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INTRODUCTIONThe Alzheimer's Disease Assessment Scale Cognitive Subscale (ADAS‐Cog), designed to assess the severity of cognitive dysfunction in Alzheimer's disease (AD,)1 has been a mainstay in AD studies since its creation in 1984.2 Given its widespread use, many studies have aimed to evaluate,1,3,4 modify,5,6 and optimize7–9 the ADAS‐Cog for its various applications. The commonest application of the ADAS‐Cog has been to track AD progression over time in clinical trials and observational studies.Several studies have questioned the ability of the ADAS‐Cog to track changes over time reliably.10 Discrepancies have been described between changes on the ADAS‐Cog scores and clinical improvement on measures such as the Clinician's Interview‐Based Impression of Change Plus caregiver input and the Goal Attainment Scaling.11 Studies have also described some unfavorable psychometric characteristics, including ceiling and floor effects,7,12,13 and poor test–retest reliability among 7 of 11 items including “following commands” (intraclass correlation coefficient [ICC] = 0.44), “ideational praxis” (ICC = 0.58), “word recognition” (ICC = 0.60), “spoken language ability” (ICC = 0.68), “word‐finding difficulty” (ICC = 0.69), and “comprehension” (ICC = 0.66).14 The minimum standards for reliability for research purposes are often considered to be ICC values >0.6 to 0.8.15–17 However, to guide clinical decision making, values of 0.9018
Alzheimer s & Dementia Translational Research & Clinical Interventions – Wiley
Published: Jan 1, 2023
Keywords: Alzheimer's Disease Assessment Scale Cognitive Subscale; Alzheimer's disease; cognition; latent state–trait autoregressive model; structural equation modelling
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