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抑郁焦虑压力量表(DASS):大型非临床样本中的常模数据和潜在结构

The Depression Anxiety Stress Scales (DASS): normative data and latent structure in a large non-clinical sample.

作者信息

Crawford John R, Henry Julie D

机构信息

Department of Psychology, King's College, University of Aberdeen, UK.

出版信息

Br J Clin Psychol. 2003 Jun;42(Pt 2):111-31. doi: 10.1348/014466503321903544.

Abstract

OBJECTIVES

To provide UK normative data for the Depression Anxiety and Stress Scale (DASS) and test its convergent, discriminant and construct validity.

DESIGN

Cross-sectional, correlational and confirmatory factor analysis (CFA).

METHODS

The DASS was administered to a non-clinical sample, broadly representative of the general adult UK population (N = 1,771) in terms of demographic variables. Competing models of the latent structure of the DASS were derived from theoretical and empirical sources and evaluated using confirmatory factor analysis. Correlational analysis was used to determine the influence of demographic variables on DASS scores. The convergent and discriminant validity of the measure was examined through correlating the measure with two other measures of depression and anxiety (the HADS and the sAD), and a measure of positive and negative affectivity (the PANAS).

RESULTS

The best fitting model (CFI =.93) of the latent structure of the DASS consisted of three correlated factors corresponding to the depression, anxiety and stress scales with correlated error permitted between items comprising the DASS subscales. Demographic variables had only very modest influences on DASS scores. The reliability of the DASS was excellent, and the measure possessed adequate convergent and discriminant validity Conclusions: The DASS is a reliable and valid measure of the constructs it was intended to assess. The utility of this measure for UK clinicians is enhanced by the provision of large sample normative data.

摘要

目的

提供英国人群抑郁焦虑压力量表(DASS)的常模数据,并检验其收敛效度、区分效度和结构效度。

设计

横断面研究、相关性研究和验证性因素分析(CFA)。

方法

将DASS施测于一个非临床样本,该样本在人口统计学变量方面广泛代表了英国一般成年人群(N = 1771)。DASS潜在结构的竞争模型源自理论和实证来源,并使用验证性因素分析进行评估。相关性分析用于确定人口统计学变量对DASS分数的影响。通过将该量表与另外两种抑郁和焦虑量表(医院焦虑抑郁量表(HADS)和简易焦虑自评量表(sAD))以及一种正负性情绪量表(正负性情绪量表(PANAS))进行相关性分析,来检验该量表的收敛效度和区分效度。

结果

DASS潜在结构的最佳拟合模型(比较拟合指数(CFI)= 0.93)由三个相关因素组成,分别对应抑郁、焦虑和压力量表,且允许DASS子量表中的项目之间存在相关误差。人口统计学变量对DASS分数的影响非常小。DASS的信度极佳,且该量表具有足够的收敛效度和区分效度。结论:DASS是一种可靠且有效的量表,能够测量其旨在评估的构念。通过提供大样本常模数据,增强了该量表对英国临床医生的实用性。

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