Exploring Empathy and Callous–unemotional Traits as Predictors of Animal Abuse Perpetrated by Children Exposed to Intimate Partner Violence

Publication Date

7-25-2016

Document Type

Article

Organizational Units

Graduate School of Social Work

Keywords

Affective empathy, Animal cruelty, Callous–unemotional traits, Child animal abuse, Cognitive empathy.

Abstract

We explored the relation between empathy, callous-unemotional (CU) traits, and animal abuse in a sample of 290 seven- to twelve-year-old children whose mothers were exposed to intimate partner violence (IPV). The sample comprises mostly Latino and White participants, and 55% of the children's mothers were born outside the United States (primarily Mexico). To our knowledge, among studies examining child-perpetrated animal abuse, this study is the first to examine empathy levels and one of only a few to examine CU traits. When comparing Griffith Empathy Measure (empathy) and Inventory of Callous-Unemotional Traits (callous-unemotional [CU] traits) scores with those from studies of White schoolchildren, our sample scored lower on affective empathy, higher on cognitive empathy, and lower for overall CU scores as well as Callous and Unemotional subscales. Of 290 children, 47 (16.2%) harmed an animal at least once according to either mother or child report. There were no significant sex or age differences between Abuse and No Abuse groups. The Abuse group scored significantly higher on affective empathy, CU, and Callousness/Unemotional subscales, and significantly lower on cognitive empathy. However, in regression analyses that controlled for income, only lower cognitive empathy and higher CU significantly predicted having abused an animal. In summary, low cognitive empathy (but not affective empathy) and CU traits may serve as reliable predictors of child animal abuse. However, replication of these results is necessary. A larger sample with a high percentage of Latino children whose mothers were exposed to IPV, along with a non-exposed comparison group, would be ideal.

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