Community Factors in Differential Responses of Child Protective Services
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Abstract
Child maltreatment results in over 3 million referrals annually to U. S. child protective services agencies and an estimated 695,000 children who are determined to be child maltreatment victims. There are ongoing concerns about the large volume and complexity of referrals and the appropriateness of an investigative model that has been criticized as adversarial, intrusive, and inappropriate for some referrals. In response, a Differential Response Model of child protection has emerged, with investigative and non-investigative alternative response paths that better acknowledge the complexities of child maltreatment and child protection. The purpose of this study was to add to the knowledge base by identifying the relationships and significance of county-level community variables in the investigative and non-investigative response paths of the Differential Response Model. Secondary data analysis used retrospective child maltreatment data from the National Child Abuse and Neglect Data System. County-level data on social, economic, and demographic variables were obtained from the American Community Survey, an ongoing national survey conducted by the U.S. Census Bureau. The final dataset included 62,499 cases in 98 counties from Kentucky, Louisiana, Missouri, North Carolina, and Virginia. Predictor variables included data at child, county, and state levels. Multilevel modeling procedures were used to build multiple three-level models to analyze predictors for the binary outcome variable of child protective services differential response path: alternative response (noninvestigation) or non-alternative response (investigation). The final three-level model demonstrated that county-level factors accounted for 12.30% of the variability in the response path outcome variable. Key results indicated that the county-level variables of housing vacancy, unemployment, child poverty, and households with public assistance were significant (p<.05) in predicting response pathway. Child-level variables (report source, maltreatment type, child age, race, and number of children in the report), and the state variable of number of years since implementation of differential response were also significant (p<.05) predictors in the response path outcome variable. Results demonstrated that factors from multiple levels and contexts impact how child protection units in the Differential Response Model respond to maltreatment referrals. Research using advanced multilevel analytic procedures is essential for accurate modeling and clarification of variables in nested relationships.
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Introduction -- Review of literature -- Methodology -- Results -- Discussion -- Appendix A. University of Missouri-Kansas City Institutional Review Board Exemption -- Appendix B. Data license: National Child Abuse and Neglect Data System Child File
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Ph.D.