a Centre for Psychological Assessment , University Southern Queensland , Ipswich , Australia.
b School of Psychology and Counselling , University Southern Queensland , Ipswich , Australia.
Clin Neuropsychol. 2018 Apr;32(3):510-523. doi: 10.1080/13854046.2017.1357756. Epub 2017 Jul 28.
Discrepancy analyses refer to comparison methods that evaluate the relationship or differences between two measures in the same individual. A common type of discrepancy analysis involves the comparison of two trials within a measure, such as, Trails A and B of the Trail Making Test (TMT). The TMT is well-suited to this role as the two measures are highly correlated, assess similar underlying constructs, and most importantly demonstrate differential vulnerability to the impact of pathology. While the inclusion of these types of data in the form of difference scores or ratios has become more frequent, this information has been presented only for demographically adjusted subgroups and has not taken into account the level of performance of the comparison trial, Trails A.
The role and advantages of discrepancy analysis with the TMT stratified by level of Trails A performance were demonstrated with an Australian normative sample of 647 participants and a heterogeneous clinical sample consisting of 2,292 Australian and U.S.
The ability to differentiate between the influence of slowed visual scanning and/or graphomotor speed, and reduced mental flexibility was demonstrated by applying the normative data to clinical case discrepancies. The importance of accounting for the variability in discrepancy scores associated with the level of performance of Trails A was also highlighted.
A simple, efficient, and effective approach to examining the basis for differences between TMT-A and TMT-B performances is provided to examine the relative contributions of perceptual/motor abilities, and mental flexibility.
差异分析是指在同一个体中比较两种测量方法之间的关系或差异的比较方法。一种常见的差异分析类型涉及对同一测量中的两个试验进行比较,例如,连线测验 A 和 B(TMT)。TMT 非常适合这种作用,因为这两种测量方法高度相关,评估相似的潜在结构,最重要的是,对病理影响的敏感性不同。虽然这些类型的数据以差值分数或比率的形式包含在内变得越来越频繁,但这些信息仅针对经过人口统计学调整的亚组呈现,并且没有考虑到比较试验(Trails A)的表现水平。
通过对澳大利亚 647 名参与者的正常样本和包括澳大利亚和美国 2292 名参与者的异质临床样本进行分层,展示了 TMT 差异分析的作用和优势,其依据是 Trails A 的表现水平。
通过将规范数据应用于临床病例差异,证明了差异分析在区分视觉扫描速度和/或手眼协调速度减慢以及心理灵活性降低的影响方面的能力。还强调了考虑与 Trails A 表现水平相关的差异得分变异性的重要性。
提供了一种简单、高效和有效的方法来检查 TMT-A 和 TMT-B 表现差异的基础,以检查感知/运动能力和心理灵活性的相对贡献。