b =.270, p< .001).
Findings primarily suggest that online social negativity was positively associated with depression anxiety, stress, and poor sleep quality. That online social negativity was positively associated with negative affect indicates that negatively perceived experiences on social media (e.g., feeling rejected or embarrassed online) may lead to negative affect or that negative affect may lead one to interpret their online social experiences more negatively. Similarly, online social negativity may lead to poor sleep quality, as one may have trouble sleeping from ruminating about their adverse online interactions. Due to the cross-sectional design of the present study, future prospective studies that determine the temporality of these observed relationships are warranted. Presently, it may be prudent to develop interventions that target how one can reduce online social negativity.