Kendell K

Martin CR

Morse RC

Rodgers J

Verrill MW

Background To determine the psychometric properties of the Hospital Anxiety and Depression Scale (HADS) in patients with breast cancer and determine the suitability of the instrument for use with this clinical group. Methods A cross-sectional design was used. The study used a pooled data set from three breast cancer clinical groups. The dependent variables were HADS anxiety and depression sub-scale scores. Exploratory and confirmatory factor analyses were conducted on the HADS to determine its psychometric properties in 110 patients with breast cancer. Seven models were tested to determine model fit to the data. Results Both factor analysis methods indicated that three-factor models provided a better fit to the data compared to two-factor (anxiety and depression) models for breast cancer patients. Clark and Watson\u27s three factor tripartite and three factor hierarchical models provided the best fit. Conclusion The underlying factor structure of the HADS in breast cancer patients comprises three distinct, but correlated factors, negative affectivity, autonomic anxiety and anhedonic depression. The clinical utility of the HADS in screening for anxiety and depression in breast cancer patients may be enhanced by using a modified scoring procedure based on a three-factor model of psychological distress. This proposed alternate scoring method involving regressing autonomic anxiety and anhedonic depression factors onto the third factor (negative affectivity) requires further investigation in order to establish its efficacy

Newcastle University E-Prints

English

An investigation into the psychometric properties of the Hospital Anxiety and Depression Scale in patients with breast cancer

https://eprint.ncl.ac.uk/file_store/production/56795/1DE6584E-6767-4192-B8C6-74EBC56931D9.pdf

An investigation into the psychometric properties of the Hospital Anxiety and Depression Scale in patients with breast cancer

Abstract

Similar works

Full text

Available Versions

Newcastle University E-Prints