Another Pandora's box? Some pros and cons of predictive risk modeling Irene de Haan and Marie Connolly
By: de Haan, Irene
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Contributor(s): Connolly, Marie.
Material type: 
ArticleSeries: Children and Youth Services Review.Publisher: Elsevier, 2014Subject(s): CHILD PROTECTION | PREDICTIVE RISK MODELLING | SOCIAL SERVICES | NEW ZEALAND | CHILD ABUSEOnline resources: Access the abstract
In:
Children and Youth Services Review, 2014, 47(1): 86-91Summary: Early intervention, promoted as being important to the prevention of child maltreatment, is challenged by the difficulty of identifying at risk families before patterns of abuse are established. A way of identifying these families before they reach the radar of statutory systems of child protection is through predictive risk modeling (PRM). Using large datasets PRM tools are able to use algorithms with significant capacity to ascertain and stratify children's risk of experiencing maltreatment in the future. In the process, however, they also identify families who may well benefit from support but are not on a maltreatment trajectory — the so called ‘false positives’ who would not be among those families later identified as mistreating their children. (from the abstract)
Children and Youth Services Review, 2014, 47(1): 86-91
Early intervention, promoted as being important to the prevention of child maltreatment, is challenged by the difficulty of identifying at risk families before patterns of abuse are established. A way of identifying these families before they reach the radar of statutory systems of child protection is through predictive risk modeling (PRM). Using large datasets PRM tools are able to use algorithms with significant capacity to ascertain and stratify children's risk of experiencing maltreatment in the future. In the process, however, they also identify families who may well benefit from support but are not on a maltreatment trajectory — the so called ‘false positives’ who would not be among those families later identified as mistreating their children. (from the abstract)
