School of Behavioral Sciences
Master of Science in Psychology (MS)
Online sexual victimization, sexting, online sexual solicitations, online sexual interactions, risky online behaviors, sexual exploitation
Psychology | Sociology
Knight, Tianna Joy, "Predicting Online Sexual Victimization Among College Students: Sexting, Solicitations, and Other Risky Online Behaviors" (2022). Masters Theses. 839.
With the high prevalence rates of internet usage and smartphone ownership, risky online behaviors have become more and more widespread. These behaviors include sexting, online sexual solicitations, and online sexual interactions. Research indicates that these risky behaviors are related to online sexual victimization (OSV). OSV has been associated with poorer mental health, loneliness, lower life satisfaction, and other negative outcomes. Another phenomenon linked to OSV and sexting is sexual exploitation, but no study has yet analyzed the predictive ability of beliefs and awareness about sexual exploitation and human trafficking on OSV. Optimism bias, or the tendency to think that one’s chances of experiencing a negative event are less than the average person’s chances, is a bias that is related to one’s own risky behaviors, but no research has looked at its connection with OSV and sexting. The purpose of this study was to analyze the ability of sexting, online sexual solicitations, online sexual interactions, optimism bias, attitudes about human trafficking, social media, and the amount of time one spends on their cell phone and the internet to predict OSV. This project analyzed self-reported levels of OSV, sexting, online sexual solicitations, online sexual interactions, optimism bias, human trafficking myth acceptance, number of social media platforms, time spent on the internet, and cell phone screen time among a sample of undergraduate university students (N = 458). Independent samples t-tests were conducted to compare males and females. A multiple linear regression was conducted using the eight variables as predictors of OSV, and then a regression with a reduced model was conducted with only five predictors. Males reported higher levels of sexting than females, and females reported spending more time online than males. The regression analysis revealed that the model explained 60% of the variance in OSV scores. Based on the β weights, squared structure coefficients, and p values, sexting and solicitations were the strongest predictors of OSV. The reduced model, which excluded cell phone screen time, internet time, and optimism bias, also explained 60% of the variance in OSV scores. Findings indicate strong predictive abilities of sexting and solicitations on OSV experience, expanding the current understanding of OSV and its predictors. Future research should aim to further analyze the individual predictors as well as determining the direction of these relationships.