title: Commentary on: Are we overpathologizing everyday life? A tenable blueprint for behavioral addiction research. The diagnostic pitfalls of surveys: If you score positive on a test of addiction, you still have a good chance not to be addicted.
abstract: OBJECTIVE
  Survey-based studies often fail to take into account the predictive value of a test, in other words, the probability of a person having (or not having) the disease when scoring positive (or negative) on the given screening test.
  
  
  METHODS
  We re-visited the theory and basic calculations of diagnostic accuracy.
  
  
  RESULTS
  In general, the lower the prevalence the worse the predictive value is. When the disorder is relatively rare, a positive test finding is typically not useful in confirming its presence given the high proportion of false positive cases. For example, using the Compulsive Buying Scale (Faber & O'Guinn, 1992) three in four people classified as having compulsive buying disorder will in fact not have the disorder.
  
  
  CONCLUSIONS
  Screening tests are limited to serve as an early detection "gate" and only clinical (interview-based) studies are suitable to claim that a certain behaviour is truly "pathological".
authors.affiliation: Doctoral School of Psychology, Eötvös Loránd University , Budapest , Hungary.|Institute of Psychology, Eötvös Loránd University , Budapest , Hungary.
authors.forename: Aniko
authors.initials: A
authors.lastname: Maraz
authors.affiliation: Institute of Psychology, Eötvös Loránd University , Budapest , Hungary.
authors.forename: Orsolya
authors.initials: O
authors.lastname: Király
authors.affiliation: Institute of Psychology, Eötvös Loránd University , Budapest , Hungary.
authors.forename: Zsolt
authors.initials: Z
authors.lastname: Demetrovics
mesh_terms: D016739:Behavior, Addictive / Q000523:psychology*; D035841:Behavioral Research / Q000379:methods*; D006801:Humans; D008962:Models, Theoretical
keywords: accuracy; assessment; behavioural addiction; diagnosis; negative predictive value; positive predictive value; sensitivity; severity; specificity