title: Early detection of children at risk for antisocial behaviour using data from routine preventive child healthcare.
abstract: BACKGROUND
  Youth antisocial behaviour is highly prevalent. Young people are usually not willing to disclose such behaviour to professionals and parents. Our aim was to assess whether child health professionals (CHP) working in preventive child healthcare could identify pre-adolescents at risk for antisocial behaviour through using data that they obtain in routine practice.
  
  
  METHODS
  CHPs examined a national sample of 974 pre-adolescents aged 8-12 years (response 79.1%), and interviewed parents and children during routine well-child assessments. We obtained data on family background and current health of the child from the CHP; on developmental concerns from parents, and on social and emotional well-being, injuries, and substance use from the children. Antisocial behaviour concerned the adolescent-reported 15 item International Self-Reported Delinquency study questionnaire, among which are 5 items on violence against people.
  
  
  RESULTS
  The prevalence of 2+acts of any antisocial behaviour was 21.8%, and 33.9% for 1+acts of violence (10.5% for 2+). Children who were male, had a young mother, no parent employed, recent injuries, poor performance at school or who were bored by school, and who had parental concerns more often reported 2+antisocial acts and 1+violence against people. Detection algorithms on the basis of these variables were moderately able to classify outcomes, with Areas-Under-the-Curves ranging from 0.66 to 0.71.
  
  
  CONCLUSIONS
  Data from routine well-child assessment can help CHPs to detect pre-adolescents at risk for antisocial behaviour, but detection algorithms need to be further improved. This could be done by obtaining additional information on factors that are associated with antisocial behaviour.
authors.affiliation: Department of Health Sciences, University of Groningen, Groningen, The Netherlands. s.a.reijneveld@umcg.nl
authors.forename: Sijmen A
authors.initials: SA
authors.lastname: Reijneveld
authors.forename: Matty R
authors.initials: MR
authors.lastname: Crone
authors.forename: Gea
authors.initials: G
authors.lastname: de Meer
mesh_terms: D000465:Algorithms; D000987:Antisocial Personality Disorder / Q000175:diagnosis / Q000209:etiology / Q000517:prevention & control; D002648:Child; D002653:Child Behavior Disorders / Q000175:diagnosis* / Q000209:etiology / Q000517:prevention & control; D019955:Conduct Disorder / Q000175:diagnosis / Q000209:etiology / Q000517:prevention & control; D042241:Early Diagnosis; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D011314:Preventive Health Services; D012306:Risk; D057566:Self Report; D014754:Violence / Q000517:prevention & control / Q000706:statistics & numerical data