Enhancing the Efficiency of Confrontation Naming Assessment for Aphasia Using Computer Adaptive Testing

利用计算机自适应测试提高失语症命名对抗评估的效率

阅读:1

Abstract

Purpose In this study, we investigated the agreement between the 175-item Philadelphia Naming Test (PNT; Roach, Schwartz, Martin, Grewal, & Brecher, 1996 ) and a 30-item computer adaptive PNT (PNT-CAT; Fergadiotis, Kellough, & Hula, 2015 ; Hula, Kellough, & Fergadiotis, 2015 ) created using item response theory (IRT) methods. Method The full PNT and the PNT-CAT were administered to 47 participants with aphasia in counterbalanced order. Latent trait-naming ability estimates for the 2 PNT versions were analyzed in a Bayesian framework, and the agreement between them was evaluated using correlation and measures of constant, variable, and total error. We also evaluated the extent to which individual pairwise differences were credibly greater than 0 and whether the IRT measurement model provided an adequate indication of the precision of individual score estimates. Results The agreement between the PNT and the PNT-CAT was strong, as indicated by high correlation ( r = .95, 95% CI [.92, .97]), negligible bias, and low variable and total error. The number of statistically robust pairwise score differences did not credibly exceed the Type I error rate, and the precision of individual score estimates was reasonably well predicted by the IRT model. Discussion The strong agreement between the full PNT and the PNT-CAT suggests that the latter is a suitable measurement of anomia in group studies. The relatively robust estimates of score precision also suggest that the PNT-CAT can be useful for the clinical assessment of anomia in individual cases. Finally, the IRT methods used to construct the PNT-CAT provide a framework for additional development to further reduce measurement error. Supplemental Material https://doi.org/10.23641/asha.8202176.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。