Method: 958 adolescents from 7 public high schools in Texas participated in the study over four years. At baseline, the sample was 57% female with a mean age of 16.1. Approximately one third of participants self-identified as Hispanic, White, or African American. Psychological abuse victimization was measured using the Conflict in Adolescent Dating Relationships Inventory (Wolfe et al., 2001) at waves 2, 3, and 4. Cyber dating abuse (Zweing et al., 2013; Picard, 2007) was measured at waves 4 and 5. We used growth curve modeling to examine how change and initial level of psychological victimization at wave 2 predicted cyber dating abuse at wave 4 and wave 5. Gender, ethnicity, and parental education were included in the models as time-invariant covariates. Because cyber DV victimization and perpetration were positively skewed, maximum likelihood estimator with robust standard errors (MLR) was employed in Mplus 7.11.
Results: The growth curve model was acceptable: (χ2 [21] = 64.27.73, p = <.05; RMSEA = 0.05, 90% CI = .035, .063; CFI =.95; SRMR= .04). Positive linear trend of psychological victimization was related to cyber dating abuse victimization (b=1.12, SE=0.25, p<.001) and perpetration (b=1.74, SE=0.34, p<.001) at wave 4, whereas the level of psychological abuse at wave 2 was not related to cyber dating abuse at wave 4 or wave 5. Perpetration of cyber dating abuse at wave 4 was positively related to cyber dating abuse victimization (b=.74, SE=.31, p<.05) and perpetration (b=.55, SE=.23, p<.05) at wave5.
Conclusion: Findings provide evidence suggesting that psychological abuse victimization may serve as a catalyst for the development of cyber dating abuse. It is becoming increasingly clear that the line separating adolescents’ online and offline lives is becoming blurred. In order to be effective, dating violence prevention and intervention programs must target both traditional and cyber forms of dating abuse.