Identifying Child Abusers: Defeating Their Efforts to “Fake Good”

When child abuse is suspected, parents and/or caregivers may be referred for evaluation by professionals. In addition to an interview, a variety of tests can be used to help differentiate abusers from non-abusers. However, potential abusers are likely motivated to respond to items in a manner that they feel will produce a positive perception of their overall caregiving, rather than answering honestly. This is an example of the Social Desirability Bias. On existing measures, such as the widely-administered Child Abuse Potential Inventory (CAPI), it may be fairly obvious to a participant what each item attempts to measure. Therefore, a participant may be motivated to respond in a socially desirable manner. We often refer to this behavior as “faking good”. To address this, a measure called the Child Guidance Inventory (CGInv) is being developed. The CGInv presents participants with specific scenarios involving problematic child behaviors. The participants are then asked to rate responses that represent how they might react. The CGInv is intended to produce information about maladaptive parenting practices in three areas: Rejection, Chaos and Coercion. These areas have been identified as the three major subcategories of maladaptive caregiving by the Parenting as Social Context Questionnaire (PASCQ) scale. A previous study of a first version of the CGInv indicated that it did not accurately distinguish between abusers and non-abusers. The measure has since been modified to include more scenarios with more comprehensive, subtle response options. Administered along with the PASCQ, individuals are instructed to “fake good” or “answer honestly” in order to test the possibility that the “fake good” motivation is defeated. It is predicted that the current CGInv will neutralize the effect of the social desirability bias on participants, potentially resulting in more accurate identification of child abusers over and above the results of the existing, standardized CAPI