Diagnostic Accuracy of the Algorithm of the Norwegian Verison of Strengths and Difficulties Questionnaire (SDQ) - Eidstuen, Jon Sigurd; Kornør, Hege (PsykTestBarn, 2017)
Description: Strengths and Difficulties Questionnaire (SDQ) is a set of questionnaires with three informant versions: parents, teachers and youth aged ≥ 11 years. The psychometric properties of the various SDQ informant versions have been assessed in separate PsykTestBarn articles. Robert Goodman has developed an algorithm for the prediction of the presence of a mental health disorder. The SDQ algorithm encompasses data from at least two informants, but can also include data from all three categories of informants. The algorithm can estimate the likelihood of a child’s diagnoses within four broad categories: emotional disorder, behaviour disorder, hyperkinetic/attention disorder and any disorder. The likelihood is expressed at one of three thresholds; unlikely, possible and probable. The aim of this systematic review is to assess the diagnostic accuracy of the SDQ algorithm in Scandinavian samples. Literature search: Out of 541 unique hits, we screened 133 in full text, whereof 11 publications met the inclusion criteria. Five publications were sub-studies in the Bergen Child Study, five were other Norwegian studies, and one was a Danish study. The studies included both population based and selected samples with an age range of 5 to 18 years. Psychometrics: Six studies reported relevant diagnostic accuracy data, while five reported prevalence rates. The SDQ algorithm had generally good sensitivities, specificities and negative predictive values (NPV) in selected samples, but the positive predictive values (PPV) varied. In population-based samples where ADHD was the only target disorder, the algorithm had excellent specificity and NPV, while the sensitivity and PPV were poor. None of the reference standards used in the studies had sufficiently documented criterion validity. Conclusion: The SDQ algorithm has a good ability to identify children with and without mental health disorders in selected samples. In population-based samples, the SDQ-algorithm can exclude ADHD correctly with great accuracy, but its ability to detect ADHD is poor. We need studies using reference standards with documented criterion validity to gain better knowledge of the diagnostic accuracy of the SDQ-algorithm.