Christidi Foteini, Kararizou Evangelia, Triantafyllou Nikolaos, Anagnostouli Maria, Zalonis Ioannis
a Neuropsychological Laboratory, A' Department of Neurology, Aeginition Hospital, Medical School , National & Kapodistrian University , Athens , Greece.
Neuropsychol Dev Cogn B Aging Neuropsychol Cogn. 2015;22(6):667-78. doi: 10.1080/13825585.2015.1027650. Epub 2015 Mar 23.
We examined the contribution of demographics and cognitive background variables (processing speed, visuospatial skill, working memory, and interference control) on derived Trail Making Test (TMT) scores in a large sample of Greek healthy participants. We included 775 participants and administered the TMT (TMT-A and TMT-B) and the Wechsler Intelligence Adult Scale (WAIS). Direct (TMT-A & TMT-B time-to-completion) and derived [difference TMT-(B - A) & ratio TMT-(B/A)] scores were calculated. Demographics (age, age(2), education, and gender) and WAIS Full Intelligence Quotient significantly predicted the direct TMT-A (R(2) = 0.426) and TMT-B (R(2) = 0.593) scores and to a lesser extent, the derived TMT-(B - A) (R(2) = 0.343) and TMT-(B/A) (R(2) = 0.088) scores. In a subsample of 537 healthy participants who also completed the Stroop Neuropsychological Screening Test (SNST), demographics (age and education), WAIS Digit Symbol, Block Design, Arithmetic, and SNST accounted for 44.8% and 59.7% of the variance on TMT-A and TMT-B, and 32.5% and 9.6% of the variance on TMT-(B - A) and TMT-(B/A), respectively. We found minimal influence of Block Design and Arithmetic on TMT-(B - A) and an absence of significant influence of any cognitive variable on TMT-(B/A) score. Concluding, derived TMT scores are suggested as indices to detect impairment in cognitive flexibility across the adult life span, since they minimize the effect of demographics and other cognitive background variables.
我们在一大群希腊健康参与者中，研究了人口统计学和认知背景变量（处理速度、视觉空间技能、工作记忆和干扰控制）对改良版连线测验（TMT）分数的影响。我们纳入了775名参与者，并对其进行了TMT（TMT-A和TMT-B）以及韦氏成人智力量表（WAIS）测试。计算了直接分数（TMT-A和TMT-B的完成时间）和衍生分数[差异分数TMT-(B - A)以及比率分数TMT-(B/A)]。人口统计学因素（年龄、年龄平方、教育程度和性别）以及WAIS全量表智商显著预测了直接的TMT-A（R² = 0.426）和TMT-B（R² = 0.593）分数，对衍生的TMT-(B - A)（R² = 0.343）和TMT-(B/A)（R² = 0.088）分数的预测程度较低。在另外537名同样完成了斯特鲁普神经心理筛查测试（SNST）的健康参与者子样本中，人口统计学因素（年龄和教育程度）、WAIS数字符号、积木图案、算术以及SNST分别解释了TMT-A和TMT-B分数变异的44.8%和59.7%，以及TMT-(B - A)和TMT-(B/A)分数变异的32.5%和9.6%。我们发现积木图案和算术对TMT-(B - A)的影响极小，且任何认知变量对TMT-(B/A)分数均无显著影响。综上所述，改良版TMT分数建议作为检测成年期认知灵活性受损的指标，因为它们能将人口统计学和其他认知背景变量的影响降至最低。
