Abstract

Child identity fraud, or the criminal exploitation of a child's personal data, poses serious risks and challenges for youth in foster care. Despite the 10-year history of a federal mandate requiring state child welfare agencies to conduct annual credit checks for adolescent foster youth (42 U.S.C. § 675), identity fraud has received scant attention in child welfare research. Analyzing a state-level administrative dataset with linked child welfare and consumer credit records, we employed hierarchical binary logistic regression modeling to analyze demographic and foster care placement factors associated with identity fraud victimization among a statewide population cohort of 1176 youth (age 14-17) in foster care in a mid-Atlantic state. In the model of best fit, covariates significantly associated with differing odds of identity fraud victimization included African American race (OR = 2.67, p < .001); two or more races (OR = 2.95, p = .003); and older age at credit check (OR = 3.49, p < .001). Youth with history of prior home removals (OR = 1.59, p = .059) were marginally more likely than youth with no prior home removals to experience identity fraud, controlling for all other variables.

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