Multicomponent analysis of a digital Trail Making Test. Issue 1 (2nd January 2017)

• Record Type: Journal Article
• Authors: Fellows, Robert P.; Dahmen, Jessamyn; Cook, Diane; Schmitter-Edgecombe, Maureen
• Is Part Of: Clinical neuropsychologist. Volume 31:Issue 1(2017)
• Page Start: 154
• Page End: 167
• Publication Date: 2017-01-02
• Subjects: Trail Making Test -- executive functions -- speed -- medication management -- inhibition; Neuropsychology -- Periodicals; Neuropsychology -- Periodicals; Mental Disorders -- Periodicals; 612.805
• DOI: 10.1080/13854046.2016.1238510
• Languages: English
• ISSNs: 1385-4046

Abstract

Abstract: Objective : The purpose of the current study was to use a newly developed digital tablet-based variant of the TMT to isolate component cognitive processes underlying TMT performance.Method : Similar to the paper-based trail making test, this digital variant consists of two conditions, Part A and Part B. However, this digital version automatically collects additional data to create component subtest scores to isolate cognitive abilities. Specifically, in addition to the total time to completion and number of errors, the digital Trail Making Test (dTMT) records several unique components including the number of pauses, pause duration, lifts, lift duration, time inside each circle, and time between circles. Participants were community-dwelling older adults who completed a neuropsychological evaluation including measures of processing speed, inhibitory control, visual working memory/sequencing, and set-switching. The abilities underlying TMT performance were assessed through regression analyses of component scores from the dTMT with traditional neuropsychological measures.Results : Results revealed significant correlations between paper and digital variants of Part A ( r s = .541, p < .001) and paper and digital versions of Part B ( r s = .799, p < .001). Regression analyses with traditional neuropsychological measures revealed that Part A components were best predicted by speeded processing, while inhibitory control and visual/spatial sequencing were predictors of specific components of Part B. Exploratory analyses revealed that specific dTMT-B components were associated with a performance-based medication management task.Conclusions : Taken together, these results elucidate specific cognitive abilities underlying TMT performance, as well as the utility of isolating digital components.