The Inventory Of Depressive Symptomatology (IDS-C(28)) is more sensitive to changes in depressive symptomatology than the Hamilton Depression Rating Scale (HAMD(17)) in patients with mild major, minor or subsyndromal depression
- PMID: 21132437
- DOI: 10.1007/s00406-010-0175-1
The Inventory Of Depressive Symptomatology (IDS-C(28)) is more sensitive to changes in depressive symptomatology than the Hamilton Depression Rating Scale (HAMD(17)) in patients with mild major, minor or subsyndromal depression
Abstract
Depression rating scales play a decisive role in the assessment of the severity of depression and the evaluation of the efficacy of antidepressant treatments. The Hamilton Depression Rating Scale (HAMD) is regarded as the 'gold standard'; nevertheless, studies suggest that the Inventory of Depressive Symptomatology (IDS) is more sensitive to detect symptom changes. The aim of the present study was to investigate whether the IDS is more sensitive in detecting changes in depression symptoms in patients with mild major, minor or subsyndromal depression (MIND). Biweekly IDS-C(28) and HAMD(17) data from 340 patients of a 10-week randomized, placebo-controlled trial comparing the effectiveness of sertraline and cognitive-behavioural therapy in patients with MIND were analysed. We investigated sensitivity to change for both scales (1) from assessment-to-assessment, (2) in relation to depression severity level, and (3) in relation to DSM-IV depression criterion symptoms. The IDS-C(28) was more sensitive in detecting changes in depression symptomatology over the treatment course as well as for different severity levels, especially in patients with a low depression severity. It assesses the DSM-IV criteria more thoroughly, is better able to track the change of cognitive symptoms and to identify residual symptoms. Both scales are well able to assess depressive symptomatology. However, the IDS-C(28) surpasses the HAMD(17) in detecting small changes especially in the core symptoms of depression. This is important for an optimal treatment by capturing early improvements, enabling prompt reactions and detecting residual symptoms.
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