Development and evaluation of the HRSD-D, an image-based digital measure of the Hamilton rating scale for depression

Abstract

Abstract The Hamilton rating scale for depression (HRSD) is considered the gold standard for the assessment of major depressive disorder. Nevertheless, it has drawbacks such as reliance on retrospective reports and a relatively long administration time. Using a combination of an experience sampling method with mobile health technology, the present study aimed at developing and conducting initial validation of HRSD-D, the first digital image-based assessment of the HRSD. Fifty-three well-trained HRSD interviewers selected the most representative image for each item from an initial sample of images. Based on their responses, we developed the prototype of HRSD-D in two versions: trait-like (HRSD-DT) and state-like (HRSD-DS). HRSD-DT collects one-time reports on general tendencies to experience depressive symptoms; HRSD-DS collects daily reports on the experience of symptoms. Using a total of 1933 responses collected in a preclinical sample (N = 86), we evaluated the validity and feasibility of HRSD-D, based on participant reports of HRSD-DT at baseline, and 28 consecutive daily reports of HRSD-DS, using smartphone devices. HRSD-D showed good convergent validity with respect to the original HRSD, as evident in high correlations between HRSD-DS and HRSD (up to Bstd = 0.80). Our combined qualitative and quantitative analyses indicate that HRSD-D captured both dynamic and stable features of symptomatology, in a user-friendly monitoring process. HRSD-D is a promising tool for the assessment of trait and state depression and contributes to the use of mobile technologies in mental health research and practice.