种族/民族与《国家人类健康行动计划》中的认知测量:关于稳健性的建议

James Iveniuk, Selena Zhong, Jocelyn Wilder, Gillian Marshall, Patricia Boyle, Jennifer Hanis-Martin, Louise Hawkley, Lissette M Piedra, Alicia R Riley, Haena Lee
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引用次数: 0

摘要

研究目的 在本研究中,我们对不同种族/民族群体的认知测量进行了研究,以制定一套偏差较小、包容性更强的测量方法,用于捕捉老年期认知的变化和衰退。方法 我们使用全国社会生活、健康和老龄化项目(NSHAP)第 2 轮(N=3377)和第 3 轮(N=4777)的数据,并检查该研究的蒙特利尔认知评估(MoCA-SA)调查调整版。我们采用探索性因子分析来探索不同种族/族裔群体的构型不变性。利用修正指数、双参数项目反应理论模型和分割样本测试,我们确定了那些似乎对种族偏差具有稳健性的项目。我们使用自我报告的痴呆诊断、工具性日常生活活动(IADLs)、痴呆的代理报告、痴呆相关死亡的代理报告以及痴呆相关死亡的国家死亡指数报告,检验了完整的(18 个项目)和简短的(4 个项目)MoCA-SAs 的预测有效性。结果 我们发现,在 NSHAP 的 MoCA-SA 中使用的 18 个测量指标中,有 4 个指标形成的量表对种族偏见的影响更强。简表对后果的预测与 NSHAP 的完整 MoCA-SA 一样好。简表与全表也有适度的相关性。讨论 虽然复杂的结构方程建模技术更适合用于确保 NSHAP 的种族测量不变性,但 MoCA-SA 的简表为研究人员提供了一种快速方法来进行稳健性检查,并了解他们记录的种族差异和关联是 "真实的 "还是人为偏差的产物。
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Race/ethnicity and the measurement of cognition in NSHAP: Recommendations for robustness
Objectives In this study, we examine the measurement of cognition in different racial/ethnic groups to move towards a less biased and more inclusive set of measures for capturing cognitive change and decline in older adulthood. Methods We use data from Round 2 (N=3377) and Round 3 (N=4777) of the National Social Life, Health, and Aging Project (NSHAP) and examine the study’s Survey Adjusted version of the Montreal Cognitive Assessment (MoCA-SA). We employ exploratory factor analyses to explore configural invariance by racial/ethnic group. Using modification indexes, two-parameter item response theory models, and split-sample testing, we identify items that seem robust to bias by race. We test the predictive validity of the full (18-item) and short (4-item) MoCA-SAs using self-reported dementia diagnosis, instrumental activities of daily living (IADLs), proxy reports of dementia, proxy reports of dementia-related death, and National Death Index reports of dementia-related death. Results We found that four measures out of the 18 used in NSHAP’s MoCA-SA formed a scale that was more robust to racial bias. The shortened form predicted consequential outcomes as well as NSHAP’s full MoCA-SA. The short form was also moderately correlated with the full form. Discussion Although sophisticated structural equation modeling techniques would be preferrable for assuaging measurement invariance by race in NSHAP, the shortened form of the MoCA-SA provides a quick way for researchers to carry out robustness checks and to see if the disparities and associations by race they document are “real” or the product of artifactual bias.
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