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Predicting Maternal and Paternal Parent-Child Aggression Risk: Longitudinal Multimethod Investigation Using Social Information Processing Theory.

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Psychology of Violence

Published online on

Abstract

Objective: Given the costly outcomes associated with the physical abuse and harsh discipline of children, identifying pathways leading parents to engage in parent–child aggression (PCA) are critical to prevention and intervention efforts. One model that attempts to identify the processes involved in increasing parents’ risk is an adaptation of Social Information Processing (SIP) theory. The current study investigated whether elements of SIP theory assessed prenatally can predict later PCA risk in a diverse sample of mothers and fathers. Method: This evaluation controlled for parents’ current level of personal vulnerabilities (psychopathology, substance use, domestic violence) or resiliencies (social support, partner satisfaction, coping) to determine the predictive value of the SIP processes in particular. This study used a multimethod approach that included several analog tasks. Dyadic analyses were conducted to contrast 196 mothers and their partners who were enrolled prenatally and then reassessed when their infants were 6 months old. Results: Findings indicate that poor empathy assessed prenatally was associated with greater overreactivity and more negative attributions regarding children’s behavior, which in turn predicted later PCA risk. Moreover, attitudes approving the use of PCA predicted later PCA risk largely due to its connection with negative child attributions, less knowledge of nonphysical discipline alternatives, and higher compliance expectations. Conclusions: The results suggest that elements of the SIP theory can be identified prenatally to estimate later risk of PCA, with some differences in profiles between mothers and fathers. Future directions for evaluating the SIP model and its implications for prevention and intervention are discussed. (PsycINFO Database Record (c) 2017 APA, all rights reserved)