Using Early Childhood Behavior Problems to Predict Adult Convictions.

Abstract

The current study examined whether teacher and parent ratings of externalizing behavior during kindergarten and 1st grade accurately predicted the presence of adult convictions by age 25. Data were collected as part of the Fast Track Project. Schools were identified based on poverty and crime rates in four locations: Durham, NC, Nashville, TN, Seattle, WA, and rural, central PA. Teacher and parent screening measures of externalizing behavior were collected at the end of kindergarten and 1st grade. ROC curves were used to visually depict the tradeoff between sensitivity and specificity and best model fit was determined. Five of the six combinations of screen scores across time points and raters met both the specificity and sensitivity cutoffs for a well-performing screening tool. When data were examined within each site separately, screen scores performed better in sites with high base rates and models including single teacher screens accurately predicted convictions. Similarly, screen scores performed better and could be used more parsimoniously for males, but not females (whose base rates were lower in this sample). Overall, results indicated that early elementary screens for conduct problems perform remarkably well when predicting criminal convictions 20 years later. However, because of variations in base rates, screens operated differently by gender and location. The results indicated that for populations with high base rates, convictions can be accurately predicted with as little as one teacher screen taken during kindergarten or 1st grade, increasing the cost-effectiveness of preventative interventions.

Department

Description

Provenance

Citation

Published Version (Please cite this version)

10.1007/s10802-018-0478-7

Publication Info

Kassing, Francesca, Jennifer Godwin, John E Lochman, John D Coie and undefined Conduct Problems Prevention Research Group (2018). Using Early Childhood Behavior Problems to Predict Adult Convictions. Journal of abnormal child psychology. 10.1007/s10802-018-0478-7 Retrieved from https://hdl.handle.net/10161/17614.

This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.

Scholars@Duke

Jennifer Godwin

Research Scientist

Jennifer Godwin is a research scientist at the Center for Child and Family Policy. She joined the Center in 2003 to provide statistical expertise for various projects. Currently, she works on the Fast Track and Childhood Risk Factors and Young Adult Competence projects, providing statistical analyses. She has extensive programming experience in SAS, Stata and MPlus, including survival analysis, mediation models, and multilevel models for continuous and categorical dependent variables.

Coie

John D. Coie

Professor Emeritus of Psychology: Social and Health Sciences

Unless otherwise indicated, scholarly articles published by Duke faculty members are made available here with a CC-BY-NC (Creative Commons Attribution Non-Commercial) license, as enabled by the Duke Open Access Policy. If you wish to use the materials in ways not already permitted under CC-BY-NC, please consult the copyright owner. Other materials are made available here through the author’s grant of a non-exclusive license to make their work openly accessible.