title: An accurate and efficient identification of children with psychosocial problems by means of computerized adaptive testing.
abstract: BACKGROUND
  Questionnaires used by health services to identify children with psychosocial problems are often rather short. The psychometric properties of such short questionnaires are mostly less than needed for an accurate distinction between children with and without problems. We aimed to assess whether a short Computerized Adaptive Test (CAT) can overcome the weaknesses of short written questionnaires when identifying children with psychosocial problems.
  
  
  METHODS
  We used a Dutch national data set obtained from parents of children invited for a routine health examination by Preventive Child Healthcare with 205 items on behavioral and emotional problems (n = 2,041, response 84%). In a random subsample we determined which items met the requirements of an Item Response Theory (IRT) model to a sufficient degree. Using those items, item parameters necessary for a CAT were calculated and a cut-off point was defined. In the remaining subsample we determined the validity and efficiency of a Computerized Adaptive Test using simulation techniques, with current treatment status and a clinical score on the Total Problem Scale (TPS) of the Child Behavior Checklist as criteria.
  
  
  RESULTS
  Out of 205 items available 190 sufficiently met the criteria of the underlying IRT model. For 90% of the children a score above or below cut-off point could be determined with 95% accuracy. The mean number of items needed to achieve this was 12. Sensitivity and specificity with the TPS as a criterion were 0.89 and 0.91, respectively.
  
  
  CONCLUSIONS
  An IRT-based CAT is a very promising option for the identification of psychosocial problems in children, as it can lead to an efficient, yet high-quality identification. The results of our simulation study need to be replicated in a real-life administration of this CAT.
authors.affiliation: Cild Health, TNO, Leiden, The Netherlands. ton.vogels@tno.nl
authors.forename: Antonius G C
authors.initials: AG
authors.lastname: Vogels
authors.forename: Gert W
authors.initials: GW
authors.lastname: Jacobusse
authors.forename: Symen A
authors.initials: SA
authors.lastname: Reijneveld
mesh_terms: D001499:Bayes Theorem; D002648:Child; D005260:Female; D006801:Humans; D016015:Logistic Models; D008297:Male; D012372:ROC Curve; D012920:Social Behavior Disorders / Q000175:diagnosis*; D011795:Surveys and Questionnaires