Refining social-information processing theory: Predicting maternal and paternal parent-child aggression risk longitudinally

Abstract

BackgroundClarifying the pathways leading parents to engage in parent-child aggression (PCA) would benefit child abuse prevention efforts during the perinatal period. ObjectiveThe present investigation empirically tested whether a social information processing (SIP) model could predict PCA risk from factors assessed in new mothers and fathers. Participants and SettingThis study recruited a diverse sample of 201 primiparous mothers in the last trimester of their pregnancy along with 151 fathers. MethodsUsing a prospective longitudinal study, the hypothesized SIP model was refined statistically using SIP factors measured prenatally to predict PCA risk when their children were 18 months. This refined model was then validated with SIP factors assessed when infants were 6 months to predict PCA risk when toddlers were 18 months. ResultsIn general, findings indicated poor empathy related to greater overreactivity and more negative child behavior attributions. Moreover, approval of PCA use, negative child attributions, less knowledge of non-physical discipline alternatives, and higher child compliance expectations predicted subsequent PCA risk. The proposed SIP model for mothers demonstrated considerable stability. Although SIP processes predicted paternal risk, several SIP relations changed over time for fathers. ConclusionsFindings suggest comprehensive theoretical models like SIP theory can guide the specific processes to target for prevention and clarify how processes may be interconnected. SIP processes appear relevant and relatively stable targets for prevention and early intervention, particularly for mothers. SIP processes were applicable for fathers although the model was less consistent, suggesting work in examining paternal PCA risk remains an important research direction.