APS
APS Virtual Poster Showcase · 2020
Predicting Adolescent Substance Use in a Child Welfare Sample: A Multi-Indicator Algorithm
- Suvarna Menon
Northern Illinois University - Hena Thakur
University of Illinois at Urbana-Champaign - Ryan Shorey
University of Wisconsin-Milwaukee - Joseph Cohen
University of Illinois at Urbana Champaign
Abstract
Aim: Quantifying incremental validity of routine assessments (CBCL and YSR) and a substance use (SU) screener (CRAFFT) to predict SU in a child welfare sample (N=1,054; AgeM=13.72). Method: ROC, reclassification analyses. Results: Baseline CRAFFT, delinquent behavior and rule-breaking behavior (males); baseline CRAFFT and delinquent behavior (females); provided incrementally valid prediction.
Substance Use and Abuse
