Grayson D, Bridges K, Cook D, Goldberg D
Department of Psychiatry, University of Manchester.
Psychol Med. 1990 Feb;20(1):209-18. doi: 10.1017/s0033291700013386.
It is argued that latent trait analysis provides a way of examining the construct validity of diagnostic concepts which are used to categorize common mental illnesses. The present study adds two additional aspects of validity using multiple discriminant analysis applied to two widely used taxonomic systems. Scales of anxiety and depression derived from previous latent trait analyses are applied to individuals reaching criteria for 'caseness' on the ID-CATEGO system and the DSM-III system, both at initial diagnosis and six months later. The first multiple discriminant analysis is carried out on the initial scale scores, and the results are interpreted in terms of concurrent validity. The second analysis uses improvement scores on the two scales and relates to predictive validity. It is argued that the ID-CATEGO system provides a better classification for common mental illnesses than the DSM-III system, since it allows a better discrimination to be made between anxiety and depressive disorders.
有人认为,潜在特质分析为检验用于对常见精神疾病进行分类的诊断概念的结构效度提供了一种方法。本研究使用应用于两个广泛使用的分类系统的多重判别分析,增加了效度的两个额外方面。从先前的潜在特质分析得出的焦虑和抑郁量表应用于在ID-CATEGO系统和DSM-III系统上达到“病例”标准的个体,包括初始诊断时和六个月后。第一次多重判别分析是对初始量表分数进行的,结果根据同时效度进行解释。第二次分析使用两个量表上的改善分数,并与预测效度相关。有人认为,ID-CATEGO系统比DSM-III系统能为常见精神疾病提供更好的分类,因为它能更好地区分焦虑症和抑郁症。