Predicting the recurrence of child abuse

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Abstract
Funding cuts are forcing protective service agencies to serve only the most serious cases of child abuse among the over 200,000 reported nationally each year. A good indication of the seriousness of a case is the likelihood of repeated abuse. This article describes a study to determine the predictability of repeated abuse by analyzing the relationship of recurrent abuse to case characteristics. The resultant statistical model predicted the recurrence of abuse with 74 percent accuracy. The authors discuss their findings in relation to improving the allocation of resources in protective service agencies.

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