Regression-based formulas for predicting change in RBANS subtests with older adults
Regression-based formulas for predicting change in RBANS subtests with older adults
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DOI：
10.1016/j.acn.2004.07.007
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发表时间：
2005-05-01
影响因子：
2.6
通讯作者：
Adams, RL
中科院分区：
文献类型：
--
作者：
Duff, K;Schoenberg, MR;Adams, RL
重复的神经心理学评估在老年人中很常见，确定随时间的临床显著变化是一个重要问题。基于回归的预测公式已用于其他患者和健康对照样本，以根据初始性能和人口统计学变量预测随访测试性能。预测和观察到的随访性能之间的比较可以帮助临床医生确定个体患者的变化。目前的研究开发了基于回归的预测方程的12个子测试的可重复电池的神经心理状态评估（RBANS）在223个社区居住的老年人的样本。所有算法均包括初始测试性能和人口统计变量。然后在单独的老年人样本（n = 222）上验证这些算法。在验证样本中，观察到的和预测的随访评分之间存在最小差异，这表明预测公式对评估老年人的从业者有用。一个案例的例子，利用公式。(c)2004年美国国家神经心理学学会。由爱思唯尔有限公司出版。保留所有权利。
Repeated neuropsychological assessments are common with older adults, and the determination of clinically significant change across time is an important issue. Regression-based prediction formulas have been utilized with other patient and healthy control samples to predict follow-up test performance based on initial performance and demographic variables. Comparisons between predicted and observed follow-up performances can assist clinicians in making the determination of change in the individual patient. The current study developed regression-based prediction equations for the twelve subtests of the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) in a sample of 223 community dwelling older adults. All algorithms included both initial test performances and demographic variables. These algorithms were then validated on a separate elderly sample (n = 222). Minimal differences were present between Observed and Predicted follow-up scores in the Validation sample, suggesting that the prediction formulas would be useful for practitioners who assess older adults. A case example is presented that utilizes the formulas. (c) 2004 National Academy of Neuropsychology. Published by Elsevier Ltd. All rights reserved.