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一种基于聚类分析得出的类型学:儿童临床诊断分类的可行替代方案?

A cluster-analytically derived typology: feasible alternative to clinical diagnostic classification of children?

作者信息

Lessing E E, Williams V, Gil E

出版信息

J Abnorm Child Psychol. 1982 Dec;10(4):451-82. doi: 10.1007/BF00920748.

DOI:10.1007/BF00920748
PMID:7161439
Abstract

Despite numerous studies of the relationships among symptoms manifested by children and adolescents, there have been few systematic attempts to group individuals on the basis of the syndromes identified. In the course of a treatment evaluation project requiring classification of both child patients and untreated controls, the present study was conducted to determine whether replicable types of children and adolescents could be identified by the cluster analysis of their IJR Behavior Checklist profiles. One clinical sample (N = 185) and two mixed clinical and normal subsamples (Ns of 358 and 373) were cluster-analyzed separately. Seven types that replicated across at least two subsamples were identified: (1) High Assets, Flat Symptom Profile; (2) Sociopathic, Academic Problems; (3) Moderate Assets, Egocentric, Incontinent; (4) Insecure, Somaticizing, Underachieving; (5) Aggressive, Overreactive; (6) Schizoid, Withdrawn, Anxious, Bizarre; and (7) Diffuse, Mixed Pathology. The issue posed by the title of the article was explored in the light of the findings.

摘要

尽管针对儿童和青少年所表现出的症状之间的关系进行了大量研究,但基于所确定的综合征对个体进行分组的系统性尝试却很少。在一个需要对儿童患者和未接受治疗的对照组进行分类的治疗评估项目过程中,开展了本研究,以确定通过对儿童和青少年的《儿童行为核查表》档案进行聚类分析,是否能够识别出可重复的类型。对一个临床样本(N = 185)以及两个临床与正常混合子样本(样本量分别为358和373)分别进行了聚类分析。确定了在至少两个子样本中重复出现的七种类型:(1)高资产,症状轮廓平坦型;(2)反社会型,学业问题型;(3)中等资产,自我中心,失禁型;(4)缺乏安全感,躯体化,学业成绩不佳型;(5)攻击性强,反应过度型;(6)分裂样,孤僻,焦虑,怪异型;以及(7)弥漫性,混合型病理型。根据研究结果对文章标题所提出的问题进行了探讨。

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本文引用的文献

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Mixture Model Tests Of Hierarchical Clustering Algorithms: The Problem Of Classifying Everybody.层次聚类算法的混合模型检验:对每个人进行分类的问题。
Multivariate Behav Res. 1979 Jul 1;14(3):367-84. doi: 10.1207/s15327906mbr1403_6.
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The Literature On Cluster Analysis.《关于聚类分析的文献》
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