Leveraging machine learning for effective child maltreatment prevention: A case study of home visiting service assessments

CONCLUSIONS: Our study underscores the potential of PRM in enhancing the risk assessment tool used by a prevention program in a child welfare center in California. The findings provide valuable insights to practitioners interested in utilizing data for PRM development, highlighting the potential of machine learning algorithms to generate accurate predictions and inform targeted preventive services.PMID:38428267 | DOI:10.1016/j.chiabu.2024.106706
Source: Child Abuse and Neglect - Category: Child Development Authors: Source Type: research