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通过对使用抗抑郁药治疗的抑郁症住院患者收集的时间序列情绪数据的计算机化数学描述进行聚类分析,得出情绪评估曲线的类型学。

Typology of mood assessment curves by means of cluster analysis of computerized mathematical descriptions of time-series mood data collected from depressive inpatients treated with antidepressants.

作者信息

Möller H J, Leitner M

机构信息

Psychiatric Clinic, Technical University, Munich, FRG.

出版信息

Pharmacopsychiatry. 1988 Jul;21(4):192-6. doi: 10.1055/s-2007-1014674.

Abstract

A recently developed method for the computerized description of mood curves was applied to self-evaluation mood data of a large sample of 136 depressive inpatients. The values of the mathematical parameters from this description were analysed by cluster analysis to determine different types of mood courses of patients undergoing therapy with antidepressants. In general, the most unfavorable type of mood course was overrepresented in the group of neurotic depressive patients, the most favorable one in the group of endogenous depressive patients. But in this latter diagnostic group, a remarkable proportion of patients with the unfavorable mood course was observed, indicating the well-known phenomenon of non-response to antidepressants. The results can be interpreted as a validation of the new method of computerized description of mood curves. This method might lead to interesting possibilities in drug treatment evaluation.

摘要

一种最近开发的用于对情绪曲线进行计算机化描述的方法,被应用于136名抑郁住院患者的大样本自我评估情绪数据。通过聚类分析对该描述中数学参数的值进行分析,以确定接受抗抑郁药物治疗患者的不同类型情绪病程。总体而言,最不利的情绪病程类型在神经症性抑郁患者组中占比过高,最有利的在内源性抑郁患者组中。但在后一个诊断组中,观察到相当比例的患者有不利的情绪病程,这表明了众所周知的对抗抑郁药无反应的现象。这些结果可被解释为对情绪曲线计算机化描述新方法的验证。该方法可能会在药物治疗评估中带来有趣的可能性。

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