首页 | 本学科首页   官方微博 | 高级检索  
     


The use of prediction data in understanding delinquency
Authors:Magda Stouthamer-Loeber  Rolf Loeber
Abstract:Predicting delinquency is valuable for understanding the course of crime, factors that influence its course, and the identification of markers that signal deviant processes. In addition, prediction data are relevant for judicial and clinical decision making. This article summarizes research findings on the prediction of delinquency. In the realm of early childhood behaviors, there is consensus that aggression (especially in conjunction with hyperactivity), drug use, truancy, lying, stealing, general problem behaviors, and poor educational achievement all predict later delinquency, albeit to varying degrees, with composite prediction scales yielding the highest degree of accuracy. In addition, studies show a reasonable consensus that the following family factors also predict delinquency: poor supervision, lack of involvement by parents, poor discipline, rejection by a parent, parental criminality and aggressiveness, marital problems, parental absence, and poor parental health. Variables reflecting socialization processes predicted later delinquency as well as children's early behavior. Although studied less frequently, youngsters' association with deviant peers is also predictive of delinquency.
Keywords:
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号