The ‘DAWBA bands’ as an ordered-categorical measure of child mental health: description and validation in British and Norwegian samples

Abstract

Goodman, A; Heiervang, E; Collishaw, S; Goodman, R (2010) The 'DAWBA bands' as an ordered-categorical measure of child mental health: description and validation in British and Norwegian samples. Social psychiatry and psychiatric epidemiology. ISSN 0933-7954 DOI: 10.1007/s00127-010-0219-x Methods:We developed computer algorithms to generate parent, teacher, child and multi-informant DAWBA bands for individual disorders and for groups of disorder (e.g. 'any emotional disorder'). The top two (out of six) Levels of the DAWBA bands were used as computer-generated DAWBA diagnoses. We validated these DAWBA bands in 7,912 British children (7-19 years) and 1,364 Norwegian children (11-13 years), using clinician-rated DAWBA diagnoses as a gold standard. Results:In general, the prevalence of clinician-rated diagnosis increased monotonically across all Levels of the DAWBA bands, and also showed a dose-response association with service use and risk factors. The prevalence estimates of the computer-generated DAWBA diagnoses were of roughly comparable magnitude to the prevalence estimates from the clinician-generated diagnoses, but the estimates were not always very close. By contrast, the estimated effect sizes, significance levels and substantive conclusions regarding risk factor associations were very similar or identical. The multi-informant and parent DAWBA bands performed especially well in these regards. Conclusion:Computer-generated DAWBA bands avoid the cost and delay occasioned by clinical rating. They may therefore sometimes provide a useful alternative to clinician-rated diagnoses when studying associations with risk factors, generating rough prevalence estimates or implementing routine mental health screening.

The contribution of prenatal and postnatal maternal anxiety and depression to child maladjustment

“…[41] In addition to generating binary (yes/no) diagnostic indicators, DAWBA algorithms have recently been developed to generate six-level ordered-categorical measures of the probability of disorder, ranging from o0.1% to 470%. [42] Evaluated in two large-scale national samples, these DAWBA ''bands'' functioned well as orderedcategorical measures, showed dose-response associations with mental health service contacts, and showed very similar associations with potential risk factors as clinician-rated diagnoses. [42] For externalizing disorders (reported by parents and teachers), we examined a summed indicator of the ordered categories of CD, ODD, and any ADHD (including hyperactive, inattentive and combined sub-types, and ADHD not otherwise specified).…”

“…[42] Evaluated in two large-scale national samples, these DAWBA ''bands'' functioned well as orderedcategorical measures, showed dose-response associations with mental health service contacts, and showed very similar associations with potential risk factors as clinician-rated diagnoses. [42] For externalizing disorders (reported by parents and teachers), we examined a summed indicator of the ordered categories of CD, ODD, and any ADHD (including hyperactive, inattentive and combined sub-types, and ADHD not otherwise specified). With regard to internalizing disorders (reported by parents), we used a summed indicator of the ordered categories of any indication of anxiety and depression.…”

The Brain’s Response to Reward Anticipation and Depression in Adolescence: Dimensionality, Specificity, and Longitudinal Predictions in a Community-Based Sample

“…The DAWBA is designed to maintain consistency across multiple cultural and language groups, as diagnoses are made by clinical raters who share a common training and participate in regular cross-language training and consensus meetings. The DAWBA generates probabilities of having DSM-IV-TR diagnoses (19), which we used to define the categorical diagnosis of depression.…”

Peer Victimization in Childhood and Internalizing Problems in Adolescence: A Prospective Longitudinal Study

“…depressive disorder and anxiety disorder at age 13 years, using a computer algorithm which has been shown to be comparable in accuracy with a clinical rating method (A. Goodman et al 2011). The emotional subscale has reported good internal consistency (Cronbach's alpha = 0.75).…”