An estimation of neuropsycological performance of adult female population of Turkey

Abstract

Ergonomic design of human-work and human-technological systems and products requires data of human cognitive and motor performances, in addition to data of physical capabilities. As the published research indicates, these performances may vary across the world populations. Some technologically advanced countries have already developed normative data for their populations. For the case of Turkey, there are only a few limited studies which are far from to satisfy the needs of the designers/engineers. Therefore, this study aims to investigate the cognitive and motor performances of adult female population of Turkey with the following specific objectives: (i) estimate the neuropsychological performances for the adult female population of Turkey in four main areas (attention, concentration and speed, memory and learning, intellectual function and motor function); and (ii) investigate the effects of age, education level, marital status and smoking on the performances. Cognitive and motor performances are measured by the widely accepted these neuropsychological tests: Digit Span, Corsi Span, Stroop-Color, Raven, Reaction Time and Purdue Pegboard. The participants of the study were 251 adult females aged from 18 to 92 with family origins from the seven regions of Turkey. The performance data collected through the application of six neuropsychological tests were statistically analyzed with respect to the objectives. The first objective, the estimations of the neuropsychological performances, was made. The second objective was achieved through the inferential statistics. The results indicate a significant negative effect of age on all performances. On the other, with increasing education most performances were increased. Other factors did not show any significant effect. All six performance measures had strong correlations among themselves. The comparison results with other nationalities show similarities as well as differences. The generated data may serve as a norm for clinical as well as ergonomic design applications.