Citation

Lonne B, Herrenkohl TI, Higgins DJ, Scott D. Int. J. Child Maltreat. 2022; 5(4): 501-517.

Copyright

(Copyright © 2022, Holtzbrinck Springer Nature Publishing Group)

DOI

10.1007/s42448-022-00126-9

PMID

unavailable

Abstract

Critics are raising serious questions about who is "served" by statutory child protection systems if they utilize an intervention model based on reporting, investigation, and removal. Public health approaches present an innovative alternative, but how to get the right support and interventions to the right people at the right time remains challenging. The power of predictive analytics and big data is seductive, yet the risks of bolting on such tools to existing statutory services may serve only to reify or increase inequity and exclusion if they are used to target "vulnerable" children and families for interventions. The use of such new techniques within the framework of statutory child protection services may be like putting new wine into old wineskins. In keeping with a public health approach, the focus, in keeping with a public health approach, should be on the use of population-based data to deliver interventions of variable intensity, aimed at reducing the exposure of the population to risk factors for each of the forms of child abuse and neglect. The use of integrated systems of administrative data with associated sophisticated predictive analytics offers a panoptic view of the causes, complex interactions, consequences, and complications of child maltreatment and our responses to deal with it. Data linkage and predictive analytics have an important and useful role to play in public health approaches to child maltreatment and service delivery but require us to be mindful of amplifying increasing existing inequalities and not making matters worse for those we are trying to assist.

Language: en

Keywords

Administrative data; Equity; Ethics; Predictive analytics; Predictive risk modeling; Privacy; Public health