Using Early Childhood Behavior Problems to Predict Adult Convictions.

Published

Journal Article

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.

Full Text

Duke Authors

Cited Authors

  • Kassing, F; Godwin, J; Lochman, JE; Coie, JD; Conduct Problems Prevention Research Group,

Published Date

  • October 3, 2018

Published In

PubMed ID

  • 30280365

Pubmed Central ID

  • 30280365

Electronic International Standard Serial Number (EISSN)

  • 1573-2835

International Standard Serial Number (ISSN)

  • 0091-0627

Digital Object Identifier (DOI)

  • 10.1007/s10802-018-0478-7

Language

  • eng