Visual tests, touch responses: Computer-based neuropsychological tools

Abstract

Objective: Investigate three new computer tests of visual abilities relative to traditional paper-and-pencil (P&P) tests on groups with and without cerebral neurological impairment (CNI, Non-CNI) based on MRI and EEG criteria. The new tests employ an intuitive interface with audio instructions, touch responses, non-response prompts, and videography of test behavior. The Presidents Test was designed as an achievement-related measure of visual knowledge; the Railroad Test - visual perception and delayed recognition; and the Swamp Test - visual attention. Attitudes toward testing were assessed with an original Testing Experience Questionnaire (TEQ). Method: Of the 129 participants, 84 were women, 73 identified as non-White, average age 45.5 and education 14.3 years. Procedures included the new computer tests and a selection of standard neuropsychological measures including performance validity tests (PVT). Participants who failed two or three PVTs or had missing PVT data were excluded from main analyses, resulting in N = 115. Results: The new computer tests demonstrated adequate reliability. Correlations and factor analyses confirmed the computer tests as functioning in accordance with design. The Presidents Test was associated with academic achievement. The Railroad and Swamp Tests were linked to visual perception and visual attention. Correlations between computer total test duration time and traditional speed of processing tasks were modest. Computer and traditional tests demonstrated similar discriminability between CNI and Non-CNI groups. TEQ indicated positive attitudes toward testing in general, and computer testing in particular. Conclusions: The new computer tests evaluated in this study were found to be reliable, functioned to assess the designed cognitive domains, and discriminated between CNI and Non-CNI participants similarly to the traditional neuropsychological measures. Attitudes toward computer testing were favorable.

Keywords: computer cognitive testing; digital neuropsychological testing; diverse sample; touch responses; visual tests.