Comparing the Performance of the HADS and the GDS-15 in the AIBL Study.

Screening measures such as the 15-item Geriatric Depression Scale (GDS-15) (Sheikh and Yesavage, 1986) and the Hospital Anxiety and Depression Scale (HADS) (Zigmond and Snaith, 1983) are important tools in the recognition of depressive symptoms in older people. While these measures are widely used, there is evidence of specific weaknesses in some cohorts and contexts, with the GDS15 showing limitations in the context of cognitive impairment (Gilley and Wilson, 1997), and the depression subscale of the HADS (HADS-D) losing sensitivity in the context of older participants in hospital inpatient settings (Davies et al., 1993). We have conducted a study to compare the performance of the GDS-15 and the HADS-D in a large cohort of older people with varying cognitive profiles ranging from cognitive health to Alzheimer’s disease (AD), and to investigate whether cognitive, health, or lifestyle factors demonstrate a relationship with GDS-15 and HADS-D scores. Analysis was performed on data (N = 972) collected for the Australian Imaging, Biomarkers and Lifestyle (AIBL) study at its second time point in 2008–2009 (mean age 73.8 years; Range = 61.41–97.2) (Ellis et al., 2009; 2014). The Healthy Control (HC) group comprised 692 participants; the Mild Cognitive Impairment (MCI) group 83 participants; and the AD group 197 participants, diagnosed by standard criteria as outlined in the original AIBL papers. Missing depression scores were concentrated among those participants with an AD diagnosis (25.9% GDS15; 27.9% HADS-D), with fewer missing scores in the MCI group (10.8% GDS-15; 6% HADS-D) and HC group (4.2% GDS-15; 3.6% HADS-D). Additional variables analyzed were: Physical activity Metabolic Equivalent Task (MET)-minutes; the Mini-Mental State Exam (MMSE); and the Clinical Dementia Rating Scale sum of boxes score (CDR-SB). Participants were grouped based on cut-off points for depressive symptoms, i.e. GDS-15 score of 5 and/or a HADS-D score of 8 (Bjelland et al., 2002; Wancata et al., 2006). Accordingly, participants were coded as “GDS+”, “GDS–”, “HADS+”, or “HADS–”. Participants were also assigned a binary code based on having concordant or discordant HADS-D or GDS15 scores. Concordant codes were assigned if participants had both GDS-15+ and HADSD+ classifications, or alternatively GDS-15– and HADS-D– classifications. Discordant codes were assigned based on participants having HADS-D+ and GDS-15– classifications, or HADS-D–, and GDS15+ classifications. Forty-five participants (5.1% of the cohort) were identified as having depressive symptoms according to the HADS-D, while 82 (9.3%) were classified by the GDS-15 as having depressive symptoms. This relatively low prevalence likely reflects that participants had been screened to ensure they were not depressed before entry to the study at baseline. Not only did the GDS-15 identify the presence of depressive symptoms in nearly twice as many participants as the HADS-D, but it also identified these symptoms in a substantially different set of participants. Indeed, of the 71 GDS15+ participants for whom a HADS-D score was recorded, 48 were classified as HADS-D–. The measures’ patterns of classification within each of the clinical groups (HC, MCI, and AD) were similar. According to both the HADS-D and the GDS-15, participants in the MCI and AD groups were more likely to be experiencing depressive symptoms than cognitively healthy older adults. The GDS-15 and HADS-D displayed similar patterns of correlation with other study variables. Age had a weak positive correlation with the GDS-15 (rs (885) = 0.23, p = <0.01) and HADS-D (rs (887) = 0.21, p = <0.01). MMSE score had a weak negative correlation with the GDS15 (rs (880) =−0.32, p =<0.01) and HADS-D (rs (884) = −0.19, p = <0.01). The GDS-15 had a moderate positive correlation with CDR-SB score (rs (880) = 0.41, p = <0.01), while the HADS-D had a weak positive correlation, rs (884) = 0.22, p = <0.01. The GDS-15 had a weak negative correlation with Physical Activity MET-Minutes (rs (678) = −0.28, p = <0.01), while the HADS-D had a very weak to negligible negative correlation, rs (686) = −0.17, p = <0.01. Participants who received discordant GDS-15+/HADS-D– or GDS-15-/HADS-D+ classifications had similar demographic and cognitive profiles, according to the study’s key variables. However, there were clear differences between the discordant and concordant participant groups. Those who received concordant HADS-D+ and GDS-15+ classifications tended to have lower MMSE scores, higher CDR-SB scores, and a lower level of physical