Abstract

Background
Youth who exit the nation’s foster care system without permanency are at high risk of experiencing difficulties during the transition to adulthood.
Objective
To present an illustrative test of whether an algorithmic decision aid could be used to identify youth at risk of existing foster care without permanency.
Methods
For youth placed in foster care between ages 12 and 14, we assessed the risk of exiting care without permanency by age 18 based on their child welfare service involvement history. To develop predictive risk models, 28 years (1991–2018) of child welfare service records from California were used. Performances were evaluated using F1, AUC, and precision and recall scores at k %. Algorithmic racial bias and fairness was also examined.
Results
The gradient boosting decision tree and random forest showed the best performance (F1 score = .54–.55, precision score = .62, recall score = .49). Among …

Date

2021

Authors

Eunhye Ahn, Yolanda Gil, Emily Putnam-Hornstein

Journal

Child abuse & neglect

Volume

117

Pages

105059

Publisher

Pergamon