Affiliations: [a]
University of British Columbia (UBC), College for Interdisciplinary Studies, Graduate program in Neuroscience, Vancouver, Canada
| [b] Department of Medicine, UBC Division of Neurology, Vancouver, Canada
| [c] Clinic for Alzheimer Disease and Related Disorders, UBC Hospital, Vancouver, Canada
| [d]
Department of Medicine, UBC Division of Geriatric Medicine, Vancouver, Canada
| [e]
Djavad Mowafaghian Centre for Brain Health, Vancouver, Canada
Correspondence:
[*]
Correspondence to: Claudia Jacova, PhD and Amir A. Sepehry, MSc, PhD, School of Graduate Psychology, Pacific University, Hillsboro, OR, USA. Tel.: +1 503 352 3613; E-mails: [email protected] (C. Jacova), [email protected] (A.A. Sepehry).
Abstract: Presented herein is evidence for criterion, content, and convergent/discriminant validity of the NIMH-Provisional Diagnostic Criteria for depression of Alzheimer’s Disease (PDC-dAD) that were formulated to address depression in Alzheimer’s disease (AD). Using meta-analytic and systematic review methods, we examined criterion validity evidence in epidemiological and clinical studies comparing the PDC-dAD to Diagnostic and Statistical Manual of Mental Disorders fourth edition (DSM-IV), and International Classification of Disease (ICD 9) depression diagnostic criteria. We estimated prevalence of depression by PDC, DSM, and ICD with an omnibus event rate effect-size. We also examined diagnostic agreement between PDC and DSM. To gauge content validity, we reviewed rates of symptom endorsement for each diagnostic approach. Finally, we examined the PDC’s relationship with assessment scales (global cognition, neuropsychiatric, and depression definition) for convergent validity evidence. The aggregate evidence supports the validity of the PDC-dAD. Our findings suggest that depression in AD differs from other depressive disorders including Major Depressive Disorder (MDD) in that dAD is more prevalent, with generally a milder presentation and with unique features not captured by the DSM. Although the PDC are the current standard for diagnosis of depression in AD, we identified the need for their further optimization based on predictive validity evidence.
