Article

A confirmatory factor analysis of the Hospital Anxiety and Depression scale: Comparing empirically and theoretically derived structures

Details

Citation

Dunbar M, Ford G, Hunt K & Der G (2000) A confirmatory factor analysis of the Hospital Anxiety and Depression scale: Comparing empirically and theoretically derived structures. British Journal of Clinical Psychology, 39 (1), pp. 79-94. https://doi.org/10.1348/014466500163121

Abstract
Objectives. To compare the fit of various factor solutions for the Hospital Anxiety and Depression scale (HAD; Zigmond and Snaith, 1983). Design. A cross-sectional postal survey was used to collect the data from community-based participants in the West of Scotland Twenty-07 study. Methods. The HAD scale, a 14-item self-administered measure of anxiety and depression, was completed by 2547 participants from three age cohorts (aged approximately 18, 39 and 58 years). Using confirmatory factor analyses four models suggested by prior exploratory factor analyses were compared to a model derived from Clark and Watson's (1991) tripartite theory of anxiety and depression. Results. The model derived from the tripartite theory of anxiety and depression (with factors labelled negative affectivity, anhedonic depression and autonomic anxiety) produced the closest lit to the data. This model produced a good fit in all three cohorts although group comparisons suggested that there were variations in the strength of some factor loadings across the three age groups. A model that had a hierarchical arrangement of the three factors in the tripartite model was also produced. This model fit the data equally as well as did the 'flat' tripartite model. Conclusions. Three factors appear to underlie the HAD scale. Research is needed that examines whether or not using sub-scales based on these factors increases the ability of the HAD scale to detect cases of anxiety and depression.

Journal
British Journal of Clinical Psychology: Volume 39, Issue 1

StatusPublished
Publication date31/12/2000
ISSN0144-6657
eISSN2044-8260

People (1)

Professor Kate Hunt

Professor Kate Hunt

Professor, Institute for Social Marketing