Does Cyber Hit Harder?: Factor Structure and Differential Longitudinal Outcomes of Victimization

Introduction: Increases in the use of electronic communication technologies have led to extensive growth in research on the prevalence and frequency of cybervictimization and its association with psychosocial adjustment. Although cybervictimization occurs less frequently than in-person victimization experiences, researchers have argued for a continued focus on cybervictimization given its potential for greater harm. Currently, major gaps in the field of cybervictimization research include the lack of rigorous measure development studies needed to test theoretical models of victimization, a cross-sectional approach rather than a longitudinal approach to examining outcomes, and a focus on cybervictimization outcomes without taking into account the broader context of peer victimization experiences. The purpose of this study was to test the factor structure of victimization and to use a longitudinal design to explore differential outcomes of cybervictimization and in-person victimization. It was hypothesized that cybervictimization would emerge as a unique form of victimization and that there would be no differences between the extent to which in-person victimization and cybervictimization predicted adolescents’ adjustment.

Method: Participants were 1,628 sixth, seventh, and eighth grade students from three public schools in a medium-sized city in the southeastern United States. The racial composition of the sample was predominantly Black or African American. Nineteen percent of participants reported that their ethnicity was Hispanic or Latino. Data were collected in the fall, winter, spring, and summer beginning in the fall of 2015. Participants who had completed at least two waves of data prior to the winter of 2017 were included in the study. Participants reported on their physical, verbal, relational, and cyber victimization, as well as their overt, relational, and cyber aggression; delinquency; substance use; academic motivation; and subjective distress.

Results: Confirmatory factor analyses found support for distinct factors representing in-person and cyber victimization. This model was consistent across gender. Longitudinal data analyses across four waves of data are being conducted to determine whether in-person victimization and cybervictimization differentially predict adolescents’ adjustment (aggression, delinquency, substance use, academic motivation, and subjective distress).

Conclusions: This study supports a theoretical model of victimization in which cybervictimization represents a distinct form of victimization. The results of the longitudinal analyses will inform the current debate in the literature about whether cybervictimization leads to greater harm than does in-person victimization for a range of outcomes of interest.