Around the world, cultural blending and conflict pose challenges for assessment and understanding of psychopathology. Economical, evidence-based, culturally robust assessment is needed for research, for answering public health questions, and for evaluating immigrant, refugee, and minority children. This article applies multicultural perspectives to behavioral, emotional, and social problems assessed on dimensions describing children's functioning, as rated by parents, teachers, children, and others. The development of Achenbach System of Empirically Based Assessment (ASEBA) and Strengths and Difficulties Questionnaire (SDQ) forms and their applications to multicultural research are presented. A primary aim of both questionnaires is to identify children at high risk of psychiatric disorders and who therefore warrant further assessment. The forms are self-administered or administered by lay interviewers. ASEBA problem items are scored on 6 DSM-oriented scales and 3 broader band scales, plus 8 syndromes derived statistically as taxonomic constructs and supported by uniform confirmatory factor analyses of samples from many populations. Comparisons of ASEBA scale scores, psychometrics, and correlates are available for diverse populations. SDQ forms are scored on one broad-band scale and 5 a priori behavioral dimensions supported by data from various populations. For both instruments, factor analyses, psychometrics, and correlates are available for diverse populations. The willingness and ability of hundreds of thousands of respondents from diverse groups to complete ASEBA and SDQ forms support this approach to multicultural assessment. Although particular items and scales may have differential relevance among groups and additional assessment procedures are needed, comparable results are found in many populations. Scale scores vary more within than between populations, and distributions of scores overlap greatly among different populations. Ratings of children's problems thus indicate more heterogeneity within populations than distinctiveness between populations. Norms from multiple populations can be used to compare children's scores with relevant peer groups. Multicultural dimensional research can advance knowledge by diversifying normative data; by comparing immigrant children with nonimmigrant compatriots and with host country children; by identifying outlier findings for elucidation by emic research; and by fostering efforts to dimensionalize DSM-V diagnostic criteria.

No 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.