An Examination of the Factors Related to Dating Violence Perpetration Among Young Men and Women and Associated Theoretical Explanations: A Review of the Literature

This article provides a review of the literature on dating violence (DV) perpetration, specifically sex similarities and differences in the correlates and predictors of DV perpetration and the utility of current theories to explain young men's and women's DV perpetration. Overall, many of the correlates and predictors of DV perpetration are similar among young men and women (e.g., witnessing interparental violence, experiencing child abuse, alcohol abuse, traditional gender roles, relationship power dynamics). However, young women's perpetration of DV is more strongly related to internalizing symptoms (e.g., depression), trait anger and hostility, and experiencing DV victimization than young men's perpetration, whereas young men's perpetration of DV is more consistently related to lower socioeconomic status and educational attainment, antisocial personality characteristics, and increased relationship length than young women's perpetration. Each theory offers insights into but does not fully account for the correlates and predictors of DV perpetration. Sociocultural theories may be useful in explaining the use of coercive control in relationships, and learning/intergenerational transmission of violence theories may be useful in explaining bidirectional couple violence. Future research should focus on integrative theories, such as in the social-ecological theory, in order to explain various forms of DV. Our understanding of young men's and young women's DV perpetration is limited by cross-sectional research designs, methodological inconsistencies, a lack of sex-specific analytic approaches, and a lack of focus on contextual factors; more multivariate and longitudinal studies are needed. Further, as DV prevention programming is often presented in mixed-sex formats, a critical understanding of sex differences and similarities in DV perpetration could ultimately refine and improve effectiveness of programming efforts aimed at reducing DV.