PURPOSE: To describe and validate the 'DAWBA bands'. These are novel ordered-categorical measures of child mental health, based on the structured sections of the Development and Well-Being Assessment (DAWBA). 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 6) 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. In 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.
PURPOSE: To describe and validate the 'DAWBA bands'. These are novel ordered-categorical measures of child mental health, based on the structured sections of the Development and Well-Being Assessment (DAWBA). 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 6) 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. In 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.
Authors: Einar Heiervang; Kjell M Stormark; Astri J Lundervold; Mikael Heimann; Robert Goodman; Maj-Britt Posserud; Anne K Ullebø; Kerstin J Plessen; Ingvar Bjelland; Stein A Lie; Christopher Gillberg Journal: J Am Acad Child Adolesc Psychiatry Date: 2007-04 Impact factor: 8.829
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Authors: Michel G Nivard; Suzanne H Gage; Jouke J Hottenga; Catharina E M van Beijsterveldt; Abdel Abdellaoui; Meike Bartels; Bart M L Baselmans; Lannie Ligthart; Beate St Pourcain; Dorret I Boomsma; Marcus R Munafò; Christel M Middeldorp Journal: Schizophr Bull Date: 2017-10-21 Impact factor: 9.306
Authors: Giovanni Abrahão Salum; Ary Gadelha; Pedro Mario Pan; Tais Silveira Moriyama; Ana Soledade Graeff-Martins; Ana Carina Tamanaha; Pedro Alvarenga; Fernanda Valle Krieger; Bacy Fleitlich-Bilyk; Andrea Jackowski; João Ricardo Sato; Elisa Brietzke; Guilherme Vanoni Polanczyk; Helena Brentani; Jair de Jesus Mari; Maria Conceição Do Rosário; Gisele Gus Manfro; Rodrigo Affonseca Bressan; Marcos Tomanik Mercadante; Eurípedes Constantino Miguel; Luis Augusto Rohde Journal: Int J Methods Psychiatr Res Date: 2014-12-03 Impact factor: 4.035
Authors: Sarah K G Jensen; Erin W Dickie; Deborah H Schwartz; C John Evans; Iroise Dumontheil; Tomáš Paus; Edward D Barker Journal: JAMA Pediatr Date: 2015-10 Impact factor: 16.193
Authors: Lorena Fernández de la Cruz; Pablo Vidal-Ribas; Nada Zahreddine; Børge Mathiassen; Per Håkan Brøndbo; Emily Simonoff; Robert Goodman; Argyris Stringaris Journal: Child Psychiatry Hum Dev Date: 2018-08