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Zung 自评焦虑量表的常模。

Norms for Zung's Self-rating Anxiety Scale.

机构信息

School of Psychology University of New England, Armidale, NSW, 2351, Australia.

出版信息

BMC Psychiatry. 2020 Feb 28;20(1):90. doi: 10.1186/s12888-019-2427-6.

Abstract

BACKGROUND

Zung's Self-rating Anxiety Scale (SAS) is a norm-referenced scale which enjoys widespread use a screener for anxiety disorders. However, recent research (Dunstan DA and Scott N, Depress Res Treat 2018:9250972, 2018) has questioned whether the existing cut-off for identifying the presence of a disorder might be lower than ideal.

METHOD

The current study explored this issue by examining sensitivity and specificity figures against diagnoses made on the basis of the Patient Health Questionnaire (PHQ) in clinical and community samples. The community sample consisted of 210 participants recruited to be representative of the Australian adult population. The clinical sample consisted of a further 141 adults receiving treatment from a mental health professional for some form of anxiety disorder.

RESULTS

Mathematical formulas, including Youden's Index and the Receiver Operating Characteristics Curve, applied to positive PHQ diagnoses (presence of a disorder) from the clinical sample and negative PHQ diagnoses (absence of a disorder) from the community sample suggested that the ideal cut-off point lies between the current and original points recommended by Zung.

CONCLUSIONS

Consideration of prevalence rates and of the potential costs of false negative and false positive diagnoses, suggests that, while the current cut-off of 36 might be appropriate in the context of clinical screening, the original raw score cut-off of 40 would be most appropriate when the SAS is used in research.

摘要

背景

Zung 的自评焦虑量表(SAS)是一种常模参照量表,广泛用于焦虑障碍的筛查。然而,最近的研究(Dunstan DA 和 Scott N,Depress Res Treat 2018:9250972,2018)质疑现有的用于识别障碍存在的分界值可能不够理想。

方法

本研究通过检查基于患者健康问卷(PHQ)在临床和社区样本中做出的诊断的敏感性和特异性来探讨这个问题。社区样本由 210 名参与者组成,旨在代表澳大利亚成年人口。临床样本由另外 141 名因某种形式的焦虑障碍而接受心理健康专业人员治疗的成年人组成。

结果

应用于临床样本中阳性 PHQ 诊断(存在障碍)和社区样本中阴性 PHQ 诊断(不存在障碍)的数学公式,包括 Youden 指数和受试者工作特征曲线,表明理想的分界点介于 Zung 推荐的当前和原始分界点之间。

结论

考虑到患病率以及假阴性和假阳性诊断的潜在成本,建议在临床筛查的情况下,当前的 36 分界值可能是合适的,而当 SAS 用于研究时,原始的原始分数分界值 40 是最合适的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f47a/7048044/bb3e8b7d926b/12888_2019_2427_Fig1_HTML.jpg

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