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军事样本中记忆抱怨量表与PAI认知偏差量表的比较

Comparison of the Memory Complaints Inventory and the PAI Cognitive Bias Scale in a Military Sample.

作者信息

Armistead-Jehle Patrick, Ingram Paul B

机构信息

Munson Army Health Center, Fort Leavenworth, Leavenworth, KS, USA.

Department of Psychological Sciences, Texas Tech University, Lubbock, TX, USA.

出版信息

Arch Clin Neuropsychol. 2023 Feb 18;38(2):270-275. doi: 10.1093/arclin/acac079.

Abstract

OBJECTIVE

The Memory Complaints Inventory (MCI) is a stand-alone memory-based symptom validity test (SVT). The measure is promising and has been used with relative frequency, but requires additional research (Armistead-Jehle & Shura, 2022). The current study sought to expand the empirical base of the MCI by comparing it to the Cognitive Bias Scale, a new symptom validity measure assessing cognitive over reporting on the Personality Assessment Inventory (PAI).

METHOD

Retrospective review of 273 military service members seen for neuropsychological evaluation and administered both the PAI and MCI.

RESULTS

Area under the curve values for the MCI overall mean score and MCI implausible scales for a PAI Cognitive Bias Scale (CBS) cut score of >14 were large in effect (0.77 and 0.78, respectively). The effect size between those that passed and failed the CBS on the mean of MCI scales was also large (d = 1.13). Classification statistics indicated that a cut score of 52% on the mean MCI scales and 29% on the mean MCI implausible subscales indicated specificities of 0.94 and 0.93 and sensitivities of 0.30 and 0.29, respectively.

CONCLUSIONS

These data support the MCI as a cognitive SVT relative to the PAI CBS. We offer guidance on how to integrate these SVT measures in military samples.

摘要

目的

记忆投诉量表(MCI)是一种独立的基于记忆的症状效度测试(SVT)。该测量方法很有前景且已得到相对频繁的使用,但仍需要更多研究(阿米斯特德 - 杰勒和舒拉,2022年)。本研究旨在通过将MCI与认知偏差量表进行比较来扩大其经验基础,认知偏差量表是一种新的症状效度测量方法,用于评估在人格评估问卷(PAI)上认知过度报告的情况。

方法

对273名接受神经心理学评估并同时接受PAI和MCI测试的军人进行回顾性研究。

结果

对于PAI认知偏差量表(CBS)得分>14的情况,MCI总体平均得分和MCI不可信量表的曲线下面积值效应较大(分别为0.77和0.78)。在MCI量表平均值上,通过和未通过CBS的人之间的效应量也很大(d = 1.13)。分类统计表明,MCI量表平均值的52%和MCI不可信子量表平均值的29%的临界值分别表明特异性为0.94和0.93,敏感性为0.30和0.29。

结论

这些数据支持MCI作为相对于PAI CBS的认知SVT。我们提供了关于如何在军事样本中整合这些SVT测量方法的指导。

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