Computerized psychiatric diagnoses based on euclidean distances: a Chinese example

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Abstract
Current diagnostic methods in psychiatry use sequential logical decision rules that generate a single diagnosis. Insufficient attention has been paid to parallel methods that can simultaneously determine the relative probability of many diagnoses. This study installed 45 items from various symptom scales on a portable computer and applied a euclidean distance formula to generate immediate diagnoses based on responses to the items. The reliability and validity of the method were assessed using Chinese psychiatric inpatients. Interrater reliability was excellent (kappa = 0.91) and 3‐week test‐retest reliability was fair (k = 0.50). The concordance of this method with clinicians’ diagnoses and with diagnoses based on standardized Chinese diagnostic criteria was excellent (k = 0.73 and 0.76). Concordance with DSM‐III‐R diagnoses and ICD‐10 diagnoses was fair (kappa = 0.55 and 0.65). The clinical utility of such parallel methods of psychiatric diagnosis deserves further evaluation.