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Published on: April 28, 2016
Using Early Childhood Behavior Problems to Predict Adult Convictions.
Francesca Kassing1, Jennifer Godwin2, John E Lochman3
1Department of Psychology, The University of Alabama, Box 870348, Tuscaloosa, AL, 35487, USA. fkassing@crimson.ua.edu.
Early childhood behavior screenings by teachers and parents effectively predict adult criminal convictions. High-risk populations benefit most, with single kindergarten or first-grade teacher screens showing predictive accuracy for future legal issues.
Area of Science:
- Developmental Psychology
- Criminology
- Educational Psychology
Background:
- Externalizing behaviors in early childhood are linked to later life outcomes.
- Predicting adult criminal convictions from childhood behavior is crucial for early intervention.
Purpose of the Study:
- To assess the predictive validity of teacher and parent ratings of externalizing behavior in kindergarten and 1st grade for adult convictions by age 25.
- To examine how screening tool performance varies by location, gender, and base rates of conduct problems.
Main Methods:
- Utilized data from the Fast Track Project, collecting teacher and parent ratings of externalizing behavior.
- Employed Receiver Operating Characteristic (ROC) curves to evaluate screening tool accuracy (sensitivity and specificity).
- Analyzed data across four diverse locations, considering gender and site-specific base rates.
Main Results:
- Five of six screen score combinations accurately predicted adult convictions.
- Screening tools performed better in locations with higher base rates of conduct problems.
- Single teacher screens in kindergarten or 1st grade accurately predicted convictions in high base rate populations, especially for males.
Conclusions:
- Early elementary screening for conduct problems is a strong predictor of adult criminal convictions.
- Screening tool effectiveness is influenced by demographic factors like gender and geographic location's base rates.
- Cost-effective early interventions can be targeted using predictive data from high-risk populations.
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