Details

Autor(en) / Beteiligte

• Dunstan, Debra A
• Scott, Ned
• Todd, Anna K

Titel

Screening for anxiety and depression: reassessing the utility of the Zung scales

Ist Teil von

• BMC psychiatry, 2017-09, Vol.17 (1), p.329-329, Article 329

Ort / Verlag

England: BioMed Central Ltd

Erscheinungsjahr

2017

Link zum Volltext

Quelle

MEDLINE

Beschreibungen/Notizen

• While the gold standard for the diagnosis of mental disorders remains the structured clinical interview, self-report measures continue to play an important role in screening and measuring progress, as well as being frequently employed in research studies. Two widely-used self-report measures in the area of depression and anxiety are Zung's Self-Rating Depression Scale (SDS) and Self Rating Anxiety Scale (SAS). However, considerable confusion exists in their application, with clinical cut-offs often applied incorrectly. This study re-examines the credentials of the Zung scales by comparing them with the Depression Anxiety Stress Scale (DASS) in terms of their ability to predict clinical diagnoses of anxiety and depression made using the Patient Health Questionnaire (PHQ). A total sample of 376 adults, of whom 87 reported being in receipt of psychological treatment, completed the two-page version of the PHQ relating to depression and anxiety, together with the SDS, the SAS and the DASS. Overall, although the respective DASS scales emerged as marginally stronger predictors of PHQ diagnoses of anxiety and depression, the Zung indices performed more than acceptably in comparison. The DASS also had an advantage in discriminative ability. Using the current recommended cut-offs for all scales, the DASS has the edge on specificity, while the Zung scales are superior in terms of sensitivity. There are grounds to consider making the Zung cut-offs more conservative, and doing this would produce comparable numbers of 'Misses' and 'False Positives' to those obtained with the DASS. Given these promising results, further research is justified to assess the Zung scales ability against full clinical diagnoses and to further explore optimum cut-off levels.