State, trait, and accumulated features of the Alzheimer's Disease Assessment Scale Cognitive Subscale (ADAS‐Cog) in mild Alzheimer's disease

Abstract

AbstractBackgroundThe Alzheimer's Disease Assessment Scale Cognitive Subscale (ADAS‐Cog) is used to assess decline in memory, language, and praxis in Alzheimer's disease (AD).MethodsA latent state–trait model with autoregressive effects was used to determine how much of the ADAS‐Cog item measurement was reliable, and of that, how much of the information was occasion specific (state) versus consistent (trait or accumulated from one visit to the next).ResultsParticipants with mild AD (n = 341) were assessed four times over 24 months. Praxis items were generally unreliable as were some memory items. Language items were generally the most reliable, and this increased over time. Only two ADAS‐Cog items showed reliability >0.70 at all four assessments, word recall (memory) and naming (language). Of the reliable information, language items exhibited greater consistency (63.4% to 88.2%) than occasion specificity, and of the consistent information, language items tended to reflect effects of AD progression that accumulated from one visit to the next (35.5% to 45.3%). In contrast, reliable information from praxis items tended to come from trait information. The reliable information in the memory items reflected more consistent than occasion‐specific information, but they varied between items in the relative amounts of trait versus accumulated effects.ConclusionsAlthough the ADAS‐Cog was designed to track cognitive decline, most items were unreliable, and each item captured different amounts of information related to occasion‐specific, trait, and accumulated effects of AD over time. These latent properties complicate the interpretation of trends seen in ordinary statistical analyses of trials and other clinical studies with repeated ADAS‐Cog item measures.Highlights Studies have described unfavorable psychometric properties of the Alzheimer's Disease Assessment Scale Cognitive Subscale (ADAS‐Cog), bringing into question its ability to track changes in cognition uniformly over time. There remains a need to estimate how much of the ADAS‐Cog measurement is reliable, of that how much is occasion specific versus consistent, and of the consistent information, how much represents enduring traits versus autoregressive effects (i.e., effects of Alzheimer's disease [AD] progression carried over from one assessment to the next). A latent state–trait model with autoregressive effects in mild AD found most items to be unreliable, and each item to capture different amounts of occasion‐specific, trait, and autoregressive information. Language items, specifically, naming and the memory item word recall, were the most reliable. Psychometric idiosyncrasies of individual items complicate the interpretation of their summed score, biasing ordinary statistical analyses of repeated measures in mild AD. Future studies should consider item trajectories individually.