Defining hospital anxiety and depression scale (HADS) structure by confirmatory factor analysis: a contribution to validation for oncological settings

Abstract

Background: Despite its popularity, not a definitive word has yet been said about the latent structure of the Hospital Anxiety and Depression Scale (HADS). The present work is a contribution to this issue: statistically identifying the best tool structure helps in understanding which constructs the tool actually detects.

Participants and methods: Five hundred and twelve Italian consecutive hospitalized cancer patients completed the HADS together with a form for the collection of personal and clinical data. Two confirmatory factor analyses (CFAs) were carried out to test the validity of both two- and one-factor models, whereas qualitative and quantitative (i.e. Akaike information criterion) indices were used to assess which model among them would fit better with the observed data. Finally, two multigroup CFAs were carried out to test the factorial invariance across gender and disease phase (diagnostic, therapeutic) of the best-fitting model.

Results: Although both considered models provide a good fit to the observed data, the two-factor model is more adequate; it is invariant across gender and disease phase.

Conclusions: The present study gives evidence for using HADS to detect anxious and depressive states separately as originally suggested by its authors. Given that this work involved only Italian cancer inpatients, replications in different cultural/national contexts are recommended.