Norms for Zung's Self-rating Anxiety Scale

Debra A Dunstan, Ned Scott, Debra A Dunstan, Ned Scott

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.

Keywords: Anxiety screening; Cut-off score; Zung self-rating anxiety scale (SAS).

Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
ROC curve for the combined Positive Clinical and Negative Community samples (blue line). Sensitivity of the SAS in the Positive Clinical subsample is graphed against 1 - the specificity in the Negative Community subsample for each potential SAS cut-off point

References

    1. Andrews G, Henderson S, Hall W. Prevalence, comorbidity, disability and service utilisation Overview of the Australian National Mental Health Survey. Br J Psychiatry. 2001;178:145–153. doi: 10.1192/bjp.178.2.145.
    1. Kessler RC, Aguilar-Gaxiola S, Alonso J, Chatterji S, Lee S, Ormel J, et al. The global burden of mental disorders: An update from the WHO World Mental Health (WMH) Surveys. Epidemiol Psichiatr Soc. 2009;18:23–33. doi: 10.1017/S1121189X00001421.
    1. American Psychiatric Association . Diagnostic and statistical manual of mental disorders. 5. Arlington: American Psychiatric Publishing; 2013.
    1. Spitzer RL, Kroenke K, Williams JBW. Patient Health Questionaire Primary Study Group. Validation and utility of a self-report version of PRIME-MD: the PHQ primary care study. JAMA. 1999;282:1737–1744. doi: 10.1001/jama.282.18.1737.
    1. Lovibond PF, Lovibond SH. The structure of negative emotional states: Comparison of the Depression Anxiety Stress Scales (DASS) with the Beck Depression and Anxiety Inventories. Behav Res Ther. 1995;33:335–343. doi: 10.1016/0005-7967(94)00075-U.
    1. Beck AT, Epstein N, Brown G, Steer RA. An inventory for measuring clinical anxiety: Psychometric properties. J Consult. 1988;56:893. doi: 10.1037/0022-006X.56.6.893.
    1. Spielberger CD. State-trait anxiety inventory for adults. 1983.
    1. Clarke LA, Watson D. Theoretical and empirical issues in differentiating depression from anxiety. In: Becker J, Kleinman A, editors. Psychosocial aspects of mood disorders. Hillsdale: Lawrence Erlbaum Associates; 1991. pp. 39–65.
    1. Fischer EH, Goethe JW. Measurement of depression and anxiety for hospitalized depressed patients. Psychiatr Serv. 1997;48:705–707. doi: 10.1176/ps.48.5.705.
    1. Feldman LA. Distinguishing depression and anxiety in self-report: evidence from confirmatory factor analysis on nonclinical and clinical samples. J Consult Clin Psychol. 1993;61:631–638. doi: 10.1037/0022-006X.61.4.631.
    1. Tanaka-Matsumi J, Kameoka VA. Reliabilities and concurrent validities of popular self-report measures of depression, anxiety, and social desirability. J Consult Clin Psychol. 1986;54:328. doi: 10.1037/0022-006X.54.3.328.
    1. Balsamo M, Cataldi F, Carlucci L, Padulo C, Fairfield B. Assessment of late-life depression via self-report measures: A review. Clin Interv Aging. 2018;13:2021. doi: 10.2147/CIA.S114100.
    1. Balsamo M, Cataldi F, Carlucci L, Fairfield B. Assessment of anxiety in older adults: A review of self-report measures. Clin Interv Aging. 2018;13:573.15. doi: 10.2147/CIA.S114100.
    1. Zung WWK. A rating instrument for anxiety disorders. Psychosomatics. 1971;12:371–379. doi: 10.1016/S0033-3182(71)71479-0.
    1. Zung WWK. A self-rating depression scale. Arch Gen Psychiatry. 1965;12(1):63–70. doi: 10.1001/archpsyc.1965.01720310065008.
    1. Dunstan DA, Scott N, Todd AK. Screening for anxiety and depression: reassessing the utility of the Zung scales. BMC Psychiatry. 2017;17:329. doi: 10.1186/s12888-017-1489-6.
    1. Dunstan DA, Scott N. Assigning clinical significance and symptom severity using the Zung scales: Levels of misclassification arising from confusion between Index and Raw scores. Depress Res Treat. 2018;2018:9250972.
    1. Zung WWK. How normal is anxiety? Durham: Upjohn; 1980.
    1. Zung WWK. The measurement of affects: Depression and anxiety. Mod Probl Pharmacopsychiatry. 1974;7:170–188. doi: 10.1159/000395075.
    1. Dunstan DA, Scott N. Clarification of the cut-off score for Zung’s Self-rating Depression Scale. BMC Psychiatry. 2019;19:177. doi: 10.1186/s12888-019-2161-0.
    1. Habibzadeh F, Habibzadeh P, Yadollahie M. On determining the most appropriate test cut-off value: the case of tests with continuous results. Biochem Medica. 2016;26:297–307. doi: 10.11613/BM.2016.034.
    1. Youden WJ. Index for rating diagnostic tests. Cancer. 1950;3(1):32–35. doi: 10.1002/1097-0142(1950)3:1<32::AID-CNCR2820030106>;2-3.
    1. Searle SR. Linear Models. New York: Wiley; 1971.
    1. Akobang AK. Understanding diagnostic tests 3: Receiver operating characteristic curves. Acta Paediatr. 2007;96:644–647. doi: 10.1111/j.1651-2227.2006.00178.x.
    1. Balsamo M, Imperatori C, Sergi MR, Belvederi Murri M, Continisio M, Tamburello A, Innamorati M, Saggino A. Cognitive vulnerabilities and depression in young adults: An ROC curves analysis. Depress Res Treat. 2013;2013:407602.
    1. Balsamo M, Saggino A. Determining a diagnostic cut-off on the Teate Depression Inventory. Neuropsychiatr Dis Treat. 2014;10:987. doi: 10.2147/NDT.S55706.
    1. Hanley JA, McNeil BJ. The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology. 1982;143(1):29–36. doi: 10.1148/radiology.143.1.7063747.
    1. Ridge SE, Vizard AL. Determination of the optimal cutoff value for a serological assay: An example using the Johne’s absorbed EIA. J Clin Microbiol. 1993;31:1256–1261. doi: 10.1128/JCM.31.5.1256-1261.1993.
    1. McEvoy PM, Grove R, Slade T. Epidemiology of anxiety disorders in the Australian general population: Findings in the 2007 Australian National Survey of Mental Health and Wellbeing. Aust N Z J Psychiatry. 2011;45:957–967. doi: 10.3109/00048674.2011.624083.
    1. Nieuwhenuijsen K, de Boer AGEM, Verbeek JHAM, Blonk RWB, van Dijk FJH. The Depression Anxiety Stress Scales (DASS): Detecting anxiety disorder and depression in employees absent from work because of mental health problems. Occup Environ Med. 2003;60:i77–i82. doi: 10.1136/oem.60.suppl_1.i77.
    1. Tran TD, Tran T, Fisher J. Validation of the depression anxiety stress scales (DASS) 21 as a screening instrument for depression and anxiety in a rural community-based cohort of northern Vietnamese women. BMC Psychiatry. 2013;13(1):24. doi: 10.1186/1471-244X-13-24.

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