A general population comparison of the Composite International Diagnostic Interview (CIDI) and the Schedules for Clinical Assessment in Neuropsychiatry
journal contributionposted on 14.09.2006, 15:28 by Traolach S. Brugha, Rachel Jenkins, Nick A. Taub, Howard Meltzer, Paul E. Bebbington
Background. In psychiatric surveys of the general population, there has been considerable discrepancy between diagnoses obtained by fully structured interviews and those established by systematic semi-structured clinical evaluation. The Composite International Diagnostic Interview (CIDI) is an example of the first type of interview widely used in general population surveys. We compared its performance in diagnosing current depressive and anxiety disorders with the Schedules for Clinical Assessment in Neuropsychiatry (SCAN), a semi-structured diagnostic interview administered by clinically trained interviewers. Methods. Household addresses in Leicestershire, UK, were randomly sampled and 860 adults were screened with the Revised Clinical Interview Schedule. Adults with too few symptoms to fulfil diagnostic criteria for study disorders were excluded to increase the proportion re-interviewed who met such criteria. Repeat diagnostic interviews with the CIDI and SCAN, ordered randomly, were sought from eligible screen positive respondents. Recalibrated CIDI prevalence estimates were derived from the SCAN classification using Bayesian statistics. Results. Concordance ranged between `poor' and `fair' across almost all types of study disorders, and for co-morbidity. Concordance was somewhat better for severity of depression and when lower diagnostic thresholds were used for depression. Interview order effects were suggested with lower concordance when CIDI followed SCAN. Recalibration reduced the prevalence of depressive or anxiety disorder from 9.0 to 6.2%. Conclusions. Community psychiatric surveys using structured diagnostic interview data must be interpreted cautiously. They should include an element of clinical re-appraisal so findings can be adjusted for estimation differences between fully structured and clinical assessments.