Stratifying Risk for Cognitive Decline in Older Adult Populations using the Geriatric Depression Scale.

Journal of psychiatry and cognitive behaviour Pub Date : 2024-01-01 Epub Date: 2024-03-18
Mirnova E Ceïde, Sarah Wang, Matthew R Lootens, Aviva Cantor, Joe Verghese, David W Lounsbury
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Abstract

Objectives: Late-life psychological symptoms in older adults such as depression and apathy have been increasingly associated with increased risk of cognitive and functional decline. The goal of this study was to conduct a confirmatory factor analysis of the Geriatric Depression Scale (GDS), pooling 3 unique cohorts of older adults to 1) develop a novel measurement model that distinguishes apathy from other domains of depression including dysphoria and cognitive concern and 2) evaluate if the measurement model distinguishes older adult populations with varied risk for cognitive decline.

Methods: We pooled the baseline waves of three older adult cohorts (N=1421). With the aim of partitioning apathy from other constructs that compose the GDS and with a PCA suggesting 3-component solution, we then conducted a confirmatory factor analysis (CFA) using lavaan and less R.

Results: CFA yielded 3 factors: dysphoria, apathy, and cognitive concern. All the dysphoria, apathy, and cognitive concern factors showed acceptable unidimensionality with α=.76, .59, and .54, respectively. The Cognitive Risk Primary Care cohort had significantly higher mean dysphoria, apathy and cognitive concern scales.

Conclusions: This culturally, linguistically, and educationally diverse sample population yielded factors with acceptable reliability and good face validity. This strategy has resulted in a generalizable measurement model to identify people at risk for Alzheimer's disease and related dementia. In particular, the apathy scale score can be used to identify older adults at risk for cognitive and functional decline across research and clinical settings.

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使用老年抑郁量表对老年人认知能力下降的风险进行分层。
目的:老年人的晚年心理症状,如抑郁和冷漠,越来越多地与认知和功能衰退的风险增加相关。本研究的目的是对老年抑郁量表(GDS)进行验证性因素分析,汇集3个独特的老年人队列,以1)开发一种新的测量模型,将冷漠与其他抑郁领域(包括不安和认知担忧)区分开来;2)评估该测量模型是否区分了具有不同认知衰退风险的老年人。方法:我们汇总了三个老年人队列(N=1421)的基线波。为了将冷漠从构成GDS的其他构念中分离出来,并使用PCA建议的3组分解决方案,我们随后使用lavaan和less r进行了验证性因素分析(CFA)。结果:CFA产生了3个因素:烦躁不安、冷漠和认知关注。焦虑、冷漠和认知关注因子均呈可接受的单维度,α=。分别为76、0.59和0.54。认知风险初级保健队列的平均焦虑、冷漠和认知关注量表显著较高。结论:这个文化、语言和教育上多样化的样本人口产生了可接受的信度和良好的面效度。这一策略产生了一个可推广的测量模型,用于识别有阿尔茨海默病和相关痴呆症风险的人群。特别是,在研究和临床环境中,冷漠量表得分可用于识别有认知和功能下降风险的老年人。
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